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Glossary of VSA attributes

This Glossary alphabetically lists all attributes used in the VSAv20241206 database(s) held in the VSA. If you would like to have more information about the schema tables please use the VSAv20241206 Schema Browser (other Browser versions).
A B C D E F G H I J K L M
N O P Q R S T U V W X Y Z

S

NameSchema TableDatabaseDescriptionTypeLengthUnitDefault ValueUnified Content Descriptor
S14 nvssSource NVSS Integrated 1.4GHz flux density of radio source real 4 mJy   phot.flux.density;em.radio.750-1500MHz
S145Mag combo17CDFSSource COMBO17 Absolute restframe magnitude in 145/10 (synthetic narrow rectangular passband at 140-150 nm calculated from redshifted best_fit template, only calculated for objects classified as quasars) real 4 mag    
S280Mag combo17CDFSSource COMBO17 Absolute restframe magnitude in 280/40 (calculated from redshifted best_fit template, depending on redshift and filter extrapolation outside the COMBO-17 filter set can be necessary, only calculated for objects classified as galaxies; synthetic UV continuum rectangular passband at 260-300 nm) real 4 mag    
s_hp hipparcos_new_reduction GAIADR1 Scatter in Hipparcos magnitudes float 8 mag   stat.error;phot.mag;em.opt
sadtAreaID MultiframeEsoKeys SHARKSv20210222 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys SHARKSv20210421 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys ULTRAVISTADR4 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSDR1 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSDR2 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSDR3 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSDR4 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSDR5 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSDR6 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSv20120926 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSv20130417 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSv20140409 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSv20150108 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSv20160114 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSv20160507 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSv20170630 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSv20180419 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSv20201209 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSv20231101 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VHSv20240731 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIDEODR2 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIDEODR3 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIDEODR4 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIDEODR5 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIDEOv20111208 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIKINGDR2 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIKINGDR3 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIKINGDR4 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIKINGv20110714 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIKINGv20111019 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIKINGv20130417 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIKINGv20140402 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIKINGv20150421 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIKINGv20151230 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIKINGv20160406 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIKINGv20161202 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VIKINGv20170715 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCDEEPv20230713 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCDEEPv20240506 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCDR1 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCDR2 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCDR3 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCDR4 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCDR5 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20110816 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20110909 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20120126 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20121128 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20130304 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20130805 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20140428 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20140903 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20150309 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20151218 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20160311 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20160822 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20170109 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20170411 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20171101 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20180702 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20181120 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20191212 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20210708 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20230816 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VMCv20240226 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VSAQC SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VVVDR1 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VVVDR2 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VVVDR5 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VVVXDR1 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtAreaID MultiframeEsoKeys VVVv20110718 SADT Survey area ID {image primary HDU keyword: HIERARCH ESO OCS SADT AREA ID} int 4   -99999999  
sadtMaxJit MultiframeEsoKeys SHARKSv20210222 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys SHARKSv20210421 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys ULTRAVISTADR4 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSDR1 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSDR2 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSDR3 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSDR4 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSDR5 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSDR6 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSv20120926 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSv20130417 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSv20140409 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSv20150108 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSv20160114 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSv20160507 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSv20170630 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSv20180419 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSv20201209 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSv20231101 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VHSv20240731 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIDEODR2 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIDEODR3 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIDEODR4 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIDEODR5 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIDEOv20111208 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIKINGDR2 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIKINGDR3 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIKINGDR4 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIKINGv20110714 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIKINGv20111019 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIKINGv20130417 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIKINGv20140402 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIKINGv20150421 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIKINGv20151230 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIKINGv20160406 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIKINGv20161202 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VIKINGv20170715 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCDEEPv20230713 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCDEEPv20240506 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCDR1 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCDR2 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCDR3 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCDR4 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCDR5 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20110816 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20110909 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20120126 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20121128 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20130304 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20130805 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20140428 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20140903 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20150309 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20151218 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20160311 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20160822 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20170109 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20170411 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20171101 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20180702 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20181120 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20191212 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20210708 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20230816 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VMCv20240226 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VSAQC SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VVVDR1 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VVVDR2 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VVVDR5 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VVVXDR1 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtMaxJit MultiframeEsoKeys VVVv20110718 SADT maximum jitter size {image primary HDU keyword: HIERARCH ESO OCS SADT MAXJIT} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys SHARKSv20210222 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys SHARKSv20210421 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys ULTRAVISTADR4 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSDR1 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSDR2 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSDR3 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSDR4 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSDR5 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSDR6 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSv20120926 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSv20130417 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSv20140409 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSv20150108 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSv20160114 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSv20160507 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSv20170630 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSv20180419 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSv20201209 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSv20231101 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VHSv20240731 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIDEODR2 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIDEODR3 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIDEODR4 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIDEODR5 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIDEOv20111208 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIKINGDR2 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIKINGDR3 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIKINGDR4 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIKINGv20110714 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIKINGv20111019 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIKINGv20130417 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIKINGv20140402 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIKINGv20150421 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIKINGv20151230 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIKINGv20160406 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIKINGv20161202 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VIKINGv20170715 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCDEEPv20230713 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCDEEPv20240506 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCDR1 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCDR2 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCDR3 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCDR4 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCDR5 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20110816 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20110909 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20120126 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20121128 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20130304 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20130805 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20140428 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20140903 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20150309 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20151218 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20160311 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20160822 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20170109 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20170411 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20171101 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20180702 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20181120 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20191212 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20210708 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20230816 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VMCv20240226 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VSAQC SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VVVDR1 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VVVDR2 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VVVDR5 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VVVXDR1 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapX MultiframeEsoKeys VVVv20110718 SADT tile overlap in X {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPX} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys SHARKSv20210222 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys SHARKSv20210421 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys ULTRAVISTADR4 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSDR1 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSDR2 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSDR3 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSDR4 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSDR5 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSDR6 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSv20120926 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSv20130417 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSv20140409 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSv20150108 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSv20160114 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSv20160507 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSv20170630 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSv20180419 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSv20201209 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSv20231101 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VHSv20240731 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIDEODR2 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIDEODR3 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIDEODR4 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIDEODR5 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIDEOv20111208 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIKINGDR2 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIKINGDR3 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIKINGDR4 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIKINGv20110714 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIKINGv20111019 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIKINGv20130417 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIKINGv20140402 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIKINGv20150421 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIKINGv20151230 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIKINGv20160406 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIKINGv20161202 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VIKINGv20170715 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCDEEPv20230713 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCDEEPv20240506 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCDR1 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCDR2 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCDR3 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCDR4 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCDR5 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20110816 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20110909 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20120126 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20121128 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20130304 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20130805 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20140428 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20140903 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20150309 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20151218 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20160311 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20160822 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20170109 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20170411 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20171101 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20180702 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20181120 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20191212 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20210708 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20230816 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VMCv20240226 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VSAQC SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VVVDR1 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VVVDR2 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VVVDR5 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VVVXDR1 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtOverlapY MultiframeEsoKeys VVVv20110718 SADT tile overlap in Y {image primary HDU keyword: HIERARCH ESO OCS SADT OVERLAPY} real 4 arcsec -0.9999995e9  
sadtPattern MultiframeEsoKeys SHARKSv20210222 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys SHARKSv20210421 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys ULTRAVISTADR4 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSDR1 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSDR2 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSDR3 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSDR4 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSDR5 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSDR6 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSv20120926 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSv20130417 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSv20140409 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSv20150108 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSv20160114 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSv20160507 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSv20170630 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSv20180419 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSv20201209 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSv20231101 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VHSv20240731 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIDEODR2 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIDEODR3 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIDEODR4 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIDEODR5 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIDEOv20111208 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIKINGDR2 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIKINGDR3 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIKINGDR4 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIKINGv20110714 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIKINGv20111019 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIKINGv20130417 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIKINGv20140402 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIKINGv20150421 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIKINGv20151230 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIKINGv20160406 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIKINGv20161202 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VIKINGv20170715 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCDEEPv20230713 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCDEEPv20240506 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCDR1 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCDR2 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCDR3 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCDR4 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCDR5 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20110816 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20110909 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20120126 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20121128 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20130304 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20130805 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20140428 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20140903 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20150309 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20151218 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20160311 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20160822 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20170109 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20170411 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20171101 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20180702 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20181120 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20191212 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20210708 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20230816 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VMCv20240226 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VSAQC SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VVVDR1 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VVVDR2 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VVVDR5 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VVVXDR1 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtPattern MultiframeEsoKeys VVVv20110718 SADT pattern ID {image primary HDU keyword: HIERARCH ESO OCS SADT PATTERN} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys SHARKSv20210222 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys SHARKSv20210421 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys ULTRAVISTADR4 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSDR1 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSDR2 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSDR3 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSDR4 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSDR5 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSDR6 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSv20120926 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSv20130417 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSv20140409 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSv20150108 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSv20160114 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSv20160507 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSv20170630 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSv20180419 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSv20201209 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSv20231101 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VHSv20240731 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIDEODR2 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIDEODR3 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIDEODR4 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIDEODR5 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIDEOv20111208 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIKINGDR2 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIKINGDR3 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIKINGDR4 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIKINGv20110714 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIKINGv20111019 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIKINGv20130417 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIKINGv20140402 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIKINGv20150421 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIKINGv20151230 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIKINGv20160406 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIKINGv20161202 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VIKINGv20170715 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCDEEPv20230713 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCDEEPv20240506 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCDR1 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCDR2 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCDR3 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCDR4 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCDR5 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20110816 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20110909 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20120126 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20121128 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20130304 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20130805 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20140428 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20140903 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20150309 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20151218 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20160311 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20160822 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20170109 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20170411 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20171101 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20180702 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20181120 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20191212 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20210708 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20230816 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VMCv20240226 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VSAQC SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VVVDR1 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VVVDR2 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VVVDR5 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VVVXDR1 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtSurveyID MultiframeEsoKeys VVVv20110718 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
sadtTileDec MultiframeEsoKeys SHARKSv20210222 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys SHARKSv20210421 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys ULTRAVISTADR4 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSDR1 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSDR2 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSDR3 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSDR4 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSDR5 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSDR6 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSv20120926 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSv20130417 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSv20140409 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSv20150108 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSv20160114 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSv20160507 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSv20170630 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSv20180419 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSv20201209 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSv20231101 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VHSv20240731 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIDEODR2 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIDEODR3 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIDEODR4 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIDEODR5 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIDEOv20111208 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIKINGDR2 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIKINGDR3 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIKINGDR4 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIKINGv20110714 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIKINGv20111019 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIKINGv20130417 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIKINGv20140402 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIKINGv20150421 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIKINGv20151230 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIKINGv20160406 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIKINGv20161202 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VIKINGv20170715 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCDEEPv20230713 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCDEEPv20240506 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCDR1 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCDR2 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCDR3 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCDR4 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCDR5 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20110816 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20110909 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20120126 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20121128 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20130304 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20130805 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20140428 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20140903 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20150309 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20151218 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20160311 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20160822 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20170109 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20170411 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20171101 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20180702 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20181120 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20191212 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20210708 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20230816 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VMCv20240226 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VSAQC SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VVVDR1 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VVVDR2 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VVVDR5 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VVVXDR1 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileDec MultiframeEsoKeys VVVv20110718 SADT tile declination {image primary HDU keyword: HIERARCH ESO OCS SADT TILE DEC} real 4 DDMMSS.TTT -0.9999995e9  
sadtTileID MultiframeEsoKeys SHARKSv20210222 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys SHARKSv20210421 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys ULTRAVISTADR4 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSDR1 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSDR2 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSDR3 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSDR4 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSDR5 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSDR6 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSv20120926 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSv20130417 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSv20140409 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSv20150108 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSv20160114 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSv20160507 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSv20170630 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSv20180419 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSv20201209 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSv20231101 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VHSv20240731 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIDEODR2 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIDEODR3 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIDEODR4 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIDEODR5 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIDEOv20111208 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIKINGDR2 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIKINGDR3 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIKINGDR4 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIKINGv20110714 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIKINGv20111019 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIKINGv20130417 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIKINGv20140402 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIKINGv20150421 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIKINGv20151230 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIKINGv20160406 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIKINGv20161202 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VIKINGv20170715 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCDEEPv20230713 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCDEEPv20240506 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCDR1 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCDR2 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCDR3 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCDR4 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCDR5 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20110816 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20110909 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20120126 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20121128 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20130304 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20130805 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20140428 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20140903 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20150309 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20151218 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20160311 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20160822 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20170109 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20170411 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20171101 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20180702 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20181120 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20191212 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20210708 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20230816 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VMCv20240226 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VSAQC SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VVVDR1 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VVVDR2 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VVVDR5 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VVVXDR1 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileID MultiframeEsoKeys VVVv20110718 SADT tile ID within survey area {image primary HDU keyword: HIERARCH ESO OCS SADT TILE ID} varchar 64   NONE  
sadtTileOffAngle MultiframeEsoKeys SHARKSv20210222 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys SHARKSv20210421 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys ULTRAVISTADR4 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSDR1 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSDR2 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSDR3 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSDR4 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSDR5 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSDR6 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSv20120926 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSv20130417 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSv20140409 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSv20150108 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSv20160114 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSv20160507 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSv20170630 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSv20180419 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSv20201209 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSv20231101 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VHSv20240731 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIDEODR2 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIDEODR3 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIDEODR4 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIDEODR5 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIDEOv20111208 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIKINGDR2 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIKINGDR3 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIKINGDR4 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIKINGv20110714 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIKINGv20111019 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIKINGv20130417 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIKINGv20140402 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIKINGv20150421 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIKINGv20151230 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIKINGv20160406 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIKINGv20161202 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VIKINGv20170715 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCDEEPv20230713 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCDEEPv20240506 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCDR1 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCDR2 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCDR3 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCDR4 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCDR5 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20110816 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20110909 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20120126 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20121128 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20130304 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20130805 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20140428 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20140903 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20150309 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20151218 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20160311 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20160822 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20170109 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20170411 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20171101 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20180702 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20181120 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20191212 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20210708 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20230816 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VMCv20240226 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VSAQC SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VVVDR1 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VVVDR2 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VVVDR5 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VVVXDR1 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileOffAngle MultiframeEsoKeys VVVv20110718 SADT tile rotator offset angle {image primary HDU keyword: HIERARCH ESO OCS SADT TILE OFFANGLE} real 4 deg -0.9999995e9  
sadtTileRa MultiframeEsoKeys SHARKSv20210222 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys SHARKSv20210421 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys ULTRAVISTADR4 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSDR1 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSDR2 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSDR3 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSDR4 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSDR5 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSDR6 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSv20120926 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSv20130417 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSv20140409 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSv20150108 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSv20160114 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSv20160507 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSv20170630 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSv20180419 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSv20201209 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSv20231101 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VHSv20240731 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIDEODR2 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIDEODR3 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIDEODR4 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIDEODR5 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIDEOv20111208 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIKINGDR2 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIKINGDR3 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIKINGDR4 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIKINGv20110714 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIKINGv20111019 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIKINGv20130417 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIKINGv20140402 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIKINGv20150421 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIKINGv20151230 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIKINGv20160406 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIKINGv20161202 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VIKINGv20170715 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCDEEPv20230713 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCDEEPv20240506 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCDR1 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCDR2 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCDR3 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCDR4 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCDR5 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20110816 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20110909 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20120126 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20121128 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20130304 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20130805 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20140428 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20140903 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20150309 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20151218 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20160311 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20160822 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20170109 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20170411 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20171101 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20180702 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20181120 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20191212 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20210708 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20230816 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VMCv20240226 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VSAQC SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VVVDR1 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VVVDR2 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VVVDR5 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VVVXDR1 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
sadtTileRa MultiframeEsoKeys VVVv20110718 SADT tile RA {image primary HDU keyword: HIERARCH ESO OCS SADT TILE RA} real 4 HHMMSS.TTT -0.9999995e9  
satnum allwise_sc WISE Minimum sample at which saturation occurs in each band. Four character string, one character per band, that indicates the minimum SUTR sample in which any pixel in the profile-fitting area in all of the single-exposure images used to characterize this source was flagged as having reached the saturation level in the on-board WISE payload processing. If no pixels in a given band are flagged as saturated, the value for that band is "0". varchar 4      
satnum wise_allskysc WISE Minimum sample at which saturation occurs in each band.
Four character string, one character per band, that indicates the minimum SUTR sample in which any pixel in the profile-fitting area in all of the single-exposure images used to characterize this source was flagged as having reached the saturation level in the on-board WISE payload processing. If no pixels in a given band are flagged as saturated, the value for that band is "0".
char 4      
satnum wise_prelimsc WISE Minimum sample at which saturation occurs in each band
Four character string, one character per band, that indicates the minimum SUTR sample in which any pixel in the profile-fitting area in all of the single-exposure images used to characterize this source was flagged as having reached the saturation level in the on-board WISE payload processing. If no pixels in a given band are flagged as saturated, the value for that band is "0".
char 4      
saturatCorr sharksDetection SHARKSv20210222 saturation correction real 4   0.0 stat.param
saturatCorr sharksDetection SHARKSv20210421 saturation correction real 4   0.0 stat.param
saturatCorr ultravistaDetection, ultravistaMapRemeasurement ULTRAVISTADR4 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSDR1 saturation correction real 4   0.0  
saturatCorr vhsDetection VHSDR2 saturation correction real 4   0.0  
saturatCorr vhsDetection VHSDR3 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSDR4 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSDR5 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSDR6 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSv20120926 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSv20130417 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSv20140409 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSv20150108 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSv20160114 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSv20160507 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSv20170630 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSv20180419 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSv20201209 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSv20231101 saturation correction real 4   0.0 stat.param
saturatCorr vhsDetection VHSv20240731 saturation correction real 4   0.0 stat.param
saturatCorr videoDetection VIDEODR2 saturation correction real 4   0.0  
saturatCorr videoDetection VIDEODR3 saturation correction real 4   0.0 stat.param
saturatCorr videoDetection VIDEODR4 saturation correction real 4   0.0 stat.param
saturatCorr videoDetection VIDEODR5 saturation correction real 4   0.0 stat.param
saturatCorr videoDetection VIDEOv20111208 saturation correction real 4   0.0  
saturatCorr vikingDetection VIKINGDR2 saturation correction real 4   0.0  
saturatCorr vikingDetection VIKINGDR3 saturation correction real 4   0.0 stat.param
saturatCorr vikingDetection VIKINGDR4 saturation correction real 4   0.0 stat.param
saturatCorr vikingDetection VIKINGv20110714 saturation correction real 4   0.0  
saturatCorr vikingDetection VIKINGv20111019 saturation correction real 4   0.0  
saturatCorr vikingDetection VIKINGv20130417 saturation correction real 4   0.0 stat.param
saturatCorr vikingDetection VIKINGv20140402 saturation correction real 4   0.0 stat.param
saturatCorr vikingDetection VIKINGv20150421 saturation correction real 4   0.0 stat.param
saturatCorr vikingDetection VIKINGv20151230 saturation correction real 4   0.0 stat.param
saturatCorr vikingDetection VIKINGv20160406 saturation correction real 4   0.0 stat.param
saturatCorr vikingDetection VIKINGv20161202 saturation correction real 4   0.0 stat.param
saturatCorr vikingDetection VIKINGv20170715 saturation correction real 4   0.0 stat.param
saturatCorr vikingMapRemeasurement VIKINGZYSELJv20160909 saturation correction real 4   0.0 stat.param
saturatCorr vikingMapRemeasurement VIKINGZYSELJv20170124 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCDR1 saturation correction real 4   0.0  
saturatCorr vmcDetection VMCDR2 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCDR3 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCDR4 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCDR5 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20110816 saturation correction real 4   0.0  
saturatCorr vmcDetection VMCv20110909 saturation correction real 4   0.0  
saturatCorr vmcDetection VMCv20120126 saturation correction real 4   0.0  
saturatCorr vmcDetection VMCv20121128 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20130304 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20130805 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20140428 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20140903 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20150309 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20151218 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20160311 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20160822 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20170109 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20170411 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20171101 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20180702 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20181120 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20191212 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20210708 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20230816 saturation correction real 4   0.0 stat.param
saturatCorr vmcDetection VMCv20240226 saturation correction real 4   0.0 stat.param
saturatCorr vmcdeepDetection VMCDEEPv20230713 saturation correction real 4   0.0 stat.param
saturatCorr vmcdeepDetection VMCDEEPv20240506 saturation correction real 4   0.0 stat.param
saturatCorr vvvDetection VVVDR1 saturation correction real 4   0.0 stat.param
saturatCorr vvvDetection VVVDR2 saturation correction real 4   0.0 stat.param
saturatCorr vvvDetection, vvvDetectionPawPrints, vvvDetectionTiles VVVDR5 saturation correction real 4   0.0 stat.param
SC_CHI2PROB twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM The Chi² probability (based on the null hypothesis) that the unique source SRCID as detected by any of the observations is constant, that is, the minimum value of the EPIC probabilities in each detection, EP_CHI2PROB, is given. real 4      
SC_CHI2PROB xmm3dr4 XMM The Chi² probability (based on the null hypothesis) that the unique source SRCID as detected by any of the observations is constant, that is, the minimum value of the EPIC probabilities in each detection, EP_CHI2PROB, is given. float 8      
SC_DEC twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean Declination in degrees (J2000) of all the detections of the source SRCID (see DEC) weighted by the positional errors POSERR. float 8 degrees    
SC_DET_ML twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The total band detection likelihood of the source SRCID is the maximum of the likelihoods of all detections of this source (EP_8_DET_ML). real 4      
SC_DR_FIRST twoxmmi_dr3_v1_0 XMM This flag indicates in which catalogue in the 2XMM catalogue series (starting from 2XMM) this unique source first appeared. The flag is DR1 for 2XMM, DR2 for 2XMMi and DR3 for the present 2XMMi-DR3 catalogue. int 4      
SC_DR_LAST twoxmmi_dr3_v1_0 XMM This flag indicates in which catalogue in the 2XMM catalogue series (starting from 2XMM) the parameters of this unique source were last updated (e.g. due to the inclusion of one or more new detections which can add to, or even split, the source). The flag is DR1 for 2XMM, DR2 for 2XMMi and DR3 for the present 2XMMi-DR3 catalogue. int 4      
SC_EP_1_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean band 1 flux (0.2 - 0.5 keV) of all the detections of the source SRCID (see EP_1_FLUX) weighted by the errors (EP_1_FLUX_ERR), in erg/cm2/s. real 4 erg/cm**2/s    
SC_EP_1_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Error on the weighted mean band 1 flux in SC_EP_1_FLUX. real 4 erg/cm**2/s    
SC_EP_2_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean band 2 flux (0.5 - 1.0 keV) of all the detections of the source SRCID (see EP_2_FLUX) weighted by the errors (EP_2_FLUX_ERR), in erg/cm2/s. real 4 erg/cm**2/s    
SC_EP_2_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Error on the weighted mean band 2 flux in SC_EP_2_FLUX. real 4 erg/cm**2/s    
SC_EP_3_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean band 3 flux (1.0 - 2.0 keV) of all the detections of the source SRCID (see EP_3_FLUX) weighted by the errors (EP_3_FLUX_ERR), in erg/cm2/s. real 4 erg/cm**2/s    
SC_EP_3_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Error on the weighted mean band 3 flux in SC_EP_3_FLUX. real 4 erg/cm**2/s    
SC_EP_4_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean band 4 flux (2.0 - 4.5 keV) of all the detections of the source SRCID (see EP_4_FLUX) weighted by the errors (EP_4_FLUX_ERR), in erg/cm2/s. real 4 erg/cm**2/s    
SC_EP_4_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Error on the weighted mean band 4 flux in SC_EP_4_FLUX. real 4 erg/cm**2/s    
SC_EP_5_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean band 5 flux (4.5 - 12 keV) of all the detections of the source SRCID (see EP_5_FLUX) weighted by the errors (EP_5_FLUX_ERR), in erg/cm2/s. real 4 erg/cm**2/s    
SC_EP_5_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Error on the weighted mean band 5 flux in SC_EP_5_FLUX. real 4 erg/cm**2/s    
SC_EP_8_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean total band flux (0.2 - 12 keV) of all the detections of the source SRCID (see EP_8_FLUX) weighted by the errors (EP_8_FLUX_ERR), in erg/cm2/s. real 4 erg/cm**2/s    
SC_EP_8_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Error on the weighted mean total band flux in SC_EP_8_FLUX. real 4 erg/cm**2/s    
SC_EP_8_FMAX xmm3dr4 XMM The maximum EPIC band 8 flux (EP_8_FLUX) amongst any of the constituent detections of the unique source. real 4 erg/cm**2/s    
SC_EP_8_FMAX_ERR xmm3dr4 XMM The error on the maximum EPIC band 8 flux (EP_8_FLUX_ERR) amongst any of the constituent detections of the unique source. real 4 erg/cm**2/s    
SC_EP_8_FMIN xmm3dr4 XMM The minimum EPIC band 8 flux (EP_8_FLUX) amongst any of the constituent detections of the unique source. real 4 erg/cm**2/s    
SC_EP_8_FMIN_ERR xmm3dr4 XMM The error on the minimum EPIC band 8 flux (EP_8_FLUX_ERR) amongst any of the constituent detections of the unique source. real 4 erg/cm**2/s    
SC_EP_9_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean band 9 flux (0.5 - 4.5 keV) of all the detections of the source SRCID (see EP_9_FLUX) weighted by the errors (EP_9_FLUX_ERR), in erg/cm2/s. real 4 erg/cm**2/s    
SC_EP_9_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Error on the weighted mean band 9 flux in SC_EP_9_FLUX. real 4 erg/cm**2/s    
SC_EXT_ML twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The total band detection likelihood of the extended source SRCID is the average of the extent likelihoods of all detections of this source (EP_EXTENT_ML). real 4      
SC_EXTENT twoxmmi_dr3_v1_0, xmm3dr4 XMM The total band extent of the source SRCID is the weighted average of the EPIC extents of all detections of this source (EP_EXTENT). real 4 arcsec    
SC_FVAR xmm3dr4 XMM The fractional excess variance of the unique source. It is the value corresponding to the exposure and instrument that shows the lowest probability of being constant (i.e. it is the PN_FVAR, M1_FVAR or M2_FVAR value corresponding to EP_CHI2PROB, SC_CHI2PROB). float 8      
SC_FVARERR xmm3dr4 XMM The error on the fractional excess variance of the unique source. float 8      
SC_HR1 twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean hardness ratio of the bands 1 and 2 of all the detections of the source SRCID (EP_HR1) weighted by the errors(EP_HR1_ERR). real 4      
SC_HR1_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Error on the weighted mean hardness ratio in SC_HR1. real 4      
SC_HR2 twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean hardness ratio of the bands 2 and 3 of all the detections of the source SRCID (EP_HR2) weighted by the errors(EP_HR2_ERR). real 4      
SC_HR2_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Error on the weighted mean hardness ratio in SC_HR2. real 4      
SC_HR3 twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean hardness ratio of the bands 3 and 4 of all the detections of the source SRCID (EP_HR3) weighted by the errors(EP_HR3_ERR). real 4      
SC_HR3_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Error on the weighted mean hardness ratio in SC_HR3. real 4      
SC_HR4 twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean hardness ratio of the bands 4 and 5 of all the detections of the source SRCID (EP_HR4) weighted by the errors(EP_HR4_ERR). real 4      
SC_HR4_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Error on the weighted mean hardness ratio in SC_HR4. real 4      
SC_POSERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The error of the weighted mean position given in SC_RA and SC_DEC in arcseconds. real 4 arcsec    
SC_RA twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The mean Right Ascension in degrees (J2000) of all the detections of the source SRCID (see RA) weighted by the positional errors POSERR. float 8 degrees    
SC_SUM_FLAG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM The summary flag for the unique source SRCID is taken to be the worst flag of all detections of this source (SUM_FLAG). int 4      
SC_SUM_FLAG xmm3dr4 XMM The summary flag for the unique source SRCID is taken to be the worst flag of all detections of this source (SUM_FLAG). smallint 2      
SC_VAR_FLAG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM The variability flag for the unique source SRCID is set to VAR_FLAG of the most variable detection of this source. varchar 5      
SC_VAR_FLAG xmm3dr4 XMM The variability flag for the unique source SRCID is set to VAR_FLAG of the most variable detection of this source (0=False, 1=True). bit 1      
scan twomass_psc TWOMASS The nightly scan number in which the source was detected. smallint 2     meta.number
scan twomass_scn TWOMASS Scan number (unique within date). smallint 2     meta.number
scan twomass_sixx2_scn TWOMASS scan number (unique within date) smallint 2      
scan twomass_xsc TWOMASS scan number (unique within date). smallint 2     meta.number
scan_direction_mean_k1 gaia_source GAIAEDR3 Mean position angle of scan directions across the source real 4 degrees   pos.posAng;stat.mean
scan_direction_mean_k1 gaia_source, tgas_source GAIADR1 Mean position angle of scan directions across the source real 4 degrees    
scan_direction_mean_k2 gaia_source GAIAEDR3 Mean position angle of scan directions across the source real 4 degrees   pos.posAng;stat.mean
scan_direction_mean_k2 gaia_source, tgas_source GAIADR1 Mean position angle of scan directions across the source real 4 degrees    
scan_direction_mean_k3 gaia_source GAIAEDR3 Mean position angle of scan directions across the source real 4 degrees   pos.posAng;stat.mean
scan_direction_mean_k3 gaia_source, tgas_source GAIADR1 Mean position angle of scan directions across the source real 4 degrees    
scan_direction_mean_k4 gaia_source GAIAEDR3 Mean position angle of scan directions across the source real 4 degrees   pos.posAng;stat.mean
scan_direction_mean_k4 gaia_source, tgas_source GAIADR1 Mean position angle of scan directions across the source real 4 degrees    
scan_direction_strength_k1 gaia_source GAIAEDR3 Degree of concentration of scan directions across the source real 4     stat.value
scan_direction_strength_k1 gaia_source, tgas_source GAIADR1 Degree of concentration of scan directions across the source real 4      
scan_direction_strength_k2 gaia_source GAIAEDR3 Degree of concentration of scan directions across the source real 4     stat.value
scan_direction_strength_k2 gaia_source, tgas_source GAIADR1 Degree of concentration of scan directions across the source real 4      
scan_direction_strength_k3 gaia_source GAIAEDR3 Degree of concentration of scan directions across the source real 4     stat.value
scan_direction_strength_k3 gaia_source, tgas_source GAIADR1 Degree of concentration of scan directions across the source real 4      
scan_direction_strength_k4 gaia_source GAIAEDR3 Degree of concentration of scan directions across the source real 4     stat.value
scan_direction_strength_k4 gaia_source, tgas_source GAIADR1 Degree of concentration of scan directions across the source real 4      
scan_key twomass_psc TWOMASS Unique identification number of the record in the Scan Information Table that corresponds to the survey scan in which this source was detected. int 4     meta.id
scan_key twomass_scn TWOMASS the unique identification number for this scan. int 4     meta.id
scan_key twomass_sixx2_xsc TWOMASS key to scan data record in "scan DB" int 4      
scan_key twomass_xsc TWOMASS key to scan data record in "scan DB". int 4     meta.id
scosID twompzPhotoz TWOMPZ SuperCOSMOS Source table (objID) {image primary HDU keyword: SCOS_objID} bigint 8   -99999999 meta.id
scosID wiseScosPhotoz, wiseScosPhotozRejects WISExSCOSPZ SuperCOSMOS Source table (objID) {image primary HDU keyword: objID} bigint 8   -99999999 meta.id
scosID wiseScosSvm WISExSCOSPZ SuperCOSMOS Source table (objID) {image primary HDU keyword: scos_objID} bigint 8   -99999999 meta.id
sd twomass_scn TWOMASS Scanning direction: "n" = north-going, "s" = south-going. varchar 1     pos.posAng
sd twomass_sixx2_scn TWOMASS direction of scan -- north/south-bound (n/s) varchar 1      
sdet twomass_sixx2_psc, twomass_sixx2_xsc TWOMASS # of scans in which src was detected in >=1 band smallint 2      
SDSS_CAMCOL mgcBrightSpec MGC SDSS camera column int 4      
SDSS_CLASS mgcBrightSpec MGC MGC translation of SDSS_TYPE smallint 2      
SDSS_DEC mgcBrightSpec MGC SDSS object declination in deg (J2000) float 8      
SDSS_EXTINC_G mgcBrightSpec MGC SDSS Galactic extinction correction in mag real 4      
SDSS_EXTINC_I mgcBrightSpec MGC SDSS Galactic extinction correction in mag real 4      
SDSS_EXTINC_R mgcBrightSpec MGC SDSS Galactic extinction correction in mag real 4      
SDSS_EXTINC_U mgcBrightSpec MGC SDSS Galactic extinction correction in mag real 4      
SDSS_EXTINC_Z mgcBrightSpec MGC SDSS Galactic extinction correction in mag real 4      
SDSS_FIELD mgcBrightSpec MGC SDSS field number int 4      
SDSS_MODMAG_G mgcBrightSpec MGC SDSS extinction corrected model magnitude real 4      
SDSS_MODMAG_I mgcBrightSpec MGC SDSS extinction corrected model magnitude real 4      
SDSS_MODMAG_R mgcBrightSpec MGC SDSS extinction corrected model magnitude real 4      
SDSS_MODMAG_U mgcBrightSpec MGC SDSS extinction corrected model magnitude real 4      
SDSS_MODMAG_Z mgcBrightSpec MGC SDSS extinction corrected model magnitude real 4      
SDSS_N mgcBrightSpec MGC Number of SDSS objects matched to MGC object int 4      
SDSS_OBJID mgcBrightSpec MGC SDSS PhotoObject ID bigint 8      
SDSS_PETMAG_G mgcBrightSpec MGC SDSS extinction corrected Petrosian magnitude real 4      
SDSS_PETMAG_I mgcBrightSpec MGC SDSS extinction corrected Petrosian magnitude real 4      
SDSS_PETMAG_R mgcBrightSpec MGC SDSS extinction corrected Petrosian magnitude real 4      
SDSS_PETMAG_U mgcBrightSpec MGC SDSS extinction corrected Petrosian magnitude real 4      
SDSS_PETMAG_Z mgcBrightSpec MGC SDSS extinction corrected Petrosian magnitude real 4      
SDSS_PETR50_G mgcBrightSpec MGC SDSS radius containing 50% Petrosian flux in arcsec real 4      
SDSS_PETR50_I mgcBrightSpec MGC SDSS radius containing 50% Petrosian flux in arcsec real 4      
SDSS_PETR50_R mgcBrightSpec MGC SDSS radius containing 50% Petrosian flux in arcsec real 4      
SDSS_PETR50_U mgcBrightSpec MGC SDSS radius containing 50% Petrosian flux in arcsec real 4      
SDSS_PETR50_Z mgcBrightSpec MGC SDSS radius containing 50% Petrosian flux in arcsec real 4      
SDSS_PSFMAG_G mgcBrightSpec MGC SDSS extinction corrected PSF magnitude real 4      
SDSS_PSFMAG_I mgcBrightSpec MGC SDSS extinction corrected PSF magnitude real 4      
SDSS_PSFMAG_R mgcBrightSpec MGC SDSS extinction corrected PSF magnitude real 4      
SDSS_PSFMAG_U mgcBrightSpec MGC SDSS extinction corrected PSF magnitude real 4      
SDSS_PSFMAG_Z mgcBrightSpec MGC SDSS extinction corrected PSF magnitude real 4      
SDSS_RA mgcBrightSpec MGC SDSS object right ascension in deg (J2000) float 8      
SDSS_RERUN mgcBrightSpec MGC SDSS rerun number int 4      
SDSS_RUN mgcBrightSpec MGC SDSS run number int 4      
SDSS_SPCLASS mgcBrightSpec MGC MGC translation of SDSS_SPECCLASS smallint 2      
SDSS_SPECCLASS mgcBrightSpec MGC SDSS spectroscopic classification smallint 2      
SDSS_TYPE mgcBrightSpec MGC SDSS morphological classification smallint 2      
SDSS_Z mgcBrightSpec MGC SDSS redshift real 4      
SDSS_ZQUAL mgcBrightSpec MGC SDSS redshift quality tinyint 1      
sdssClass first08Jul16Source, firstSource12Feb16 FIRST morphological classification in SDSS DR6 (s=stellar, g=nonstellar/galaxy) varchar 1      
sdssMag first08Jul16Source, firstSource12Feb16 FIRST SDSS i magnitude real 4 mag    
sdssMatches first08Jul16Source FIRST number of matches within a fiducial radius (8 arcsec) with SDSS DR6 int 4      
sdssMatches firstSource12Feb16 FIRST number of matches within a fiducial radius (8 arcsec) with SDSS DR6 smallint 2      
sdssPrimary ultravistaSourceXDR13PhotoObj, ultravistaSourceXDR13PhotoObjAll ULTRAVISTADR4 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vhsSourceXDR13PhotoObj VHSv20201209 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vhsSourceXDR13PhotoObj VHSv20231101 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vhsSourceXDR13PhotoObj VHSv20240731 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vhsSourceXDR13PhotoObj, vhsSourceXDR13PhotoObjAll, vhsSourceXDR7PhotoObj, vhsSourceXDR7PhotoObjAll, vhsSourceXStripe82PhotoObjAll VHSv20180419 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary videoSourceXStripe82PhotoObjAll VIDEODR2 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary videoSourceXStripe82PhotoObjAll VIDEODR3 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary videoSourceXStripe82PhotoObjAll VIDEODR4 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary videoSourceXStripe82PhotoObjAll VIDEODR5 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary videoSourceXStripe82PhotoObjAll VIDEOv20100513 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary videoSourceXStripe82PhotoObjAll VIDEOv20111208 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vikingSourceXDR7PhotoObj VIKINGDR3 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vikingSourceXDR7PhotoObj VIKINGDR4 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vikingSourceXDR7PhotoObj VIKINGv20110714 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vikingSourceXDR7PhotoObj VIKINGv20111019 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vikingSourceXDR7PhotoObj VIKINGv20130417 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vikingSourceXDR7PhotoObj VIKINGv20140402 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vikingSourceXDR7PhotoObj VIKINGv20150421 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vikingSourceXDR7PhotoObj VIKINGv20151230 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vikingSourceXDR7PhotoObj VIKINGv20160406 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssPrimary vikingSourceXDR7PhotoObj, vikingSourceXDR7PhotoObjAll, vikingSourceXStripe82PhotoObjAll VIKINGDR2 SDSS flag for neighbour being primary (1) or secondary (0) tinyint 1   255 meta.code
sdssSep first08Jul16Source, firstSource12Feb16 FIRST separation of the nearest match in SDSS DR6 from the FIRST position real 4 arcsec    
sdssType ultravistaSourceXDR13PhotoObj, ultravistaSourceXDR13PhotoObjAll ULTRAVISTADR4 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vhsSourceXDR13PhotoObj VHSv20201209 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vhsSourceXDR13PhotoObj VHSv20231101 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vhsSourceXDR13PhotoObj VHSv20240731 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vhsSourceXDR13PhotoObj, vhsSourceXDR13PhotoObjAll, vhsSourceXDR7PhotoObj, vhsSourceXDR7PhotoObjAll, vhsSourceXStripe82PhotoObjAll VHSv20180419 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType videoSourceXStripe82PhotoObjAll VIDEODR2 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType videoSourceXStripe82PhotoObjAll VIDEODR3 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType videoSourceXStripe82PhotoObjAll VIDEODR4 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType videoSourceXStripe82PhotoObjAll VIDEODR5 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType videoSourceXStripe82PhotoObjAll VIDEOv20100513 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType videoSourceXStripe82PhotoObjAll VIDEOv20111208 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vikingSourceXDR7PhotoObj VIKINGDR3 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vikingSourceXDR7PhotoObj VIKINGDR4 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vikingSourceXDR7PhotoObj VIKINGv20110714 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vikingSourceXDR7PhotoObj VIKINGv20111019 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vikingSourceXDR7PhotoObj VIKINGv20130417 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vikingSourceXDR7PhotoObj VIKINGv20140402 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vikingSourceXDR7PhotoObj VIKINGv20150421 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vikingSourceXDR7PhotoObj VIKINGv20151230 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vikingSourceXDR7PhotoObj VIKINGv20160406 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sdssType vikingSourceXDR7PhotoObj, vikingSourceXDR7PhotoObjAll, vikingSourceXStripe82PhotoObjAll VIKINGDR2 SDSS type of neighbour: 3=galaxy; 6=star tinyint 1   255 src.class
sectionID FilterSections SHARKSv20210421 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections ULTRAVISTADR4 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VHSDR3 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VHSDR4 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VHSDR5 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VHSDR6 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VHSv20150108 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VHSv20160114 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VHSv20160507 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VHSv20170630 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VHSv20180419 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VHSv20201209 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VHSv20231101 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VHSv20240731 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VIDEODR4 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VIDEODR5 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VIKINGDR4 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VIKINGv20150421 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VIKINGv20151230 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VIKINGv20160406 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VIKINGv20161202 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VIKINGv20170715 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCDEEPv20230713 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCDEEPv20240506 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCDR3 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCDR4 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCDR5 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20140428 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20140903 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20150309 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20151218 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20160311 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20160822 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20170109 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20170411 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20171101 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20180702 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20181120 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20191212 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20210708 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20230816 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VMCv20240226 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VSAQC UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VVVDR5 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections VVVXDR1 UID of section of focal plane with different filter tinyint 1      
sectionID FilterSections, SectionDetectors SHARKSv20210222 UID of section of focal plane with different filter tinyint 1      
seeing MultiframeDetector SHARKSv20210222 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector SHARKSv20210421 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector ULTRAVISTADR4 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSDR1 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSDR2 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSDR3 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSDR4 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSDR5 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSDR6 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSv20120926 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSv20130417 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSv20140409 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSv20150108 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSv20160114 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSv20160507 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSv20170630 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSv20180419 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSv20201209 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSv20231101 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VHSv20240731 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIDEODR2 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIDEODR3 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIDEODR4 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIDEODR5 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIDEOv20100513 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIDEOv20111208 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIKINGDR2 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIKINGDR3 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIKINGDR4 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIKINGv20110714 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIKINGv20111019 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIKINGv20130417 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIKINGv20140402 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIKINGv20150421 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIKINGv20151230 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIKINGv20160406 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIKINGv20161202 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VIKINGv20170715 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCDEEPv20230713 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCDEEPv20240506 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCDR1 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCDR2 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCDR3 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCDR4 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCDR5 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20110816 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20110909 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20120126 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20121128 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20130304 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20130805 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20140428 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20140903 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20150309 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20151218 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20160311 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20160822 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20170109 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20170411 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20171101 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20180702 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20181120 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20191212 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20210708 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20230816 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VMCv20240226 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VVVDR1 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VVVDR2 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VVVDR5 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VVVXDR1 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VVVv20100531 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing MultiframeDetector VVVv20110718 Average FWHM {catalogue extension keyword:  SEEING} real 4 pixels -0.9999995e9 ??
An average realistic FWHM estimated directly from the stellar images on the frame. Multiply by pixel scale size to convert to arcsec (eg. ×0.400 WFCAM; ×0.333 INT WFC).
seeing sharksMultiframeDetector, ultravistaMultiframeDetector, vhsMultiframeDetector, videoMultiframeDetector, vikingMultiframeDetector, vmcMultiframeDetector, vvvMultiframeDetector VSAQC Average FWHM real 4 pixels -0.9999995e9 ??
selection RequiredListDrivenProduct VHSv20130417 Selection SQL or filename containing list varchar 1024   NONE  
selection RequiredListDrivenProduct VIKINGv20130417 Selection SQL or filename containing list varchar 1024   NONE  
selection RequiredListDrivenProduct VMCv20130805 Selection SQL or filename containing list varchar 1024   NONE  
selection RequiredMatchedApertureProduct SHARKSv20210222 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct SHARKSv20210421 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct ULTRAVISTADR4 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct VHSv20201209 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct VHSv20231101 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct VHSv20240731 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct VMCDEEPv20230713 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct VMCDEEPv20240506 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct VMCDR5 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct VMCv20191212 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct VMCv20210708 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct VMCv20230816 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct VMCv20240226 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct VVVDR5 Selection SQL or filename containing list varchar 1024      
selection RequiredMatchedApertureProduct VVVXDR1 Selection SQL or filename containing list varchar 1024      
sep gaiaxwise_matches GAIAXWISE Angular separation between sources float 8 arcsec    
SEP_1XMM twoxmm, twoxmm_v1_2 XMM The distance between this source and the matched 1XMM source (MATCH_1XMM) in arcseconds. real 4 arcsec    
SEP_2XMMP twoxmm, twoxmm_v1_2 XMM The distance between this source and the matched 2XMMp source (MATCH_2XMMp) in arcseconds. real 4 arcsec    
seqNo first08Jul16Source, firstSource, firstSource12Feb16 FIRST sequential object number int 4     meta.id
seqNo glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca, glimpse_hrc_inter GLIMPSE sequential object number in the HRC int 4     meta.id
seqNo glimpse_mca_inter GLIMPSE sequential object number in the MCA int 4     meta.id
seqNo iras_psc IRAS sequential object number int 4     meta.id
seqNo nvssSource NVSS sequential object number int 4     meta.id
seqNo ogle3LpvLmcSource, ogle3LpvSmcSource, ogle4CepLmcSource, ogle4CepSmcSource, ogle4RRLyrLmcSource, ogle4RRLyrSmcSource OGLE sequential object number int 4     meta.number
seqNo rosat_bsc ROSAT sequential object number in the BSC int 4     meta.id
seqNo rosat_fsc ROSAT sequential object number in the FSC int 4     meta.id
SEQNUM akari_lmc_psa_v1, akari_lmc_psc_v1 AKARI Sequential number (unique object ID) int 4      
SEQNUM grs_ngpSource, grs_ranSource, grs_sgpSource TWODFGRS Assigned sequence number to this object; determines the FITS filename (SEQNUM.fits) int 4     meta.id
seqNum combo17CDFSSource COMBO17 Sequential number (unique object ID) int 4      
seqNum denisDR3Source DENIS Sequential number (unique object ID) int 4      
seqNum eros2LMCSource, eros2SMCSource, erosLMCSource, erosSMCSource EROS Sequential number (unique object ID) int 4      
seqNum machoLMCSource, machoSMCSource MACHO Sequential number (unique object ID) int 4      
seqNum mcps_lmcSource, mcps_smcSource MCPS Sequential number (unique object ID) int 4      
seqNum sharksDetection SHARKSv20210222 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum sharksDetection SHARKSv20210421 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum sharksSourceXDetectionBestMatch SHARKSv20210222 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum sharksSourceXDetectionBestMatch SHARKSv20210421 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum spitzer_smcSource SPITZER Sequential number (unique object ID) int 4      
seqNum twomass_sixx2_psc TWOMASS Sequential number (unique object ID) int 4      
seqNum ultravistaDetection ULTRAVISTADR4 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum ultravistaSourceXDetectionBestMatch ULTRAVISTADR4 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vhsDetection VHSDR2 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vhsDetection VHSDR3 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vhsDetection VHSDR4 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vhsDetection VHSDR5 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vhsDetection VHSDR6 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vhsDetection VHSv20120926 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vhsDetection VHSv20130417 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vhsDetection VHSv20140409 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vhsDetection VHSv20150108 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vhsDetection VHSv20160114 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vhsDetection VHSv20160507 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vhsDetection VHSv20170630 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vhsDetection VHSv20180419 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vhsDetection VHSv20201209 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vhsDetection VHSv20231101 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vhsDetection VHSv20240731 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vhsDetection, vhsListRemeasurement VHSDR1 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum videoDetection VIDEODR2 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum videoDetection VIDEODR3 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum videoDetection VIDEODR4 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum videoDetection VIDEODR5 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum videoDetection VIDEOv20111208 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum videoDetection, videoListRemeasurement VIDEOv20100513 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum videoSourceXDetectionBestMatch VIDEODR2 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.id
seqNum videoSourceXDetectionBestMatch VIDEODR3 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum videoSourceXDetectionBestMatch VIDEODR4 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum videoSourceXDetectionBestMatch VIDEODR5 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum videoSourceXDetectionBestMatch VIDEOv20100513 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.id
seqNum videoSourceXDetectionBestMatch VIDEOv20111208 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.id
seqNum vikingDetection VIKINGDR2 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vikingDetection VIKINGDR3 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vikingDetection VIKINGDR4 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vikingDetection VIKINGv20111019 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vikingDetection VIKINGv20130417 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vikingDetection VIKINGv20140402 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vikingDetection VIKINGv20150421 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vikingDetection VIKINGv20151230 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vikingDetection VIKINGv20160406 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vikingDetection VIKINGv20161202 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vikingDetection VIKINGv20170715 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vikingDetection, vikingListRemeasurement VIKINGv20110714 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vikingSourceXDetectionBestMatch VIKINGDR2 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.id
seqNum vikingSourceXDetectionBestMatch VIKINGDR3 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vikingSourceXDetectionBestMatch VIKINGDR4 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vikingSourceXDetectionBestMatch VIKINGv20110714 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.id
seqNum vikingSourceXDetectionBestMatch VIKINGv20111019 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.id
seqNum vikingSourceXDetectionBestMatch VIKINGv20130417 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vikingSourceXDetectionBestMatch VIKINGv20140402 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vikingSourceXDetectionBestMatch VIKINGv20150421 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vikingSourceXDetectionBestMatch VIKINGv20151230 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vikingSourceXDetectionBestMatch VIKINGv20160406 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vikingSourceXDetectionBestMatch VIKINGv20161202 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vikingSourceXDetectionBestMatch VIKINGv20170715 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vmcDetection VMCDR1 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vmcDetection VMCDR2 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCDR3 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCDR4 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCDR5 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vmcDetection VMCv20110909 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vmcDetection VMCv20120126 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vmcDetection VMCv20121128 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20130304 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20130805 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20140428 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20140903 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20150309 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20151218 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20160311 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20160822 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20170109 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20170411 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20171101 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20180702 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20181120 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vmcDetection VMCv20191212 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vmcDetection VMCv20210708 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vmcDetection VMCv20230816 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vmcDetection VMCv20240226 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vmcDetection, vmcListRemeasurement VMCv20110816 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vmcdeepDetection VMCDEEPv20230713 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vmcdeepDetection VMCDEEPv20240506 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vvvDetection VVVDR1 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vvvDetection VVVDR2 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vvvDetection, vvvDetectionPawPrints, vvvDetectionTiles VVVDR5 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.number
seqNum vvvDetection, vvvListRemeasurement VVVv20100531 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4     meta.id
seqNum vvvSourceXDetectionBestMatch VVVDR1 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vvvSourceXDetectionBestMatch VVVDR2 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vvvSourceXDetectionBestMatch VVVDR5 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.number
seqNum vvvSourceXDetectionBestMatch VVVv20100531 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.id
seqNum vvvSourceXDetectionBestMatch VVVv20110718 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.id
seqNum vvvxSourceXDetectionBestMatch VVVXDR1 the running number of this detection {catalogue TType keyword: Sequence_number}
The running number for ease of reference, in strict order of image detections.
int 4   -99999999 meta.id
SerFit1DChi2 sharksDetection SHARKSv20210222 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 sharksDetection SHARKSv20210421 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 ultravistaDetection ULTRAVISTADR4 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_chi2} real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSDR2 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSDR3 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSDR4 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSDR5 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSDR6 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSv20120926 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSv20130417 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSv20140409 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSv20150108 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSv20160114 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSv20160507 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSv20170630 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSv20180419 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSv20201209 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSv20231101 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection VHSv20240731 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vhsDetection, vhsListRemeasurement VHSDR1 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 videoDetection VIDEODR2 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_chi2} real 4   -0.9999995e9  
SerFit1DChi2 videoDetection VIDEODR3 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_chi2} real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 videoDetection VIDEODR4 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_chi2} real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 videoDetection VIDEODR5 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_chi2} real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 videoDetection VIDEOv20100513 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_chi2} real 4   -0.9999995e9  
SerFit1DChi2 videoDetection VIDEOv20111208 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_chi2} real 4   -0.9999995e9  
SerFit1DChi2 videoListRemeasurement VIDEOv20100513 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vikingDetection VIKINGDR2 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vikingDetection VIKINGDR3 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vikingDetection VIKINGDR4 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vikingDetection VIKINGv20111019 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vikingDetection VIKINGv20130417 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vikingDetection VIKINGv20140402 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vikingDetection VIKINGv20150421 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vikingDetection VIKINGv20151230 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vikingDetection VIKINGv20160406 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vikingDetection VIKINGv20161202 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vikingDetection VIKINGv20170715 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vikingDetection, vikingListRemeasurement VIKINGv20110714 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vmcdeepDetection VMCDEEPv20230713 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit1DChi2 vmcdeepDetection VMCDEEPv20240506 Error in 1D fit {catalogue TType keyword: 1D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 sharksDetection SHARKSv20210222 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 sharksDetection SHARKSv20210421 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 ultravistaDetection ULTRAVISTADR4 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_chi2} real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSDR2 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSDR3 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSDR4 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSDR5 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSDR6 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSv20120926 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSv20130417 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSv20140409 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSv20150108 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSv20160114 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSv20160507 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSv20170630 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSv20180419 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSv20201209 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSv20231101 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection VHSv20240731 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vhsDetection, vhsListRemeasurement VHSDR1 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 videoDetection VIDEODR2 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_chi2} real 4   -0.9999995e9  
SerFit2DChi2 videoDetection VIDEODR3 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_chi2} real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 videoDetection VIDEODR4 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_chi2} real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 videoDetection VIDEODR5 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_chi2} real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 videoDetection VIDEOv20100513 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_chi2} real 4   -0.9999995e9  
SerFit2DChi2 videoDetection VIDEOv20111208 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_chi2} real 4   -0.9999995e9  
SerFit2DChi2 videoListRemeasurement VIDEOv20100513 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vikingDetection VIKINGDR2 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vikingDetection VIKINGDR3 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vikingDetection VIKINGDR4 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vikingDetection VIKINGv20111019 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vikingDetection VIKINGv20130417 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vikingDetection VIKINGv20140402 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vikingDetection VIKINGv20150421 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vikingDetection VIKINGv20151230 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vikingDetection VIKINGv20160406 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vikingDetection VIKINGv20161202 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vikingDetection VIKINGv20170715 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vikingDetection, vikingListRemeasurement VIKINGv20110714 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vmcdeepDetection VMCDEEPv20230713 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFit2DChi2 vmcdeepDetection VMCDEEPv20240506 Error in 2D fit {catalogue TType keyword: 2D_Sersic_fit_chi2}
standard normalised variance of fit [For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerFitNu1D sharksDetection SHARKSv20210222 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D sharksDetection SHARKSv20210421 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D ultravistaDetection ULTRAVISTADR4 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_nu} real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSDR2 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSDR3 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSDR4 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSDR5 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSDR6 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSv20120926 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSv20130417 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSv20140409 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSv20150108 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSv20160114 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSv20160507 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSv20170630 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSv20180419 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSv20201209 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSv20231101 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection VHSv20240731 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vhsDetection, vhsListRemeasurement VHSDR1 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D videoDetection VIDEODR2 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_nu} real 4   -0.9999995e9  
SerFitNu1D videoDetection VIDEODR3 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_nu} real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D videoDetection VIDEODR4 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_nu} real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D videoDetection VIDEODR5 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_nu} real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D videoDetection VIDEOv20100513 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_nu} real 4   -0.9999995e9  
SerFitNu1D videoDetection VIDEOv20111208 SExtractor parameter {catalogue TType keyword: 1D_Sersic_fit_nu} real 4   -0.9999995e9  
SerFitNu1D videoListRemeasurement VIDEOv20100513 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vikingDetection VIKINGDR2 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vikingDetection VIKINGDR3 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vikingDetection VIKINGDR4 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vikingDetection VIKINGv20111019 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vikingDetection VIKINGv20130417 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vikingDetection VIKINGv20140402 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vikingDetection VIKINGv20150421 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vikingDetection VIKINGv20151230 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vikingDetection VIKINGv20160406 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vikingDetection VIKINGv20161202 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vikingDetection VIKINGv20170715 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vikingDetection, vikingListRemeasurement VIKINGv20110714 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vmcdeepDetection VMCDEEPv20230713 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu1D vmcdeepDetection VMCDEEPv20240506 No. of degrees of freedom for 1D Sersic fit {catalogue TType keyword: 1D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D sharksDetection SHARKSv20210222 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D sharksDetection SHARKSv20210421 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D ultravistaDetection ULTRAVISTADR4 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_nu} real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSDR2 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSDR3 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSDR4 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSDR5 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSDR6 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSv20120926 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSv20130417 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSv20140409 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSv20150108 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSv20160114 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSv20160507 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSv20170630 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSv20180419 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSv20201209 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSv20231101 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection VHSv20240731 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vhsDetection, vhsListRemeasurement VHSDR1 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D videoDetection VIDEODR2 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_nu} real 4   -0.9999995e9  
SerFitNu2D videoDetection VIDEODR3 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_nu} real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D videoDetection VIDEODR4 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_nu} real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D videoDetection VIDEODR5 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_nu} real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D videoDetection VIDEOv20100513 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_nu} real 4   -0.9999995e9  
SerFitNu2D videoDetection VIDEOv20111208 SExtractor parameter {catalogue TType keyword: 2D_Sersic_fit_nu} real 4   -0.9999995e9  
SerFitNu2D videoListRemeasurement VIDEOv20100513 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vikingDetection VIKINGDR2 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vikingDetection VIKINGDR3 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vikingDetection VIKINGDR4 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vikingDetection VIKINGv20111019 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vikingDetection VIKINGv20130417 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vikingDetection VIKINGv20140402 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vikingDetection VIKINGv20150421 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vikingDetection VIKINGv20151230 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vikingDetection VIKINGv20160406 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vikingDetection VIKINGv20161202 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vikingDetection VIKINGv20170715 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vikingDetection, vikingListRemeasurement VIKINGv20110714 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vmcdeepDetection VMCDEEPv20230713 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFitNu2D vmcdeepDetection VMCDEEPv20240506 No. of degrees of freedom for 2D Sersic fit {catalogue TType keyword: 2D_Sersic_fit_nu}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.dof
SerFlux1D sharksDetection SHARKSv20210222 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D sharksDetection SHARKSv20210421 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D ultravistaDetection ULTRAVISTADR4 SExtractor parameter {catalogue TType keyword: 1D_Sersic_flux} real 4   -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSDR2 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count;em.opt
SerFlux1D vhsDetection VHSDR3 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSDR4 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSDR5 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSDR6 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSv20120926 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSv20130417 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSv20140409 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSv20150108 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSv20160114 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSv20160507 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSv20170630 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSv20180419 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSv20201209 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSv20231101 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection VHSv20240731 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vhsDetection, vhsListRemeasurement VHSDR1 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count;em.opt
SerFlux1D videoDetection VIDEODR2 SExtractor parameter {catalogue TType keyword: 1D_Sersic_flux} real 4   -0.9999995e9  
SerFlux1D videoDetection VIDEODR3 SExtractor parameter {catalogue TType keyword: 1D_Sersic_flux} real 4   -0.9999995e9 phot.count
SerFlux1D videoDetection VIDEODR4 SExtractor parameter {catalogue TType keyword: 1D_Sersic_flux} real 4   -0.9999995e9 phot.count
SerFlux1D videoDetection VIDEODR5 SExtractor parameter {catalogue TType keyword: 1D_Sersic_flux} real 4   -0.9999995e9 phot.count
SerFlux1D videoDetection VIDEOv20100513 SExtractor parameter {catalogue TType keyword: 1D_Sersic_flux} real 4   -0.9999995e9  
SerFlux1D videoDetection VIDEOv20111208 SExtractor parameter {catalogue TType keyword: 1D_Sersic_flux} real 4   -0.9999995e9  
SerFlux1D videoListRemeasurement VIDEOv20100513 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count;em.opt
SerFlux1D vikingDetection VIKINGDR2 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count;em.opt
SerFlux1D vikingDetection VIKINGDR3 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vikingDetection VIKINGDR4 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vikingDetection VIKINGv20111019 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count;em.opt
SerFlux1D vikingDetection VIKINGv20130417 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vikingDetection VIKINGv20140402 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vikingDetection VIKINGv20150421 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vikingDetection VIKINGv20151230 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vikingDetection VIKINGv20160406 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vikingDetection VIKINGv20161202 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vikingDetection VIKINGv20170715 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vikingDetection, vikingListRemeasurement VIKINGv20110714 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count;em.opt
SerFlux1D vmcdeepDetection VMCDEEPv20230713 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux1D vmcdeepDetection VMCDEEPv20240506 1D Sersic flux {catalogue TType keyword: 1D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D sharksDetection SHARKSv20210222 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D sharksDetection SHARKSv20210421 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D ultravistaDetection ULTRAVISTADR4 SExtractor parameter {catalogue TType keyword: 2D_Sersic_flux} real 4   -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSDR2 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count;em.opt
SerFlux2D vhsDetection VHSDR3 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSDR4 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSDR5 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSDR6 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSv20120926 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSv20130417 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSv20140409 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSv20150108 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSv20160114 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSv20160507 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSv20170630 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSv20180419 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSv20201209 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSv20231101 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection VHSv20240731 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vhsDetection, vhsListRemeasurement VHSDR1 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count;em.opt
SerFlux2D videoDetection VIDEODR2 SExtractor parameter {catalogue TType keyword: 2D_Sersic_flux} real 4   -0.9999995e9  
SerFlux2D videoDetection VIDEODR3 SExtractor parameter {catalogue TType keyword: 2D_Sersic_flux} real 4   -0.9999995e9 phot.count
SerFlux2D videoDetection VIDEODR4 SExtractor parameter {catalogue TType keyword: 2D_Sersic_flux} real 4   -0.9999995e9 phot.count
SerFlux2D videoDetection VIDEODR5 SExtractor parameter {catalogue TType keyword: 2D_Sersic_flux} real 4   -0.9999995e9 phot.count
SerFlux2D videoDetection VIDEOv20100513 SExtractor parameter {catalogue TType keyword: 2D_Sersic_flux} real 4   -0.9999995e9  
SerFlux2D videoDetection VIDEOv20111208 SExtractor parameter {catalogue TType keyword: 2D_Sersic_flux} real 4   -0.9999995e9  
SerFlux2D videoListRemeasurement VIDEOv20100513 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count;em.opt
SerFlux2D vikingDetection VIKINGDR2 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count;em.opt
SerFlux2D vikingDetection VIKINGDR3 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vikingDetection VIKINGDR4 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vikingDetection VIKINGv20111019 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count;em.opt
SerFlux2D vikingDetection VIKINGv20130417 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vikingDetection VIKINGv20140402 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vikingDetection VIKINGv20150421 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vikingDetection VIKINGv20151230 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vikingDetection VIKINGv20160406 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vikingDetection VIKINGv20161202 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vikingDetection VIKINGv20170715 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vikingDetection, vikingListRemeasurement VIKINGv20110714 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count;em.opt
SerFlux2D vmcdeepDetection VMCDEEPv20230713 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerFlux2D vmcdeepDetection VMCDEEPv20240506 2D Sersic flux {catalogue TType keyword: 2D_Sersic_flux}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 ADU -0.9999995e9 phot.count
SerIdx1D sharksDetection SHARKSv20210222 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D sharksDetection SHARKSv20210421 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D ultravistaDetection ULTRAVISTADR4 SExtractor parameter {catalogue TType keyword: 1D_Sersic_index} real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSDR2 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSDR3 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSDR4 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSDR5 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSDR6 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSv20120926 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSv20130417 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSv20140409 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSv20150108 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSv20160114 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSv20160507 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSv20170630 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSv20180419 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSv20201209 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSv20231101 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection VHSv20240731 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vhsDetection, vhsListRemeasurement VHSDR1 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D videoDetection VIDEODR2 SExtractor parameter {catalogue TType keyword: 1D_Sersic_index} real 4   -0.9999995e9  
SerIdx1D videoDetection VIDEODR3 SExtractor parameter {catalogue TType keyword: 1D_Sersic_index} real 4   -0.9999995e9 stat.fit.param
SerIdx1D videoDetection VIDEODR4 SExtractor parameter {catalogue TType keyword: 1D_Sersic_index} real 4   -0.9999995e9 stat.fit.param
SerIdx1D videoDetection VIDEODR5 SExtractor parameter {catalogue TType keyword: 1D_Sersic_index} real 4   -0.9999995e9 stat.fit.param
SerIdx1D videoDetection VIDEOv20100513 SExtractor parameter {catalogue TType keyword: 1D_Sersic_index} real 4   -0.9999995e9  
SerIdx1D videoDetection VIDEOv20111208 SExtractor parameter {catalogue TType keyword: 1D_Sersic_index} real 4   -0.9999995e9  
SerIdx1D videoListRemeasurement VIDEOv20100513 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vikingDetection VIKINGDR2 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vikingDetection VIKINGDR3 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vikingDetection VIKINGDR4 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vikingDetection VIKINGv20111019 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vikingDetection VIKINGv20130417 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vikingDetection VIKINGv20140402 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vikingDetection VIKINGv20150421 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vikingDetection VIKINGv20151230 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vikingDetection VIKINGv20160406 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vikingDetection VIKINGv20161202 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vikingDetection VIKINGv20170715 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vikingDetection, vikingListRemeasurement VIKINGv20110714 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vmcdeepDetection VMCDEEPv20230713 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx1D vmcdeepDetection VMCDEEPv20240506 Power law index {catalogue TType keyword: 1D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D sharksDetection SHARKSv20210222 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D sharksDetection SHARKSv20210421 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D ultravistaDetection ULTRAVISTADR4 SExtractor parameter {catalogue TType keyword: 2D_Sersic_index} real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSDR2 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSDR3 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSDR4 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSDR5 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSDR6 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSv20120926 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSv20130417 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSv20140409 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSv20150108 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSv20160114 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSv20160507 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSv20170630 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSv20180419 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSv20201209 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSv20231101 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection VHSv20240731 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vhsDetection, vhsListRemeasurement VHSDR1 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D videoDetection VIDEODR2 SExtractor parameter {catalogue TType keyword: 2D_Sersic_index} real 4   -0.9999995e9  
SerIdx2D videoDetection VIDEODR3 SExtractor parameter {catalogue TType keyword: 2D_Sersic_index} real 4   -0.9999995e9 stat.fit.param
SerIdx2D videoDetection VIDEODR4 SExtractor parameter {catalogue TType keyword: 2D_Sersic_index} real 4   -0.9999995e9 stat.fit.param
SerIdx2D videoDetection VIDEODR5 SExtractor parameter {catalogue TType keyword: 2D_Sersic_index} real 4   -0.9999995e9 stat.fit.param
SerIdx2D videoDetection VIDEOv20100513 SExtractor parameter {catalogue TType keyword: 2D_Sersic_index} real 4   -0.9999995e9  
SerIdx2D videoDetection VIDEOv20111208 SExtractor parameter {catalogue TType keyword: 2D_Sersic_index} real 4   -0.9999995e9  
SerIdx2D videoListRemeasurement VIDEOv20100513 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vikingDetection VIKINGDR2 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vikingDetection VIKINGDR3 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vikingDetection VIKINGDR4 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vikingDetection VIKINGv20111019 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vikingDetection VIKINGv20130417 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vikingDetection VIKINGv20140402 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vikingDetection VIKINGv20150421 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vikingDetection VIKINGv20151230 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vikingDetection VIKINGv20160406 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vikingDetection VIKINGv20161202 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vikingDetection VIKINGv20170715 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vikingDetection, vikingListRemeasurement VIKINGv20110714 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vmcdeepDetection VMCDEEPv20230713 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerIdx2D vmcdeepDetection VMCDEEPv20240506 Power law index {catalogue TType keyword: 2D_Sersic_index}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerMag1D sharksDetection SHARKSv20210222 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D sharksDetection SHARKSv20210421 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D ultravistaDetection ULTRAVISTADR4 SExtractor parameter real 4   -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vhsDetection VHSDR2 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 PHOT_PROFILE
SerMag1D vhsDetection VHSDR3 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag1D vhsDetection VHSDR4 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vhsDetection VHSDR5 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vhsDetection VHSDR6 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vhsDetection VHSv20120926 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag1D vhsDetection VHSv20130417 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag1D vhsDetection VHSv20140409 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag1D vhsDetection VHSv20150108 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vhsDetection VHSv20160114 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vhsDetection VHSv20160507 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vhsDetection VHSv20170630 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vhsDetection VHSv20180419 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vhsDetection VHSv20201209 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vhsDetection VHSv20231101 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vhsDetection VHSv20240731 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vhsDetection, vhsListRemeasurement VHSDR1 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 PHOT_PROFILE
SerMag1D videoDetection VIDEODR2 SExtractor parameter real 4   -0.9999995e9  
SerMag1D videoDetection VIDEODR3 SExtractor parameter real 4   -0.9999995e9 stat.fit.param
SerMag1D videoDetection VIDEODR4 SExtractor parameter real 4   -0.9999995e9 stat.fit.param;phot.mag
SerMag1D videoDetection VIDEODR5 SExtractor parameter real 4   -0.9999995e9 stat.fit.param;phot.mag
SerMag1D videoDetection VIDEOv20100513 SExtractor parameter real 4   -0.9999995e9  
SerMag1D videoDetection VIDEOv20111208 SExtractor parameter real 4   -0.9999995e9  
SerMag1D videoListRemeasurement VIDEOv20100513 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 PHOT_PROFILE
SerMag1D vikingDetection VIKINGDR2 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 PHOT_PROFILE
SerMag1D vikingDetection VIKINGDR3 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag1D vikingDetection VIKINGDR4 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag1D vikingDetection VIKINGv20111019 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 PHOT_PROFILE
SerMag1D vikingDetection VIKINGv20130417 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag1D vikingDetection VIKINGv20140402 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag1D vikingDetection VIKINGv20150421 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vikingDetection VIKINGv20151230 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vikingDetection VIKINGv20160406 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vikingDetection VIKINGv20161202 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vikingDetection VIKINGv20170715 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vikingDetection, vikingListRemeasurement VIKINGv20110714 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 PHOT_PROFILE
SerMag1D vmcdeepDetection VMCDEEPv20230713 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag1D vmcdeepDetection VMCDEEPv20240506 Calibrated 1D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D sharksDetection SHARKSv20210222 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D sharksDetection SHARKSv20210421 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D ultravistaDetection ULTRAVISTADR4 SExtractor parameter real 4   -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vhsDetection VHSDR2 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 PHOT_PROFILE
SerMag2D vhsDetection VHSDR3 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag2D vhsDetection VHSDR4 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vhsDetection VHSDR5 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vhsDetection VHSDR6 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vhsDetection VHSv20120926 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag2D vhsDetection VHSv20130417 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag2D vhsDetection VHSv20140409 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag2D vhsDetection VHSv20150108 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vhsDetection VHSv20160114 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vhsDetection VHSv20160507 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vhsDetection VHSv20170630 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vhsDetection VHSv20180419 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vhsDetection VHSv20201209 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vhsDetection VHSv20231101 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vhsDetection VHSv20240731 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vhsDetection, vhsListRemeasurement VHSDR1 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 PHOT_PROFILE
SerMag2D videoDetection VIDEODR2 SExtractor parameter real 4   -0.9999995e9  
SerMag2D videoDetection VIDEODR3 SExtractor parameter real 4   -0.9999995e9 stat.fit.param
SerMag2D videoDetection VIDEODR4 SExtractor parameter real 4   -0.9999995e9 stat.fit.param;phot.mag
SerMag2D videoDetection VIDEODR5 SExtractor parameter real 4   -0.9999995e9 stat.fit.param;phot.mag
SerMag2D videoDetection VIDEOv20100513 SExtractor parameter real 4   -0.9999995e9  
SerMag2D videoDetection VIDEOv20111208 SExtractor parameter real 4   -0.9999995e9  
SerMag2D videoListRemeasurement VIDEOv20100513 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 PHOT_PROFILE
SerMag2D vikingDetection VIKINGDR2 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 PHOT_PROFILE
SerMag2D vikingDetection VIKINGDR3 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag2D vikingDetection VIKINGDR4 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag2D vikingDetection VIKINGv20111019 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 PHOT_PROFILE
SerMag2D vikingDetection VIKINGv20130417 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag2D vikingDetection VIKINGv20140402 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param
SerMag2D vikingDetection VIKINGv20150421 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vikingDetection VIKINGv20151230 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vikingDetection VIKINGv20160406 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vikingDetection VIKINGv20161202 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vikingDetection VIKINGv20170715 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vikingDetection, vikingListRemeasurement VIKINGv20110714 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 PHOT_PROFILE
SerMag2D vmcdeepDetection VMCDEEPv20230713 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerMag2D vmcdeepDetection VMCDEEPv20240506 Calibrated 2D Sersic flux
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4 mag -0.9999995e9 stat.fit.param;phot.mag
SerScaleLen1D sharksDetection SHARKSv20210222 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D sharksDetection SHARKSv20210421 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D ultravistaDetection ULTRAVISTADR4 SExtractor parameter {catalogue TType keyword: 1D_Sersic_scale_len} real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSDR2 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSDR3 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSDR4 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSDR5 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSDR6 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSv20120926 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSv20130417 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSv20140409 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSv20150108 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSv20160114 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSv20160507 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSv20170630 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSv20180419 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSv20201209 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSv20231101 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection VHSv20240731 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vhsDetection, vhsListRemeasurement VHSDR1 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D videoDetection VIDEODR2 SExtractor parameter {catalogue TType keyword: 1D_Sersic_scale_len} real 4   -0.9999995e9  
SerScaleLen1D videoDetection VIDEODR3 SExtractor parameter {catalogue TType keyword: 1D_Sersic_scale_len} real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D videoDetection VIDEODR4 SExtractor parameter {catalogue TType keyword: 1D_Sersic_scale_len} real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D videoDetection VIDEODR5 SExtractor parameter {catalogue TType keyword: 1D_Sersic_scale_len} real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D videoDetection VIDEOv20100513 SExtractor parameter {catalogue TType keyword: 1D_Sersic_scale_len} real 4   -0.9999995e9  
SerScaleLen1D videoDetection VIDEOv20111208 SExtractor parameter {catalogue TType keyword: 1D_Sersic_scale_len} real 4   -0.9999995e9  
SerScaleLen1D videoListRemeasurement VIDEOv20100513 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vikingDetection VIKINGDR2 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vikingDetection VIKINGDR3 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vikingDetection VIKINGDR4 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vikingDetection VIKINGv20111019 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vikingDetection VIKINGv20130417 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vikingDetection VIKINGv20140402 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vikingDetection VIKINGv20150421 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vikingDetection VIKINGv20151230 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vikingDetection VIKINGv20160406 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vikingDetection VIKINGv20161202 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vikingDetection VIKINGv20170715 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vikingDetection, vikingListRemeasurement VIKINGv20110714 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vmcdeepDetection VMCDEEPv20230713 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen1D vmcdeepDetection VMCDEEPv20240506 Scale length {catalogue TType keyword: 1D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D sharksDetection SHARKSv20210222 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D sharksDetection SHARKSv20210421 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D ultravistaDetection ULTRAVISTADR4 SExtractor parameter {catalogue TType keyword: 2D_Sersic_scale_len} real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSDR2 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSDR3 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSDR4 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSDR5 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSDR6 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSv20120926 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSv20130417 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSv20140409 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSv20150108 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSv20160114 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSv20160507 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSv20170630 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSv20180419 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSv20201209 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSv20231101 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection VHSv20240731 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vhsDetection, vhsListRemeasurement VHSDR1 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D videoDetection VIDEODR2 SExtractor parameter {catalogue TType keyword: 2D_Sersic_scale_len} real 4   -0.9999995e9  
SerScaleLen2D videoDetection VIDEODR3 SExtractor parameter {catalogue TType keyword: 2D_Sersic_scale_len} real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D videoDetection VIDEODR4 SExtractor parameter {catalogue TType keyword: 2D_Sersic_scale_len} real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D videoDetection VIDEODR5 SExtractor parameter {catalogue TType keyword: 2D_Sersic_scale_len} real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D videoDetection VIDEOv20100513 SExtractor parameter {catalogue TType keyword: 2D_Sersic_scale_len} real 4   -0.9999995e9  
SerScaleLen2D videoDetection VIDEOv20111208 SExtractor parameter {catalogue TType keyword: 2D_Sersic_scale_len} real 4   -0.9999995e9  
SerScaleLen2D videoListRemeasurement VIDEOv20100513 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vikingDetection VIKINGDR2 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vikingDetection VIKINGDR3 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vikingDetection VIKINGDR4 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vikingDetection VIKINGv20111019 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vikingDetection VIKINGv20130417 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vikingDetection VIKINGv20140402 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vikingDetection VIKINGv20150421 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vikingDetection VIKINGv20151230 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vikingDetection VIKINGv20160406 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vikingDetection VIKINGv20161202 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vikingDetection VIKINGv20170715 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vikingDetection, vikingListRemeasurement VIKINGv20110714 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vmcdeepDetection VMCDEEPv20230713 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SerScaleLen2D vmcdeepDetection VMCDEEPv20240506 Scale length {catalogue TType keyword: 2D_Sersic_scale_len}
[For numerical stability the Sersic fits will use the previously derived x-y coordinates]
real 4   -0.9999995e9 stat.fit.param
SERSIC mgcGalaxyStruct MGC Sersic Index (=4 for de Vaucouleurs profile) real 4   99.99  
SERSIC_KAPPA mgcGalaxyStruct MGC Sersic profile coefficient real 4      
SERSICm mgcGalaxyStruct MGC Sersic Index error (-) real 4   99.99  
SERSICp mgcGalaxyStruct MGC Sersic Index error (+) real 4   99.99  
ses1_100 iras_psc IRAS Number of seconds-confirmed nearby small extended sources (100 micron). tinyint 1     instr.param
ses1_12 iras_psc IRAS Number of seconds-confirmed nearby small extended sources (12 micron). tinyint 1     instr.param
ses1_25 iras_psc IRAS Number of seconds-confirmed nearby small extended sources (25 micron). tinyint 1     instr.param
ses1_60 iras_psc IRAS Number of seconds-confirmed nearby small extended sources (60 micron). tinyint 1     instr.param
ses2_100 iras_psc IRAS Number of nearby weeks-confirmed small extended sources (100 micron). tinyint 1     meta.code
ses2_12 iras_psc IRAS Number of nearby weeks-confirmed small extended sources (12 micron). tinyint 1     meta.code
ses2_25 iras_psc IRAS Number of nearby weeks-confirmed small extended sources (25 micron). tinyint 1     meta.code
ses2_60 iras_psc IRAS Number of nearby weeks-confirmed small extended sources (60 micron). tinyint 1     meta.code
setupID RegionFieldLinks SHARKSv20210421 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks ULTRAVISTADR4 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks VHSv20201209 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks VHSv20231101 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks VHSv20240731 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks VMCDEEPv20230713 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks VMCDEEPv20240506 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks VMCDR5 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks VMCv20191212 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks VMCv20210708 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks VMCv20230816 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks VMCv20240226 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks VVVDR5 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks VVVXDR1 UID of top level setup. int 4   -99999999  
setupID RegionFieldLinks, RequiredMosaic SHARKSv20210222 UID of top level setup. int 4   -99999999  
setupID RequiredMapAverages SHARKSv20210222 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages SHARKSv20210421 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages ULTRAVISTADR4 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages VHSv20201209 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages VHSv20231101 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages VHSv20240731 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages VMCDEEPv20230713 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages VMCDEEPv20240506 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages VMCDR5 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages VMCv20191212 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages VMCv20210708 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages VMCv20230816 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages VMCv20240226 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages VVVDR5 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMapAverages VVVXDR1 the setupID of the averaging process int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel SHARKSv20210222 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel SHARKSv20210421 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel ULTRAVISTADR4 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel VHSv20201209 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel VHSv20231101 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel VHSv20240731 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel VMCDEEPv20230713 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel VMCDEEPv20240506 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel VMCDR5 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel VMCv20191212 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel VMCv20210708 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel VMCv20230816 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel VMCv20240226 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel VVVDR5 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
setupID RequiredMosaicTopLevel VVVXDR1 the unique setup ID. Probably one per programme, but just in case int 4     meta.id;meta.main
SEX_FLAG mgcGalaxyStruct MGC SExtractor Flag int 4 Integer    
SG target SIXDF SSS star/galaxy flag 1=galaxy 2=star 3=unclass 4=noise smallint 2      
sharp smashdr2_deep, smashdr2_object SMASH Average DAOPHOT sharp value, measurement of peakiness real 4      
sharp smashdr2_source SMASH DAOPHOT sharp value, measurement of peakiness real 4      
sharp vvvPsfDaophotJKsSource VVVDR5 Sharpness of the gaussian [-1,1] {catalogue TType keyword: sharp} real 4     stat.fit.goodness
SHARPL15 akari_lmc_psa_v1, akari_lmc_psc_v1 AKARI Sharpness float 8   99.999  
SHARPL24 akari_lmc_psa_v1, akari_lmc_psc_v1 AKARI Sharpness float 8   99.999  
SHARPN3 akari_lmc_psa_v1, akari_lmc_psc_v1 AKARI Sharpness float 8   99.999  
SHARPS11 akari_lmc_psa_v1, akari_lmc_psc_v1 AKARI Sharpness float 8   99.999  
SHARPS7 akari_lmc_psa_v1, akari_lmc_psc_v1 AKARI Sharpness float 8   99.999  
shortName Filter SHARKSv20210222 Short identification name for the filter varchar 10     ??
shortName Filter SHARKSv20210421 Short identification name for the filter varchar 10     ??
shortName Filter ULTRAVISTADR4 Short identification name for the filter varchar 10     ??
shortName Filter VHSDR1 Short identification name for the filter varchar 10     ??
shortName Filter VHSDR2 Short identification name for the filter varchar 10     ??
shortName Filter VHSDR3 Short identification name for the filter varchar 10     ??
shortName Filter VHSDR4 Short identification name for the filter varchar 10     ??
shortName Filter VHSDR5 Short identification name for the filter varchar 10     ??
shortName Filter VHSDR6 Short identification name for the filter varchar 10     ??
shortName Filter VHSv20120926 Short identification name for the filter varchar 10     ??
shortName Filter VHSv20130417 Short identification name for the filter varchar 10     ??
shortName Filter VHSv20150108 Short identification name for the filter varchar 10     ??
shortName Filter VHSv20160114 Short identification name for the filter varchar 10     ??
shortName Filter VHSv20160507 Short identification name for the filter varchar 10     ??
shortName Filter VHSv20170630 Short identification name for the filter varchar 10     ??
shortName Filter VHSv20180419 Short identification name for the filter varchar 10     ??
shortName Filter VHSv20201209 Short identification name for the filter varchar 10     ??
shortName Filter VHSv20231101 Short identification name for the filter varchar 10     ??
shortName Filter VHSv20240731 Short identification name for the filter varchar 10     ??
shortName Filter VIDEODR2 Short identification name for the filter varchar 10     ??
shortName Filter VIDEODR3 Short identification name for the filter varchar 10     ??
shortName Filter VIDEODR4 Short identification name for the filter varchar 10     ??
shortName Filter VIDEODR5 Short identification name for the filter varchar 10     ??
shortName Filter VIDEOv20100513 Short identification name for the filter varchar 10     ??
shortName Filter VIDEOv20111208 Short identification name for the filter varchar 10     ??
shortName Filter VIKINGDR2 Short identification name for the filter varchar 10     ??
shortName Filter VIKINGDR3 Short identification name for the filter varchar 10     ??
shortName Filter VIKINGDR4 Short identification name for the filter varchar 10     ??
shortName Filter VIKINGv20110714 Short identification name for the filter varchar 10     ??
shortName Filter VIKINGv20111019 Short identification name for the filter varchar 10     ??
shortName Filter VIKINGv20130417 Short identification name for the filter varchar 10     ??
shortName Filter VIKINGv20150421 Short identification name for the filter varchar 10     ??
shortName Filter VIKINGv20151230 Short identification name for the filter varchar 10     ??
shortName Filter VIKINGv20160406 Short identification name for the filter varchar 10     ??
shortName Filter VIKINGv20161202 Short identification name for the filter varchar 10     ??
shortName Filter VIKINGv20170715 Short identification name for the filter varchar 10     ??
shortName Filter VMCDEEPv20230713 Short identification name for the filter varchar 10     ??
shortName Filter VMCDEEPv20240506 Short identification name for the filter varchar 10     ??
shortName Filter VMCDR1 Short identification name for the filter varchar 10     ??
shortName Filter VMCDR3 Short identification name for the filter varchar 10     ??
shortName Filter VMCDR4 Short identification name for the filter varchar 10     ??
shortName Filter VMCDR5 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20110816 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20110909 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20120126 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20121128 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20130304 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20130805 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20140428 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20140903 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20150309 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20151218 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20160311 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20160822 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20170109 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20170411 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20171101 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20180702 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20181120 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20191212 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20210708 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20230816 Short identification name for the filter varchar 10     ??
shortName Filter VMCv20240226 Short identification name for the filter varchar 10     ??
shortName Filter VSAQC Short identification name for the filter varchar 10     ??
shortName Filter VVVDR1 Short identification name for the filter varchar 10     ??
shortName Filter VVVDR2 Short identification name for the filter varchar 10     ??
shortName Filter VVVDR5 Short identification name for the filter varchar 10     ??
shortName Filter VVVXDR1 Short identification name for the filter varchar 10     ??
shortName Filter VVVv20100531 Short identification name for the filter varchar 10     ??
shortName Filter VVVv20110718 Short identification name for the filter varchar 10     ??
shortName FilterExtinctionCoefficients EXTINCT Short name of the filter varchar 8     meta.id
shortName FilterSections SHARKSv20210222 Short identification name for the filter section varchar 10     ??
shortName FilterSections SHARKSv20210421 Short identification name for the filter section varchar 10     ??
shortName FilterSections ULTRAVISTADR4 Short identification name for the filter section varchar 10     ??
shortName FilterSections VHSDR3 Short identification name for the filter section varchar 10     ??
shortName FilterSections VHSDR4 Short identification name for the filter section varchar 10     ??
shortName FilterSections VHSDR5 Short identification name for the filter section varchar 10     ??
shortName FilterSections VHSDR6 Short identification name for the filter section varchar 10     ??
shortName FilterSections VHSv20150108 Short identification name for the filter section varchar 10     ??
shortName FilterSections VHSv20160114 Short identification name for the filter section varchar 10     ??
shortName FilterSections VHSv20160507 Short identification name for the filter section varchar 10     ??
shortName FilterSections VHSv20170630 Short identification name for the filter section varchar 10     ??
shortName FilterSections VHSv20180419 Short identification name for the filter section varchar 10     ??
shortName FilterSections VHSv20201209 Short identification name for the filter section varchar 10     ??
shortName FilterSections VHSv20231101 Short identification name for the filter section varchar 10     ??
shortName FilterSections VHSv20240731 Short identification name for the filter section varchar 10     ??
shortName FilterSections VIDEODR4 Short identification name for the filter section varchar 10     ??
shortName FilterSections VIDEODR5 Short identification name for the filter section varchar 10     ??
shortName FilterSections VIKINGDR4 Short identification name for the filter section varchar 10     ??
shortName FilterSections VIKINGv20150421 Short identification name for the filter section varchar 10     ??
shortName FilterSections VIKINGv20151230 Short identification name for the filter section varchar 10     ??
shortName FilterSections VIKINGv20160406 Short identification name for the filter section varchar 10     ??
shortName FilterSections VIKINGv20161202 Short identification name for the filter section varchar 10     ??
shortName FilterSections VIKINGv20170715 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCDEEPv20230713 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCDEEPv20240506 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCDR3 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCDR4 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCDR5 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20140428 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20140903 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20150309 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20151218 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20160311 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20160822 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20170109 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20170411 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20171101 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20180702 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20181120 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20191212 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20210708 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20230816 Short identification name for the filter section varchar 10     ??
shortName FilterSections VMCv20240226 Short identification name for the filter section varchar 10     ??
shortName FilterSections VSAQC Short identification name for the filter section varchar 10     ??
shortName FilterSections VVVDR5 Short identification name for the filter section varchar 10     ??
shortName FilterSections VVVXDR1 Short identification name for the filter section varchar 10     ??
shortName vmcRRLyraeLightCurves VMCv20240226 Filter name varchar 2     instr.bandpass
Si ravedr5Source RAVE [Si/H] abundance of Si real 4 dex   phys.abund.Z
Si_N ravedr5Source RAVE Number of used spectral lines in calc. of [Si/H] smallint 2     meta.number
siga sharksAstrometricInfo SHARKSv20210222 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga sharksAstrometricInfo SHARKSv20210421 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga ultravistaAstrometricInfo ULTRAVISTADR4 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vhsAstrometricInfo VHSDR6 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vhsAstrometricInfo VHSv20170630 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vhsAstrometricInfo VHSv20180419 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vhsAstrometricInfo VHSv20201209 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vhsAstrometricInfo VHSv20231101 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vhsAstrometricInfo VHSv20240731 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga videoAstrometricInfo VIDEODR2 Error on coefficient a float 8 arcsec -0.9999995e9 ??
siga videoAstrometricInfo VIDEODR3 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga videoAstrometricInfo VIDEODR4 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga videoAstrometricInfo VIDEODR5 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga videoAstrometricInfo VIDEOv20111208 Error on coefficient a float 8 arcsec -0.9999995e9 ??
siga vikingAstrometricInfo VIKINGDR2 Error on coefficient a float 8 arcsec -0.9999995e9 ??
siga vikingAstrometricInfo VIKINGDR3 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vikingAstrometricInfo VIKINGDR4 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vikingAstrometricInfo VIKINGv20110714 Error on coefficient a float 8 arcsec -0.9999995e9 ??
siga vikingAstrometricInfo VIKINGv20111019 Error on coefficient a float 8 arcsec -0.9999995e9 ??
siga vikingAstrometricInfo VIKINGv20130417 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vikingAstrometricInfo VIKINGv20140402 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vikingAstrometricInfo VIKINGv20150421 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vikingAstrometricInfo VIKINGv20151230 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vikingAstrometricInfo VIKINGv20160406 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vikingAstrometricInfo VIKINGv20161202 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vikingAstrometricInfo VIKINGv20170715 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCDR1 Error on coefficient a float 8 arcsec -0.9999995e9 ??
siga vmcAstrometricInfo VMCDR2 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCDR3 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCDR4 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCDR5 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20110816 Error on coefficient a float 8 arcsec -0.9999995e9 ??
siga vmcAstrometricInfo VMCv20110909 Error on coefficient a float 8 arcsec -0.9999995e9 ??
siga vmcAstrometricInfo VMCv20120126 Error on coefficient a float 8 arcsec -0.9999995e9 ??
siga vmcAstrometricInfo VMCv20121128 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20130304 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20130805 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20140428 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20140903 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20150309 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20151218 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20160311 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20160822 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20170109 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20170411 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20171101 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20180702 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20181120 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20191212 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20210708 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20230816 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcAstrometricInfo VMCv20240226 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcdeepAstrometricInfo VMCDEEPv20230713 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vmcdeepAstrometricInfo VMCDEEPv20240506 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vvvAstrometricInfo VVVDR1 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vvvAstrometricInfo VVVDR2 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vvvAstrometricInfo VVVDR5 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
siga vvvAstrometricInfo VVVv20110718 Error on coefficient a float 8 arcsec -0.9999995e9 ??
siga vvvxAstrometricInfo VVVXDR1 Error on coefficient a float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd sharksAstrometricInfo SHARKSv20210222 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd sharksAstrometricInfo SHARKSv20210421 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd ultravistaAstrometricInfo ULTRAVISTADR4 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vhsAstrometricInfo VHSDR6 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vhsAstrometricInfo VHSv20170630 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vhsAstrometricInfo VHSv20180419 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vhsAstrometricInfo VHSv20201209 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vhsAstrometricInfo VHSv20231101 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vhsAstrometricInfo VHSv20240731 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd videoAstrometricInfo VIDEODR2 Error on coefficient d float 8 arcsec -0.9999995e9 ??
sigd videoAstrometricInfo VIDEODR3 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd videoAstrometricInfo VIDEODR4 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd videoAstrometricInfo VIDEODR5 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd videoAstrometricInfo VIDEOv20111208 Error on coefficient d float 8 arcsec -0.9999995e9 ??
sigd vikingAstrometricInfo VIKINGDR2 Error on coefficient d float 8 arcsec -0.9999995e9 ??
sigd vikingAstrometricInfo VIKINGDR3 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vikingAstrometricInfo VIKINGDR4 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vikingAstrometricInfo VIKINGv20110714 Error on coefficient d float 8 arcsec -0.9999995e9 ??
sigd vikingAstrometricInfo VIKINGv20111019 Error on coefficient d float 8 arcsec -0.9999995e9 ??
sigd vikingAstrometricInfo VIKINGv20130417 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vikingAstrometricInfo VIKINGv20140402 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vikingAstrometricInfo VIKINGv20150421 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vikingAstrometricInfo VIKINGv20151230 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vikingAstrometricInfo VIKINGv20160406 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vikingAstrometricInfo VIKINGv20161202 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vikingAstrometricInfo VIKINGv20170715 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCDR1 Error on coefficient d float 8 arcsec -0.9999995e9 ??
sigd vmcAstrometricInfo VMCDR2 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCDR3 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCDR4 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCDR5 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20110816 Error on coefficient d float 8 arcsec -0.9999995e9 ??
sigd vmcAstrometricInfo VMCv20110909 Error on coefficient d float 8 arcsec -0.9999995e9 ??
sigd vmcAstrometricInfo VMCv20120126 Error on coefficient d float 8 arcsec -0.9999995e9 ??
sigd vmcAstrometricInfo VMCv20121128 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20130304 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20130805 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20140428 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20140903 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20150309 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20151218 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20160311 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20160822 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20170109 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20170411 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20171101 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20180702 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20181120 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20191212 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20210708 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20230816 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcAstrometricInfo VMCv20240226 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcdeepAstrometricInfo VMCDEEPv20230713 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vmcdeepAstrometricInfo VMCDEEPv20240506 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vvvAstrometricInfo VVVDR1 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vvvAstrometricInfo VVVDR2 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vvvAstrometricInfo VVVDR5 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigd vvvAstrometricInfo VVVv20110718 Error on coefficient d float 8 arcsec -0.9999995e9 ??
sigd vvvxAstrometricInfo VVVXDR1 Error on coefficient d float 8 arcsec -0.9999995e9 stat.fit;stat.stdev
sigDec sharksVariability SHARKSv20210222 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec sharksVariability SHARKSv20210421 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec ultravistaVariability ULTRAVISTADR4 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vhsSourceRemeasurement VHSDR1 Uncertainty in Dec real 4 Degrees -0.9999995e9 stat.error
sigDec videoSourceRemeasurement VIDEOv20100513 Uncertainty in Dec real 4 Degrees -0.9999995e9 stat.error
sigDec videoVariability VIDEODR2 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec videoVariability VIDEODR3 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec videoVariability VIDEODR4 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec videoVariability VIDEODR5 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec videoVariability VIDEOv20100513 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec videoVariability VIDEOv20111208 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vikingSourceRemeasurement VIKINGv20110714 Uncertainty in Dec real 4 Degrees -0.9999995e9 stat.error
sigDec vikingSourceRemeasurement VIKINGv20111019 Uncertainty in Dec real 4 Degrees -0.9999995e9 stat.error
sigDec vikingVariability VIKINGDR2 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vikingVariability VIKINGDR3 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vikingVariability VIKINGDR4 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vikingVariability VIKINGv20110714 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vikingVariability VIKINGv20111019 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vikingVariability VIKINGv20130417 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vikingVariability VIKINGv20140402 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vikingVariability VIKINGv20150421 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vikingVariability VIKINGv20151230 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vikingVariability VIKINGv20160406 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vikingVariability VIKINGv20161202 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vikingVariability VIKINGv20170715 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcSourceRemeasurement VMCv20110816 Uncertainty in Dec real 4 Degrees -0.9999995e9 stat.error
sigDec vmcSourceRemeasurement VMCv20110909 Uncertainty in Dec real 4 Degrees -0.9999995e9 stat.error
sigDec vmcVariability VMCDR1 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCDR2 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCDR3 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCDR4 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCDR5 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20110816 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20110909 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20120126 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20121128 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20130304 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20130805 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20140428 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20140903 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20150309 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20151218 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20160311 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20160822 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20170109 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20170411 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20171101 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20180702 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20181120 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20191212 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20210708 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20230816 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcVariability VMCv20240226 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcdeepVariability VMCDEEPv20230713 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vmcdeepVariability VMCDEEPv20240506 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vvvSourceRemeasurement VVVv20100531 Uncertainty in Dec real 4 Degrees -0.9999995e9 stat.error
sigDec vvvSourceRemeasurement VVVv20110718 Uncertainty in Dec real 4 Degrees -0.9999995e9 stat.error
sigDec vvvVariability VVVDR1 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vvvVariability VVVDR2 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vvvVariability VVVDR5 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vvvVariability VVVv20100531 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vvvVariability VVVv20110718 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigDec vvvxVariability VVVXDR1 Uncertainty in mean Dec real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigdec allwise_sc WISE One-sigma uncertainty in declination coordinate from the non-moving source extraction. float 8 arcsec    
sigdec catwise_2020, catwise_prelim WISE uncertainty in dec (arcsec) real 4 arcsec    
sigdec wise_allskysc WISE One-sigma uncertainty in declination coordinate real 4 arcsec    
sigdec wise_prelimsc WISE One-sigma uncertainty in declination coordinate
CAUTION: The declination uncertainty is overestimated for the majority of sources in the Preliminary Release Source Catalog. Sigdec was computed by adding 0.5 arcsec in quadrature to the extraction measurement uncertainty to reflect the impact of the declination bias error known to affect a fraction of source fainter than W1~13.0 mag
real 4 arcsec    
sigdec_pm allwise_sc WISE One-sigma uncertainty in declination from the profile-fitting measurement model that includes motion. This column is null if the motion-fit failed to converge or was not attempted. float 8 arcsec    
sigdec_pm catwise_2020, catwise_prelim WISE uncertainty in dec_pm real 4 arcsec    
sigDecCen ultravistaSourceRemeasurement ULTRAVISTADR4 Uncertainty in Dec of centroid real 4 Degrees -0.9999995e9 stat.error;pos.eq.dec
sigDecCen vikingZY_selJ_SourceRemeasurement VIKINGZYSELJv20160909 Uncertainty in Dec of centroid real 4 Degrees -0.9999995e9 stat.error;pos.eq.dec
sigDecCen vikingZY_selJ_SourceRemeasurement VIKINGZYSELJv20170124 Uncertainty in Dec of centroid real 4 Degrees -0.9999995e9 stat.error;pos.eq.dec
sigMuDec sharksVariability SHARKSv20210222 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec sharksVariability SHARKSv20210421 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec ultravistaVariability ULTRAVISTADR4 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec videoVariability VIDEODR2 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec videoVariability VIDEODR3 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec videoVariability VIDEODR4 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec videoVariability VIDEODR5 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec videoVariability VIDEOv20100513 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec videoVariability VIDEOv20111208 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vikingVariability VIKINGDR2 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vikingVariability VIKINGDR3 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vikingVariability VIKINGDR4 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vikingVariability VIKINGv20110714 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vikingVariability VIKINGv20111019 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vikingVariability VIKINGv20130417 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vikingVariability VIKINGv20140402 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vikingVariability VIKINGv20150421 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vikingVariability VIKINGv20151230 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vikingVariability VIKINGv20160406 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vikingVariability VIKINGv20161202 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vikingVariability VIKINGv20170715 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCDR1 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCDR2 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCDR3 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCDR4 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCDR5 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20110816 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20110909 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20120126 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20121128 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20130304 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20130805 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20140428 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20140903 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20150309 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20151218 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20160311 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20160822 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20170109 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20170411 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20171101 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20180702 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20181120 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20191212 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20210708 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20230816 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcVariability VMCv20240226 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcdeepVariability VMCDEEPv20230713 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vmcdeepVariability VMCDEEPv20240506 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vvvVariability VVVDR1 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vvvVariability VVVDR2 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vvvVariability VVVDR5 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vvvVariability VVVv20100531 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vvvVariability VVVv20110718 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuDec vvvxVariability VVVXDR1 Error on proper motion in Dec real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa sharksVariability SHARKSv20210222 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa sharksVariability SHARKSv20210421 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa ultravistaVariability ULTRAVISTADR4 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa videoVariability VIDEODR2 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa videoVariability VIDEODR3 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa videoVariability VIDEODR4 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa videoVariability VIDEODR5 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa videoVariability VIDEOv20100513 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa videoVariability VIDEOv20111208 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vikingVariability VIKINGDR2 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vikingVariability VIKINGDR3 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vikingVariability VIKINGDR4 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vikingVariability VIKINGv20110714 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vikingVariability VIKINGv20111019 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vikingVariability VIKINGv20130417 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vikingVariability VIKINGv20140402 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vikingVariability VIKINGv20150421 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vikingVariability VIKINGv20151230 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vikingVariability VIKINGv20160406 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vikingVariability VIKINGv20161202 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vikingVariability VIKINGv20170715 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCDR1 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCDR2 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCDR3 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCDR4 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCDR5 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20110816 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20110909 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20120126 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20121128 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20130304 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20130805 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20140428 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20140903 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20150309 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20151218 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20160311 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20160822 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20170109 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20170411 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20171101 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20180702 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20181120 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20191212 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20210708 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20230816 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcVariability VMCv20240226 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcdeepVariability VMCDEEPv20230713 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vmcdeepVariability VMCDEEPv20240506 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vvvVariability VVVDR1 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vvvVariability VVVDR2 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vvvVariability VVVDR5 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vvvVariability VVVv20100531 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vvvVariability VVVv20110718 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigMuRa vvvxVariability VVVXDR1 Error on proper motion in RA real 4 mas/yr -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigPMDec catwise_2020, catwise_prelim WISE uncertainty in PMDec real 4 arcsec/yr    
sigpmdec allwise_sc WISE Uncertainty in the Dec motion estimated for this source. This column is null if the motion fit failed to converge or was not attempted. int 4 mas/year    
sigPMRA catwise_2020, catwise_prelim WISE uncertainty in PMRA real 4 arcsec/yr    
sigpmra allwise_sc WISE Uncertainty in the RA motion estimation. This column is null if the motion fit failed to converge or was not attempted. int 4 mas/year    
sigRa sharksVariability SHARKSv20210222 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa sharksVariability SHARKSv20210421 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa ultravistaVariability ULTRAVISTADR4 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vhsSourceRemeasurement VHSDR1 Uncertainty in RA real 4 Degrees -0.9999995e9 stat.error
sigRa videoSourceRemeasurement VIDEOv20100513 Uncertainty in RA real 4 Degrees -0.9999995e9 stat.error
sigRa videoVariability VIDEODR2 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa videoVariability VIDEODR3 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa videoVariability VIDEODR4 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa videoVariability VIDEODR5 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa videoVariability VIDEOv20100513 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa videoVariability VIDEOv20111208 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vikingSourceRemeasurement VIKINGv20110714 Uncertainty in RA real 4 Degrees -0.9999995e9 stat.error
sigRa vikingSourceRemeasurement VIKINGv20111019 Uncertainty in RA real 4 Degrees -0.9999995e9 stat.error
sigRa vikingVariability VIKINGDR2 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vikingVariability VIKINGDR3 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vikingVariability VIKINGDR4 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vikingVariability VIKINGv20110714 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vikingVariability VIKINGv20111019 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vikingVariability VIKINGv20130417 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vikingVariability VIKINGv20140402 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vikingVariability VIKINGv20150421 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vikingVariability VIKINGv20151230 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vikingVariability VIKINGv20160406 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vikingVariability VIKINGv20161202 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vikingVariability VIKINGv20170715 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcSourceRemeasurement VMCv20110816 Uncertainty in RA real 4 Degrees -0.9999995e9 stat.error
sigRa vmcSourceRemeasurement VMCv20110909 Uncertainty in RA real 4 Degrees -0.9999995e9 stat.error
sigRa vmcVariability VMCDR1 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCDR2 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCDR3 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCDR4 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCDR5 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20110816 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20110909 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20120126 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20121128 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20130304 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20130805 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20140428 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20140903 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20150309 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20151218 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20160311 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20160822 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20170109 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20170411 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20171101 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20180702 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20181120 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20191212 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20210708 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20230816 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcVariability VMCv20240226 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcdeepVariability VMCDEEPv20230713 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vmcdeepVariability VMCDEEPv20240506 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vvvSourceRemeasurement VVVv20100531 Uncertainty in RA real 4 Degrees -0.9999995e9 stat.error
sigRa vvvSourceRemeasurement VVVv20110718 Uncertainty in RA real 4 Degrees -0.9999995e9 stat.error
sigRa vvvVariability VVVDR1 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vvvVariability VVVDR2 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vvvVariability VVVDR5 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vvvVariability VVVv20100531 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vvvVariability VVVv20110718 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigRa vvvxVariability VVVXDR1 Uncertainty in mean RA real 4 Degrees -0.9999995e9 stat.error
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
sigra allwise_sc WISE One-sigma uncertainty in right ascension coordinate from the non-moving source extraction. float 8 arcsec    
sigra catwise_2020, catwise_prelim WISE uncertainty in ra (arcsec) real 4 arcsec    
sigra wise_allskysc, wise_prelimsc WISE One-sigma uncertainty in right ascension coordinate real 4 arcsec    
sigra_pm allwise_sc WISE One-sigma uncertainty in right ascension from the profile-fitting measurement model that includes motion. This column is null if the motion-fit failed to converge or was not attempted. float 8 arcsec    
sigra_pm catwise_2020, catwise_prelim WISE uncertainty in ra_pm real 4 arcsec    
sigRaCen ultravistaSourceRemeasurement ULTRAVISTADR4 Uncertainty in RA of centroid real 4 Degrees -0.9999995e9 stat.error;pos.eq.ra
sigRaCen vikingZY_selJ_SourceRemeasurement VIKINGZYSELJv20160909 Uncertainty in RA of centroid real 4 Degrees -0.9999995e9 stat.error;pos.eq.ra
sigRaCen vikingZY_selJ_SourceRemeasurement VIKINGZYSELJv20170124 Uncertainty in RA of centroid real 4 Degrees -0.9999995e9 stat.error;pos.eq.ra
sigradec allwise_sc WISE The co-sigma of the equatorial position uncertainties, sigra, sigdec (σα, σδ). The covariance between the position errors, Vαδ, can be derived from the quoted co-sigma, σαδ, by the formula Vαδ = σαδ×|σαδ|. This maintains the sign information for the covariance since σαδ may be negative. It is more natural to carry the co-sigma along with the other uncertainties instead of the covariance because the former is in the same units as the other uncertainties. float 8 arcsec    
sigradec catwise_2020, catwise_prelim WISE uncertainty cross-term (arcsec) real 4 arcsec    
sigradec wise_allskysc WISE The co-sigma of the equatorial position uncertainties, sig_ra, sig_dec (σα, σδ). The co-sigma is related to the covariance between the position errors Vαδ by the formula Vαδ = σαδ×|σαδ|. This maintains the sign information for the correlation, since σαδ may be negative. It is more natural to carry the co-sigma along with the other uncertainties instead of the covariance because the former is in the same units as the other uncertainties. real 4 degrees    
sigradec wise_prelimsc WISE The co-sigma of the equatorial position uncertainties, (sig_ra, sig_dec) real 4 degrees    
sigradec_pm allwise_sc WISE The co-sigma of the equatorial position uncertainties from the profile-fitting measurement model that includes motion, sigra_pm, sigdec_pm (σα_pm, σδ_pm). The covariance between the position errors, Vα_pmδ_pm, can be derived from the quoted co-sigma, σα_pmδ_pm, by the formula α_pmδ_pm = σα_pmδ_pm×|σα_pmδ_pm|. This maintains the sign information for the covariance since σα_pmδ_pm may be negative. It is more natural to carry the co-sigma along with the other uncertainties instead of the covariance because the former is in the same units as the other uncertainties. This column is null if the motion-fit failed to converge or was not attempted. float 8 arcsec    
sigradec_pm catwise_2020, catwise_prelim WISE uncertainty cross-term real 4 arcsec    
skewness phot_variable_time_series_g_fov_statistical_parameters GAIADR1 Standardized unweighted skewness of the G-band time series values float 8     stat.value
sky Detection PS1DR2 Background sky level. real 4 Janskys/arcsec^2 -999  
sky sharksDetection SHARKSv20210222 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky sharksDetection SHARKSv20210421 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky ultravistaDetection, ultravistaMapRemeasurement ULTRAVISTADR4 local interpolated sky level from background tracker (SE: BACKGROUND) {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSDR2 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSDR3 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSDR4 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSDR5 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSDR6 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSv20120926 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSv20130417 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSv20140409 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSv20150108 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSv20160114 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSv20160507 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSv20170630 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSv20180419 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSv20201209 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSv20231101 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection VHSv20240731 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vhsDetection, vhsListRemeasurement VHSDR1 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky videoDetection VIDEODR2 local interpolated sky level from background tracker (SE: BACKGROUND) {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky videoDetection VIDEODR3 local interpolated sky level from background tracker (SE: BACKGROUND) {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky videoDetection VIDEODR4 local interpolated sky level from background tracker (SE: BACKGROUND) {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky videoDetection VIDEODR5 local interpolated sky level from background tracker (SE: BACKGROUND) {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky videoDetection VIDEOv20100513 local interpolated sky level from background tracker (SE: BACKGROUND) {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky videoDetection VIDEOv20111208 local interpolated sky level from background tracker (SE: BACKGROUND) {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky videoListRemeasurement VIDEOv20100513 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingDetection VIKINGDR2 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingDetection VIKINGDR3 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingDetection VIKINGDR4 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingDetection VIKINGv20111019 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingDetection VIKINGv20130417 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingDetection VIKINGv20140402 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingDetection VIKINGv20150421 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingDetection VIKINGv20151230 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingDetection VIKINGv20160406 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingDetection VIKINGv20161202 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingDetection VIKINGv20170715 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingDetection, vikingListRemeasurement VIKINGv20110714 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingMapRemeasurement VIKINGZYSELJv20160909 local interpolated sky level from background tracker (SE: BACKGROUND) {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vikingMapRemeasurement VIKINGZYSELJv20170124 local interpolated sky level from background tracker (SE: BACKGROUND) {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCDR1 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCDR2 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCDR3 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCDR4 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCDR5 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20110909 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20120126 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20121128 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20130304 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20130805 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20140428 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20140903 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20150309 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20151218 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20160311 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20160822 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20170109 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20170411 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20171101 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20180702 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20181120 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20191212 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20210708 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20230816 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection VMCv20240226 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcDetection, vmcListRemeasurement VMCv20110816 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcdeepDetection VMCDEEPv20230713 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vmcdeepDetection VMCDEEPv20240506 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vvvDetection VVVDR1 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vvvDetection VVVDR2 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vvvDetection, vvvDetectionPawPrints, vvvDetectionTiles VVVDR5 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky vvvDetection, vvvListRemeasurement VVVv20100531 local interpolated sky level from background tracker {catalogue TType keyword: Sky_level} real 4 ADU   instr.skyLevel
sky1 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Local sky bkg. for band 1 flux real 4 MJy/sr -999.9  
sky160 sage_lmcMips160Source SPITZER Local sky background for band 160 real 4 MJy/sr    
sky2 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Local sky bkg. for band 2 flux real 4 MJy/sr -999.9  
sky24 sage_lmcMips24Source SPITZER Local sky background for band 24 real 4 MJy/sr    
sky3 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Local sky bkg. for band 3 flux real 4 MJy/sr -999.9  
sky3_6 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Local sky background for 3.6um IRAC (Band 1) real 4 MJy/sr -999.9  
sky3_6 sage_lmcIracSource SPITZER Local sky bkg. for band 3.6 real 4 MJy/sr    
sky3_6 sage_smcIRACv1_5Source SPITZER Local sky background for 3.6um IRAC (Band 1). See Appendix B of GLIMPSE Photometry (v1.0) document. real 4 MJy/sr    
sky4 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Local sky bkg. for band 4 flux real 4 MJy/sr -999.9  
sky4_5 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Local sky background for 4.5um IRAC (Band 2) real 4 MJy/sr -999.9  
sky4_5 sage_lmcIracSource SPITZER Local sky bkg. for band 4.5 real 4 MJy/sr    
sky4_5 sage_smcIRACv1_5Source SPITZER Local sky background for 4.5um IRAC (Band 2). See Appendix B of GLIMPSE Photometry (v1.0) document. real 4 MJy/sr    
sky5_8 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Local sky background for 5.8um IRAC (Band 3) real 4 MJy/sr -999.9  
sky5_8 sage_lmcIracSource SPITZER Local sky bkg. for band 5.8 real 4 MJy/sr    
sky5_8 sage_smcIRACv1_5Source SPITZER Local sky background for 5.8um IRAC (Band 3). See Appendix B of GLIMPSE Photometry (v1.0) document. real 4 MJy/sr    
sky70 sage_lmcMips70Source SPITZER Local sky background for band 70 real 4 MJy/sr    
sky8_0 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Local sky background for 8.0um IRAC (Band 4) real 4 MJy/sr -999.9  
sky8_0 sage_lmcIracSource SPITZER Local sky bkg. for band 8.0 real 4 MJy/sr    
sky8_0 sage_smcIRACv1_5Source SPITZER Local sky background for 8.0um IRAC (Band 4). See Appendix B of GLIMPSE Photometry (v1.0) document. real 4 MJy/sr    
skyAlgorithm Multiframe SHARKSv20210222 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe SHARKSv20210421 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe ULTRAVISTADR4 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSDR1 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSDR2 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSDR3 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSDR4 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSDR5 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSDR6 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSv20120926 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSv20130417 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSv20140409 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSv20150108 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSv20160114 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSv20160507 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSv20170630 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSv20180419 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSv20201209 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSv20231101 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VHSv20240731 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIDEODR2 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIDEODR3 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIDEODR4 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIDEODR5 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIDEOv20100513 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIDEOv20111208 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIKINGDR2 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIKINGDR3 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIKINGDR4 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIKINGv20110714 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIKINGv20111019 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIKINGv20130417 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIKINGv20140402 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIKINGv20150421 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIKINGv20151230 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIKINGv20160406 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIKINGv20161202 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VIKINGv20170715 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCDEEPv20230713 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCDEEPv20240506 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCDR1 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCDR2 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCDR3 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCDR4 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCDR5 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20110816 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20110909 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20120126 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20121128 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20130304 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20130805 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20140428 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20140903 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20150309 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20151218 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20160311 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20160822 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20170109 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20170411 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20171101 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20180702 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20181120 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20191212 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20210708 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20230816 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VMCv20240226 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VVVDR1 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VVVDR2 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VVVDR5 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VVVXDR1 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VVVv20100531 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm Multiframe VVVv20110718 Sky estimation algorithm {image primary HDU keyword: SKYALGO} varchar 64   NONE  
skyAlgorithm sharksMultiframe, ultravistaMultiframe, vhsMultiframe, videoMultiframe, vikingMultiframe, vmcMultiframe, vvvMultiframe VSAQC Sky estimation algorithm varchar 64   NONE  
skyCellID ObjectThin PS1DR2 Skycell region identifier. tinyint 1   255 meta.id
skyCellID StackObjectThin PS1DR2 Skycell region identifier. tinyint 1   255  
skyCorrCat MultiframeDetector SHARKSv20210222 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector SHARKSv20210421 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector ULTRAVISTADR4 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSDR1 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSDR2 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSDR3 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSDR4 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSDR5 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSDR6 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSv20120926 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSv20130417 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSv20140409 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSv20150108 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSv20160114 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSv20160507 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSv20170630 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSv20180419 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSv20201209 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSv20231101 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VHSv20240731 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIDEODR2 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIDEODR3 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIDEODR4 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIDEODR5 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIDEOv20100513 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIDEOv20111208 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIKINGDR2 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIKINGDR3 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIKINGDR4 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIKINGv20110714 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIKINGv20111019 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIKINGv20130417 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIKINGv20140402 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIKINGv20150421 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIKINGv20151230 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIKINGv20160406 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIKINGv20161202 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VIKINGv20170715 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCDEEPv20230713 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCDEEPv20240506 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCDR1 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCDR2 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCDR3 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCDR4 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCDR5 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20110816 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20110909 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20120126 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20121128 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20130304 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20130805 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20140428 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20140903 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20150309 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20151218 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20160311 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20160822 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20170109 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20170411 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20171101 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20180702 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20181120 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20191212 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20210708 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20230816 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VMCv20240226 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VVVDR1 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VVVDR2 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VVVDR5 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VVVXDR1 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VVVv20100531 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat MultiframeDetector VVVv20110718 Percentage sky correction for the catalogue data {catalogue extension keyword:  PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrCat sharksMultiframeDetector, ultravistaMultiframeDetector, vhsMultiframeDetector, videoMultiframeDetector, vikingMultiframeDetector, vmcMultiframeDetector, vvvMultiframeDetector VSAQC Percentage sky correction for the catalogue data real 4   -0.9999995e9 ??
skyCorrExt MultiframeDetector SHARKSv20210222 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector SHARKSv20210421 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector ULTRAVISTADR4 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSDR1 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSDR2 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSDR3 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSDR4 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSDR5 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSDR6 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSv20120926 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSv20130417 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSv20140409 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSv20150108 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSv20160114 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSv20160507 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSv20170630 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSv20180419 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSv20201209 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSv20231101 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VHSv20240731 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIDEODR2 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIDEODR3 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIDEODR4 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIDEODR5 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIDEOv20100513 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIDEOv20111208 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIKINGDR2 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIKINGDR3 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIKINGDR4 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIKINGv20110714 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIKINGv20111019 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIKINGv20130417 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIKINGv20140402 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIKINGv20150421 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIKINGv20151230 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIKINGv20160406 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIKINGv20161202 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VIKINGv20170715 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCDEEPv20230713 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCDEEPv20240506 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCDR1 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCDR2 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCDR3 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCDR4 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCDR5 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20110816 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20110909 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20120126 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20121128 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20130304 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20130805 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20140428 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20140903 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20150309 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20151218 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20160311 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20160822 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20170109 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20170411 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20171101 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20180702 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20181120 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20191212 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20210708 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20230816 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VMCv20240226 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VVVDR1 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VVVDR2 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VVVDR5 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VVVXDR1 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VVVv20100531 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt MultiframeDetector VVVv20110718 Percentage sky correction of the detector {image extension keyword: PERCORR}
corrected photometry = 2.5×log10(flux) + aperCor + skyCorr
real 4   -0.9999995e9 ??
This is a correction based on the median dark sky recorded in science frames compared to the median for all the detectors and as such is an ancillary correction to the gain correction derived from the flatfield (usually twilight flats) data.
skyCorrExt sharksMultiframeDetector, ultravistaMultiframeDetector, vhsMultiframeDetector, videoMultiframeDetector, vikingMultiframeDetector, vmcMultiframeDetector, vvvMultiframeDetector VSAQC Percentage sky correction of the detector real 4   -0.9999995e9 ??
skyErr Detection PS1DR2 Error in background sky level. real 4 Janskys/arcsec^2 -999  
skyID Multiframe SHARKSv20210222 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe SHARKSv20210421 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe ULTRAVISTADR4 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSDR1 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSDR2 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSDR3 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSDR4 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSDR5 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSDR6 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSv20120926 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSv20130417 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSv20140409 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSv20150108 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSv20160114 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSv20160507 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSv20170630 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSv20180419 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSv20201209 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSv20231101 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VHSv20240731 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIDEODR2 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIDEODR3 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIDEODR4 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIDEODR5 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIDEOv20100513 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIDEOv20111208 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIKINGDR2 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIKINGDR3 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIKINGDR4 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIKINGv20110714 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIKINGv20111019 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIKINGv20130417 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIKINGv20140402 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIKINGv20150421 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIKINGv20151230 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIKINGv20160406 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIKINGv20161202 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VIKINGv20170715 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCDEEPv20230713 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCDEEPv20240506 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCDR1 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCDR2 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCDR3 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCDR4 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCDR5 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20110816 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20110909 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20120126 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20121128 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20130304 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20130805 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20140428 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20140903 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20150309 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20151218 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20160311 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20160822 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20170109 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20170411 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20171101 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20180702 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20181120 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20191212 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20210708 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20230816 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VMCv20240226 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VVVDR1 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VVVDR2 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VVVDR5 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VVVXDR1 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VVVv20100531 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID Multiframe VVVv20110718 UID of library calibration sky sub frame {image extension keyword: SKYSUB} bigint 8   -99999999 obs.field
skyID sharksMultiframe, ultravistaMultiframe, vhsMultiframe, videoMultiframe, vikingMultiframe, vmcMultiframe, vvvMultiframe VSAQC UID of library calibration sky sub frame bigint 8   -99999999 obs.field
skyLevel MultiframeDetector SHARKSv20210222 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector SHARKSv20210421 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector ULTRAVISTADR4 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSDR1 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSDR2 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSDR3 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSDR4 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSDR5 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSDR6 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSv20120926 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSv20130417 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSv20140409 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSv20150108 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSv20160114 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSv20160507 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSv20170630 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSv20180419 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSv20201209 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSv20231101 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VHSv20240731 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIDEODR2 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIDEODR3 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIDEODR4 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIDEODR5 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIDEOv20100513 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIDEOv20111208 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIKINGDR2 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIKINGDR3 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIKINGDR4 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIKINGv20110714 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIKINGv20111019 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIKINGv20130417 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIKINGv20140402 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIKINGv20150421 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIKINGv20151230 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIKINGv20160406 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIKINGv20161202 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VIKINGv20170715 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCDEEPv20230713 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCDEEPv20240506 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCDR1 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCDR2 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCDR3 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCDR4 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCDR5 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20110816 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20110909 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20120126 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20121128 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20130304 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20130805 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20140428 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20140903 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20150309 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20151218 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20160311 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20160822 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20170109 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20170411 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20171101 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20180702 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20181120 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20191212 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20210708 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20230816 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VMCv20240226 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VVVDR1 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VVVDR2 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VVVDR5 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VVVXDR1 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VVVv20100531 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel MultiframeDetector VVVv20110718 Median sky brightness {catalogue extension keyword:  SKYLEVEL} real 4 counts/pixel -0.9999995e9 ??
An automatic 2D background-following algorithm is used to track and "remove" slowly varying background features such as image gradients etc.. The default scale size for background tracking (NBSIZE) is currently set to 64 pixels, coupled with a smidge of non-linear filtering this gives a background tracking scale of order 100 pixels. (A bilinear interpolator is used to generate pixel resolution background maps internally).
skyLevel sharksMultiframeDetector, ultravistaMultiframeDetector, vhsMultiframeDetector, videoMultiframeDetector, vikingMultiframeDetector, vmcMultiframeDetector, vvvMultiframeDetector VSAQC Median sky brightness real 4 counts/pixel -0.9999995e9 ??
skyNoise MultiframeDetector SHARKSv20210222 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector SHARKSv20210421 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector ULTRAVISTADR4 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSDR1 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSDR2 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSDR3 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSDR4 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSDR5 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSDR6 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSv20120926 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSv20130417 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSv20140409 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSv20150108 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSv20160114 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSv20160507 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSv20170630 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSv20180419 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSv20201209 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSv20231101 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VHSv20240731 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIDEODR2 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIDEODR3 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIDEODR4 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIDEODR5 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIDEOv20100513 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIDEOv20111208 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIKINGDR2 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIKINGDR3 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIKINGDR4 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIKINGv20110714 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIKINGv20111019 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIKINGv20130417 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIKINGv20140402 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIKINGv20150421 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIKINGv20151230 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIKINGv20160406 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIKINGv20161202 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VIKINGv20170715 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCDEEPv20230713 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCDEEPv20240506 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCDR1 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCDR2 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCDR3 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCDR4 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCDR5 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20110816 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20110909 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20120126 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20121128 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20130304 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20130805 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20140428 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20140903 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20150309 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20151218 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20160311 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20160822 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20170109 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20170411 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20171101 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20180702 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20181120 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20191212 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20210708 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20230816 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VMCv20240226 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VVVDR1 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VVVDR2 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VVVDR5 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VVVXDR1 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VVVv20100531 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise MultiframeDetector VVVv20110718 Pixel noise at sky level {catalogue extension keyword:  SKYNOISE} real 4 counts -0.9999995e9 ??
Robust MAD estimator for noise scaled to equivalent Gaussian rms value ie. = MAD × 1.48 after removing large scale sky background variations. MAD = Median of the Absolute Deviations about the median.
skyNoise sharksMultiframeDetector, ultravistaMultiframeDetector, vhsMultiframeDetector, videoMultiframeDetector, vikingMultiframeDetector, vmcMultiframeDetector, vvvMultiframeDetector VSAQC Pixel noise at sky level real 4 counts -0.9999995e9 ??
skySubScale MultiframeDetector SHARKSv20210222 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector SHARKSv20210421 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector ULTRAVISTADR4 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSDR1 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSDR2 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSDR3 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSDR4 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSDR5 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSDR6 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSv20120926 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSv20130417 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSv20140409 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSv20150108 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSv20160114 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSv20160507 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSv20170630 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSv20180419 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSv20201209 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSv20231101 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VHSv20240731 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIDEODR2 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIDEODR3 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIDEODR4 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIDEODR5 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIDEOv20100513 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIDEOv20111208 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIKINGDR2 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIKINGDR3 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIKINGDR4 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIKINGv20110714 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIKINGv20111019 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIKINGv20130417 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIKINGv20140402 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIKINGv20150421 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIKINGv20151230 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIKINGv20160406 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIKINGv20161202 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VIKINGv20170715 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCDEEPv20230713 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCDEEPv20240506 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCDR1 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCDR2 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCDR3 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCDR4 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCDR5 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20110816 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20110909 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20120126 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20121128 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20130304 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20130805 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20140428 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20140903 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20150309 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20151218 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20160311 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20160822 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20170109 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20170411 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20171101 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20180702 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20181120 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20191212 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20210708 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20230816 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VMCv20240226 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VVVDR1 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VVVDR2 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VVVDR5 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VVVXDR1 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VVVv20100531 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale MultiframeDetector VVVv20110718 Scale factor applied to sky subtraction image {image extension keyword: SKYSUB} float 8   -0.9999995e9 ??
skySubScale sharksMultiframeDetector, ultravistaMultiframeDetector, vhsMultiframeDetector, videoMultiframeDetector, vikingMultiframeDetector, vmcMultiframeDetector, vvvMultiframeDetector VSAQC Scale factor applied to sky subtraction image float 8   -0.9999995e9 ??
skyVar sharksDetection SHARKSv20210222 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar sharksDetection SHARKSv20210421 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar ultravistaDetection, ultravistaMapRemeasurement ULTRAVISTADR4 local estimate of variation in sky level around image (SE: THRESHOLD) {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSDR2 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSDR3 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSDR4 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSDR5 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSDR6 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSv20120926 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSv20130417 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSv20140409 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSv20150108 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSv20160114 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSv20160507 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSv20170630 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSv20180419 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSv20201209 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSv20231101 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection VHSv20240731 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vhsDetection, vhsListRemeasurement VHSDR1 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar videoDetection VIDEODR2 local estimate of variation in sky level around image (SE: THRESHOLD) {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar videoDetection VIDEODR3 local estimate of variation in sky level around image (SE: THRESHOLD) {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar videoDetection VIDEODR4 local estimate of variation in sky level around image (SE: THRESHOLD) {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar videoDetection VIDEODR5 local estimate of variation in sky level around image (SE: THRESHOLD) {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar videoDetection VIDEOv20100513 local estimate of variation in sky level around image (SE: THRESHOLD) {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar videoDetection VIDEOv20111208 local estimate of variation in sky level around image (SE: THRESHOLD) {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar videoListRemeasurement VIDEOv20100513 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingDetection VIKINGDR2 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingDetection VIKINGDR3 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingDetection VIKINGDR4 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingDetection VIKINGv20111019 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingDetection VIKINGv20130417 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingDetection VIKINGv20140402 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingDetection VIKINGv20150421 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingDetection VIKINGv20151230 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingDetection VIKINGv20160406 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingDetection VIKINGv20161202 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingDetection VIKINGv20170715 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingDetection, vikingListRemeasurement VIKINGv20110714 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingMapRemeasurement VIKINGZYSELJv20160909 local estimate of variation in sky level around image (SE: THRESHOLD) {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vikingMapRemeasurement VIKINGZYSELJv20170124 local estimate of variation in sky level around image (SE: THRESHOLD) {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCDR1 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCDR2 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCDR3 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCDR4 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCDR5 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20110909 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20120126 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20121128 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20130304 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20130805 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20140428 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20140903 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20150309 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20151218 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20160311 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20160822 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20170109 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20170411 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20171101 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20180702 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20181120 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20191212 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20210708 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20230816 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection VMCv20240226 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcDetection, vmcListRemeasurement VMCv20110816 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcdeepDetection VMCDEEPv20230713 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vmcdeepDetection VMCDEEPv20240506 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vvvDetection VVVDR1 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vvvDetection VVVDR2 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vvvDetection, vvvDetectionPawPrints, vvvDetectionTiles VVVDR5 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
skyVar vvvDetection, vvvListRemeasurement VVVv20100531 local estimate of variation in sky level around image {catalogue TType keyword: Sky_rms} real 4 ADU   instr.skyLevel
slaveObjID sharksSourceNeighbours SHARKSv20210222 The unique ID of the neighbour in sharksSource (=sourceID) bigint 8     meta.dataset
slaveObjID sharksSourceNeighbours SHARKSv20210421 The unique ID of the neighbour in sharksSource (=sourceID) bigint 8     meta.dataset
slaveObjID sharksSourceXDetection SHARKSv20210222 The unique ID of the neighbour in sharksDetection table (=objID) bigint 8     meta.dataset
slaveObjID sharksSourceXDetection SHARKSv20210421 The unique ID of the neighbour in sharksDetection table (=objID) bigint 8     meta.dataset
slaveObjID sharksSourceXSSASource SHARKSv20210222 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID sharksSourceXSSASource SHARKSv20210421 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID sharksSourceXallwise_sc SHARKSv20210222 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID sharksSourceXallwise_sc SHARKSv20210421 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID sharksSourceXtwomass_psc SHARKSv20210222 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID sharksSourceXtwomass_psc SHARKSv20210421 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID sharksSourceXtwompzPhotoz SHARKSv20210222 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID sharksSourceXtwompzPhotoz SHARKSv20210421 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID sharksSourceXwiseScosPhotoz SHARKSv20210222 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID sharksSourceXwiseScosPhotoz SHARKSv20210421 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID sharksSourceXwise_allskysc SHARKSv20210222 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID sharksSourceXwise_allskysc SHARKSv20210421 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID ultravistaSourceNeighbours ULTRAVISTADR4 The unique ID of the neighbour in ultravistaSource (=sourceID) bigint 8     meta.dataset
slaveObjID ultravistaSourceXDR13PhotoObj ULTRAVISTADR4 The unique ID of the neighbour in BestDR13..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID ultravistaSourceXDR13PhotoObjAll ULTRAVISTADR4 The unique ID of the neighbour in BestDR13..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID ultravistaSourceXDetection ULTRAVISTADR4 The unique ID of the neighbour in ultravistaDetection table (=objID) bigint 8     meta.dataset
slaveObjID ultravistaSourceXGDR2gaia_source ULTRAVISTADR4 The unique ID of the neighbour in GAIADR2..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID ultravistaSourceXSSASource ULTRAVISTADR4 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID ultravistaSourceXallwise_sc ULTRAVISTADR4 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID ultravistaSourceXravedr5Source ULTRAVISTADR4 The unique ID of the neighbour in RAVE..ravedr5Source (=SourceID) bigint 8     meta.dataset
slaveObjID ultravistaSourceXtwomass_psc ULTRAVISTADR4 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID ultravistaSourceXtwompzPhotoz ULTRAVISTADR4 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID ultravistaSourceXwiseScosPhotoz ULTRAVISTADR4 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID ultravistaSourceXwise_allskysc ULTRAVISTADR4 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSDR1 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceNeighbours VHSDR2 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSDR3 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSDR4 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSDR5 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSDR6 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSv20120926 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSv20130417 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSv20140409 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSv20150108 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSv20160114 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSv20160507 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSv20170630 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSv20180419 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSv20201209 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSv20231101 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceNeighbours VHSv20240731 The unique ID of the neighbour in vhsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXAtlasDR1Source VHSDR2 The unique ID of the neighbour in ATLASDR1..atlasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR10lasSource VHSv20180419 The unique ID of the neighbour in UKIDSSDR10PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR10lasSource VHSv20201209 The unique ID of the neighbour in UKIDSSDR10PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR10lasSource VHSv20231101 The unique ID of the neighbour in UKIDSSDR10PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR10lasSource VHSv20240731 The unique ID of the neighbour in UKIDSSDR10PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR13PhotoObj VHSv20180419 The unique ID of the neighbour in BestDR13..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR13PhotoObj VHSv20201209 The unique ID of the neighbour in BestDR13..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR13PhotoObj VHSv20231101 The unique ID of the neighbour in BestDR13..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR13PhotoObj VHSv20240731 The unique ID of the neighbour in BestDR13..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR13PhotoObjAll VHSv20180419 The unique ID of the neighbour in BestDR13..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR13PhotoObjAll VHSv20201209 The unique ID of the neighbour in BestDR13..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR13PhotoObjAll VHSv20231101 The unique ID of the neighbour in BestDR13..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR13PhotoObjAll VHSv20240731 The unique ID of the neighbour in BestDR13..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSDR1 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSDR2 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSDR3 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSDR4 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSDR5 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSDR6 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSv20120926 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSv20130417 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSv20140409 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSv20150108 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSv20160114 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSv20160507 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSv20170630 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSv20180419 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSv20201209 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSv20231101 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR5lasSource VHSv20240731 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSDR1 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSDR2 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSDR3 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSDR4 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSDR5 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSDR6 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSv20120926 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSv20130417 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSv20140409 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSv20150108 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSv20160114 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSv20160507 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSv20170630 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSv20180419 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSv20201209 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSv20231101 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObj VHSv20240731 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSDR1 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSDR2 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSDR3 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSDR4 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSDR5 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSDR6 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSv20120926 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSv20130417 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSv20140409 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSv20150108 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSv20160114 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSv20160507 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSv20170630 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSv20180419 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSv20201209 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSv20231101 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR7PhotoObjAll VHSv20240731 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSDR1 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSDR2 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSDR3 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSDR4 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSDR5 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSDR6 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSv20120926 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSv20130417 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSv20140409 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSv20150108 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSv20160114 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSv20160507 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXDR8lasSource VHSv20170630 The unique ID of the neighbour in UKIDSSDR8PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR1gaia_source VHSDR6 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR1gaia_source VHSv20170630 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR1gaia_source VHSv20180419 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR1gaia_source VHSv20201209 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR1gaia_source VHSv20231101 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR1gaia_source VHSv20240731 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR1tgas_source VHSDR6 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR1tgas_source VHSv20170630 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR1tgas_source VHSv20180419 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR1tgas_source VHSv20201209 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR1tgas_source VHSv20231101 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR1tgas_source VHSv20240731 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR2gaia_source VHSv20201209 The unique ID of the neighbour in GAIADR2..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR2gaia_source VHSv20231101 The unique ID of the neighbour in GAIADR2..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGDR2gaia_source VHSv20240731 The unique ID of the neighbour in GAIADR2..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXGEDR3gaia_source VHSv20240731 The unique ID of the neighbour in GAIAEDR3..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSDR1 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXPawPrints VHSDR2 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSDR3 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSDR4 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSDR5 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSDR6 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSv20120926 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSv20130417 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSv20140409 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSv20150108 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSv20160114 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSv20160507 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSv20170630 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSv20180419 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSv20201209 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSv20231101 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXPawPrints VHSv20240731 The unique ID of the neighbour in vhsDetection table (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSKYMAP_masterDR2 VHSv20201209 The unique ID of the neighbour in SKYMAPPER..masterDR2 (=object_id) bigint 8     meta.dataset
slaveObjID vhsSourceXSKYMAP_masterDR2 VHSv20231101 The unique ID of the neighbour in SKYMAPPER..masterDR2 (=object_id) bigint 8     meta.dataset
slaveObjID vhsSourceXSKYMAP_masterDR2 VHSv20240731 The unique ID of the neighbour in SKYMAPPER..masterDR2 (=object_id) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSDR1 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXSSASource VHSDR2 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSDR3 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSDR4 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSDR5 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSDR6 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSv20120926 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSv20130417 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSv20140409 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSv20150108 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSv20160114 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSv20160507 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSv20170630 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSv20180419 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSv20201209 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSv20231101 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSSASource VHSv20240731 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObj VHSDR1 The unique ID of the neighbour in SEGUEDR6..PhotoObj (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObj VHSDR2 The unique ID of the neighbour in SEGUEDR6..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObj VHSDR3 The unique ID of the neighbour in SEGUEDR6..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObj VHSDR4 The unique ID of the neighbour in SEGUEDR6..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObj VHSDR5 The unique ID of the neighbour in SEGUEDR6..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObj VHSv20120926 The unique ID of the neighbour in SEGUEDR6..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObj VHSv20130417 The unique ID of the neighbour in SEGUEDR6..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObj VHSv20140409 The unique ID of the neighbour in SEGUEDR6..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObj VHSv20150108 The unique ID of the neighbour in SEGUEDR6..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObj VHSv20160114 The unique ID of the neighbour in SEGUEDR6..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObj VHSv20160507 The unique ID of the neighbour in SEGUEDR6..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObj VHSv20170630 The unique ID of the neighbour in SEGUEDR6..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObjAll VHSDR1 The unique ID of the neighbour in SEGUEDR6..PhotoObjAll (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObjAll VHSDR2 The unique ID of the neighbour in SEGUEDR6..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObjAll VHSDR3 The unique ID of the neighbour in SEGUEDR6..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObjAll VHSDR4 The unique ID of the neighbour in SEGUEDR6..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObjAll VHSDR5 The unique ID of the neighbour in SEGUEDR6..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObjAll VHSv20120926 The unique ID of the neighbour in SEGUEDR6..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObjAll VHSv20130417 The unique ID of the neighbour in SEGUEDR6..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObjAll VHSv20140409 The unique ID of the neighbour in SEGUEDR6..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObjAll VHSv20150108 The unique ID of the neighbour in SEGUEDR6..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObjAll VHSv20160114 The unique ID of the neighbour in SEGUEDR6..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObjAll VHSv20160507 The unique ID of the neighbour in SEGUEDR6..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXSegueDR6PhotoObjAll VHSv20170630 The unique ID of the neighbour in SEGUEDR6..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSDR1 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSDR2 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSDR3 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSDR4 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSDR5 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSDR6 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSv20120926 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSv20130417 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSv20140409 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSv20150108 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSv20160114 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSv20160507 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSv20170630 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSv20180419 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSv20201209 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSv20231101 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXStripe82PhotoObjAll VHSv20240731 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vhsSourceXallwise_sc VHSDR4 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXallwise_sc VHSDR5 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXallwise_sc VHSDR6 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXallwise_sc VHSv20150108 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXallwise_sc VHSv20160114 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXallwise_sc VHSv20160507 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXallwise_sc VHSv20170630 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXallwise_sc VHSv20180419 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXallwise_sc VHSv20201209 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXallwise_sc VHSv20231101 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXallwise_sc VHSv20240731 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXatlasDR1 VHSDR4 The unique ID of the neighbour in ATLASDR1..atlasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXatlasDR1 VHSDR5 The unique ID of the neighbour in ATLASDR1..atlasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXatlasDR1 VHSDR6 The unique ID of the neighbour in ATLASDR1..atlasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXatlasDR1 VHSv20160114 The unique ID of the neighbour in ATLASDR1..atlasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXatlasDR1 VHSv20160507 The unique ID of the neighbour in ATLASDR1..atlasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXatlasDR1 VHSv20170630 The unique ID of the neighbour in ATLASDR1..atlasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXatlasDR3 VHSv20180419 The unique ID of the neighbour in ATLASDR3..atlasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXatlasDR3 VHSv20201209 The unique ID of the neighbour in ATLASDR3..atlasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXatlasDR3 VHSv20231101 The unique ID of the neighbour in ATLASDR3..atlasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXatlasDR3 VHSv20240731 The unique ID of the neighbour in ATLASDR3..atlasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSDR1 The unique ID of the neighbour in FIRST..firstSource (=seqNo) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXfirstSource VHSDR2 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSDR3 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSDR4 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSDR5 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSDR6 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSv20130417 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSv20140409 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSv20150108 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSv20160114 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSv20160507 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSv20170630 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSv20180419 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSv20201209 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSv20231101 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource VHSv20240731 The unique ID of the neighbour in FIRST..firstSource12Feb16 (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXfirstSource12Feb16 VHSv20120926 The unique ID of the neighbour in FIRST..firstSource (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSDR1 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXiras_psc VHSDR2 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSDR3 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSDR4 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSDR5 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSDR6 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSv20120926 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSv20130417 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSv20140409 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSv20150108 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSv20160114 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSv20160507 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSv20170630 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSv20180419 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSv20201209 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSv20231101 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXiras_psc VHSv20240731 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSDR1 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXmgcDetection VHSDR2 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSDR3 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSDR4 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSDR5 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSDR6 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSv20120926 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSv20130417 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSv20140409 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSv20150108 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSv20160114 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSv20160507 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSv20170630 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSv20180419 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSv20201209 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSv20231101 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXmgcDetection VHSv20240731 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vhsSourceXnvssSource VHSDR1 The unique ID of the neighbour in NVSS..nvssSource (=seqNo) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXnvssSource VHSv20120926 The unique ID of the neighbour in NVSS..nvssSource (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXnvssSource VHSv20130417 The unique ID of the neighbour in NVSS..nvssSource (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSDR1 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSDR2 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSDR3 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSDR4 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSDR5 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSDR6 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSv20120926 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSv20130417 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSv20140409 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSv20150108 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSv20160114 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSv20160507 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSv20170630 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSv20180419 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSv20201209 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSv20231101 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_bsc VHSv20240731 The unique ID of the neighbour in ROSAT..rosat_bsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSDR1 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSDR2 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSDR3 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSDR4 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSDR5 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSDR6 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSv20120926 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSv20130417 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSv20140409 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSv20150108 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSv20160114 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSv20160507 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSv20170630 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSv20180419 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSv20201209 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSv20231101 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXrosat_fsc VHSv20240731 The unique ID of the neighbour in ROSAT..rosat_fsc (=seqNo) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSDR1 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSDR2 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSDR3 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSDR4 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSDR5 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSDR6 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSv20120926 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSv20130417 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSv20140409 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSv20150108 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSv20160114 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSv20160507 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSv20170630 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSv20180419 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSv20201209 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSv20231101 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_psc VHSv20240731 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSDR1 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSDR2 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSDR3 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSDR4 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSDR5 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSDR6 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSv20120926 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSv20130417 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSv20140409 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSv20150108 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSv20160114 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSv20160507 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSv20170630 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSv20180419 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSv20201209 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSv20231101 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_sixx2_xsc VHSv20240731 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSDR1 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSDR2 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSDR3 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSDR4 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSDR5 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSDR6 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSv20120926 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSv20130417 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSv20140409 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSv20150108 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSv20160114 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSv20160507 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSv20170630 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSv20180419 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSv20201209 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSv20231101 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwomass_xsc VHSv20240731 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vhsSourceXtwompzPhotoz VHSDR5 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwompzPhotoz VHSDR6 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwompzPhotoz VHSv20170630 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwompzPhotoz VHSv20180419 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwompzPhotoz VHSv20201209 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwompzPhotoz VHSv20231101 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwompzPhotoz VHSv20240731 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSDR1 The unique ID of the neighbour in TWOXMM..twoxmm (=DETID) bigint 8     meta.id;meta.dataset
slaveObjID vhsSourceXtwoxmm VHSDR2 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSDR3 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSDR4 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSDR5 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSDR6 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSv20120926 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSv20130417 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSv20140409 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSv20150108 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSv20160114 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSv20160507 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSv20170630 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSv20180419 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSv20201209 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSv20231101 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXtwoxmm VHSv20240731 The unique ID of the neighbour in TWOXMM..twoxmmi_dr3_v1_0 (=DETID) bigint 8     meta.dataset
slaveObjID vhsSourceXwiseScosPhotoz VHSDR5 The unique ID of the neighbour in WISExSCOS..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vhsSourceXwiseScosPhotoz VHSDR6 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vhsSourceXwiseScosPhotoz VHSv20170630 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vhsSourceXwiseScosPhotoz VHSv20180419 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vhsSourceXwiseScosPhotoz VHSv20201209 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vhsSourceXwiseScosPhotoz VHSv20231101 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vhsSourceXwiseScosPhotoz VHSv20240731 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSDR2 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSDR3 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSDR4 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSDR5 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSDR6 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSv20120926 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSv20130417 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSv20140409 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSv20150108 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSv20160114 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSv20160507 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSv20170630 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSv20180419 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSv20201209 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSv20231101 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_allskysc VHSv20240731 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vhsSourceXwise_prelimsc VHSDR1 The unique ID of the neighbour in WISE..wise_prelimsc (=cntr) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceNeighbours VIDEODR2 The unique ID of the neighbour in videoSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceNeighbours VIDEODR3 The unique ID of the neighbour in videoSource (=sourceID) bigint 8     meta.dataset
slaveObjID videoSourceNeighbours VIDEODR4 The unique ID of the neighbour in videoSource (=sourceID) bigint 8     meta.dataset
slaveObjID videoSourceNeighbours VIDEODR5 The unique ID of the neighbour in videoSource (=sourceID) bigint 8     meta.dataset
slaveObjID videoSourceNeighbours VIDEOv20100513 The unique ID of the neighbour in videoSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceNeighbours VIDEOv20111208 The unique ID of the neighbour in videoSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXDetection VIDEODR2 The unique ID of the neighbour in videoDetection table (=objID) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXDetection VIDEODR3 The unique ID of the neighbour in videoDetection table (=objID) bigint 8     meta.dataset
slaveObjID videoSourceXDetection VIDEODR4 The unique ID of the neighbour in videoDetection table (=objID) bigint 8     meta.dataset
slaveObjID videoSourceXDetection VIDEODR5 The unique ID of the neighbour in videoDetection table (=objID) bigint 8     meta.dataset
slaveObjID videoSourceXDetection VIDEOv20100513 The unique ID of the neighbour in videoDetection table (=objID) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXDetection VIDEOv20111208 The unique ID of the neighbour in videoDetection table (=objID) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXSSASource VIDEODR2 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXSSASource VIDEODR3 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID videoSourceXSSASource VIDEODR4 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID videoSourceXSSASource VIDEODR5 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID videoSourceXSSASource VIDEOv20100513 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXSSASource VIDEOv20111208 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXStripe82PhotoObjAll VIDEODR2 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXStripe82PhotoObjAll VIDEODR3 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID videoSourceXStripe82PhotoObjAll VIDEODR4 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID videoSourceXStripe82PhotoObjAll VIDEODR5 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID videoSourceXStripe82PhotoObjAll VIDEOv20100513 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXStripe82PhotoObjAll VIDEOv20111208 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXallwise_sc VIDEODR4 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID videoSourceXallwise_sc VIDEODR5 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID videoSourceXtwomass_psc VIDEODR2 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXtwomass_psc VIDEODR3 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID videoSourceXtwomass_psc VIDEODR4 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID videoSourceXtwomass_psc VIDEODR5 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID videoSourceXtwomass_psc VIDEOv20100513 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXtwomass_psc VIDEOv20111208 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXtwomass_xsc VIDEODR2 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXtwomass_xsc VIDEODR3 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID videoSourceXtwomass_xsc VIDEODR4 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID videoSourceXtwomass_xsc VIDEODR5 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID videoSourceXtwomass_xsc VIDEOv20100513 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXtwomass_xsc VIDEOv20111208 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXwise_allskysc VIDEODR3 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID videoSourceXwise_allskysc VIDEODR4 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID videoSourceXwise_allskysc VIDEODR5 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID videoSourceXwise_prelimsc VIDEODR2 The unique ID of the neighbour in WISE..wise_prelimsc (=cntr) bigint 8     meta.id;meta.dataset
slaveObjID videoSourceXwise_prelimsc VIDEOv20111208 The unique ID of the neighbour in WISE..wise_prelimsc (=cntr) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceNeighbours VIKINGDR2 The unique ID of the neighbour in vikingSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceNeighbours VIKINGDR3 The unique ID of the neighbour in vikingSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceNeighbours VIKINGDR4 The unique ID of the neighbour in vikingSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceNeighbours VIKINGv20110714 The unique ID of the neighbour in vikingSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceNeighbours VIKINGv20111019 The unique ID of the neighbour in vikingSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceNeighbours VIKINGv20130417 The unique ID of the neighbour in vikingSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceNeighbours VIKINGv20140402 The unique ID of the neighbour in vikingSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceNeighbours VIKINGv20150421 The unique ID of the neighbour in vikingSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceNeighbours VIKINGv20151230 The unique ID of the neighbour in vikingSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceNeighbours VIKINGv20160406 The unique ID of the neighbour in vikingSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceNeighbours VIKINGv20161202 The unique ID of the neighbour in vikingSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceNeighbours VIKINGv20170715 The unique ID of the neighbour in vikingSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceXAtlasDR1Source VIKINGDR3 The unique ID of the neighbour in ATLASDR1..atlasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR5lasSource VIKINGDR2 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXDR5lasSource VIKINGDR3 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR5lasSource VIKINGDR4 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR5lasSource VIKINGv20110714 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXDR5lasSource VIKINGv20111019 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXDR5lasSource VIKINGv20130417 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR5lasSource VIKINGv20140402 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR5lasSource VIKINGv20150421 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR5lasSource VIKINGv20151230 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR5lasSource VIKINGv20160406 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR5lasSource VIKINGv20161202 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR5lasSource VIKINGv20170715 The unique ID of the neighbour in UKIDSSDR5PLUS..lasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObj VIKINGDR2 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXDR7PhotoObj VIKINGDR3 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObj VIKINGDR4 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObj VIKINGv20110714 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXDR7PhotoObj VIKINGv20111019 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXDR7PhotoObj VIKINGv20130417 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObj VIKINGv20140402 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObj VIKINGv20150421 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObj VIKINGv20151230 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObj VIKINGv20160406 The unique ID of the neighbour in BestDR7..PhotoObj (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObjAll VIKINGDR2 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXDR7PhotoObjAll VIKINGDR3 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObjAll VIKINGDR4 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObjAll VIKINGv20110714 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXDR7PhotoObjAll VIKINGv20111019 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXDR7PhotoObjAll VIKINGv20130417 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObjAll VIKINGv20140402 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObjAll VIKINGv20150421 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObjAll VIKINGv20151230 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDR7PhotoObjAll VIKINGv20160406 The unique ID of the neighbour in BestDR7..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDetection VIKINGDR2 The unique ID of the neighbour in vikingDetection table (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXDetection VIKINGDR3 The unique ID of the neighbour in vikingDetection table (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDetection VIKINGDR4 The unique ID of the neighbour in vikingDetection table (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDetection VIKINGv20110714 The unique ID of the neighbour in vikingDetection table (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXDetection VIKINGv20111019 The unique ID of the neighbour in vikingDetection table (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXDetection VIKINGv20130417 The unique ID of the neighbour in vikingDetection table (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDetection VIKINGv20140402 The unique ID of the neighbour in vikingDetection table (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDetection VIKINGv20150421 The unique ID of the neighbour in vikingDetection table (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDetection VIKINGv20151230 The unique ID of the neighbour in vikingDetection table (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDetection VIKINGv20160406 The unique ID of the neighbour in vikingDetection table (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDetection VIKINGv20161202 The unique ID of the neighbour in vikingDetection table (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXDetection VIKINGv20170715 The unique ID of the neighbour in vikingDetection table (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXGDR1gaia_source VIKINGv20170715 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vikingSourceXGDR1tgas_source VIKINGv20170715 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vikingSourceXSSASource VIKINGDR2 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXSSASource VIKINGDR3 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXSSASource VIKINGDR4 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXSSASource VIKINGv20110714 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXSSASource VIKINGv20111019 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXSSASource VIKINGv20130417 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXSSASource VIKINGv20140402 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXSSASource VIKINGv20150421 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXSSASource VIKINGv20151230 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXSSASource VIKINGv20160406 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXSSASource VIKINGv20161202 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXSSASource VIKINGv20170715 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXStripe82PhotoObjAll VIKINGDR2 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXStripe82PhotoObjAll VIKINGDR3 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXStripe82PhotoObjAll VIKINGDR4 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXStripe82PhotoObjAll VIKINGv20110714 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXStripe82PhotoObjAll VIKINGv20111019 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXStripe82PhotoObjAll VIKINGv20130417 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXStripe82PhotoObjAll VIKINGv20140402 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXStripe82PhotoObjAll VIKINGv20150421 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXStripe82PhotoObjAll VIKINGv20151230 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXStripe82PhotoObjAll VIKINGv20160406 The unique ID of the neighbour in Stripe82..PhotoObjAll (=objID) bigint 8     meta.dataset
slaveObjID vikingSourceXallwise_sc VIKINGv20150421 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXallwise_sc VIKINGv20151230 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXallwise_sc VIKINGv20160406 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXallwise_sc VIKINGv20161202 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXallwise_sc VIKINGv20170715 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ngpSource VIKINGDR2 The unique ID of the neighbour in TWODFGRS..grs_ngpSource (=SEQNUM) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXgrs_ngpSource VIKINGDR3 The unique ID of the neighbour in TWODFGRS..grs_ngpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ngpSource VIKINGDR4 The unique ID of the neighbour in TWODFGRS..grs_ngpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ngpSource VIKINGv20110714 The unique ID of the neighbour in TWODFGRS..grs_ngpSource (=SEQNUM) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXgrs_ngpSource VIKINGv20111019 The unique ID of the neighbour in TWODFGRS..grs_ngpSource (=SEQNUM) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXgrs_ngpSource VIKINGv20130417 The unique ID of the neighbour in TWODFGRS..grs_ngpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ngpSource VIKINGv20140402 The unique ID of the neighbour in TWODFGRS..grs_ngpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ngpSource VIKINGv20150421 The unique ID of the neighbour in TWODFGRS..grs_ngpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ngpSource VIKINGv20151230 The unique ID of the neighbour in TWODFGRS..grs_ngpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ngpSource VIKINGv20160406 The unique ID of the neighbour in TWODFGRS..grs_ngpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ngpSource VIKINGv20161202 The unique ID of the neighbour in TWODFGRS..grs_ngpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ngpSource VIKINGv20170715 The unique ID of the neighbour in TWODFGRS..grs_ngpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ranSource VIKINGDR2 The unique ID of the neighbour in TWODFGRS..grs_ranSource (=SEQNUM) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXgrs_ranSource VIKINGDR3 The unique ID of the neighbour in TWODFGRS..grs_ranSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ranSource VIKINGDR4 The unique ID of the neighbour in TWODFGRS..grs_ranSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ranSource VIKINGv20110714 The unique ID of the neighbour in TWODFGRS..grs_ranSource (=SEQNUM) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXgrs_ranSource VIKINGv20111019 The unique ID of the neighbour in TWODFGRS..grs_ranSource (=SEQNUM) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXgrs_ranSource VIKINGv20130417 The unique ID of the neighbour in TWODFGRS..grs_ranSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ranSource VIKINGv20140402 The unique ID of the neighbour in TWODFGRS..grs_ranSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ranSource VIKINGv20150421 The unique ID of the neighbour in TWODFGRS..grs_ranSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ranSource VIKINGv20151230 The unique ID of the neighbour in TWODFGRS..grs_ranSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ranSource VIKINGv20160406 The unique ID of the neighbour in TWODFGRS..grs_ranSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ranSource VIKINGv20161202 The unique ID of the neighbour in TWODFGRS..grs_ranSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_ranSource VIKINGv20170715 The unique ID of the neighbour in TWODFGRS..grs_ranSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_sgpSource VIKINGDR2 The unique ID of the neighbour in TWODFGRS..grs_sgpSource (=SEQNUM) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXgrs_sgpSource VIKINGDR3 The unique ID of the neighbour in TWODFGRS..grs_sgpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_sgpSource VIKINGDR4 The unique ID of the neighbour in TWODFGRS..grs_sgpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_sgpSource VIKINGv20110714 The unique ID of the neighbour in TWODFGRS..grs_sgpSource (=SEQNUM) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXgrs_sgpSource VIKINGv20111019 The unique ID of the neighbour in TWODFGRS..grs_sgpSource (=SEQNUM) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXgrs_sgpSource VIKINGv20130417 The unique ID of the neighbour in TWODFGRS..grs_sgpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_sgpSource VIKINGv20140402 The unique ID of the neighbour in TWODFGRS..grs_sgpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_sgpSource VIKINGv20150421 The unique ID of the neighbour in TWODFGRS..grs_sgpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_sgpSource VIKINGv20151230 The unique ID of the neighbour in TWODFGRS..grs_sgpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_sgpSource VIKINGv20160406 The unique ID of the neighbour in TWODFGRS..grs_sgpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_sgpSource VIKINGv20161202 The unique ID of the neighbour in TWODFGRS..grs_sgpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXgrs_sgpSource VIKINGv20170715 The unique ID of the neighbour in TWODFGRS..grs_sgpSource (=SEQNUM) bigint 8     meta.dataset
slaveObjID vikingSourceXmgcDetection VIKINGDR2 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXmgcDetection VIKINGDR3 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vikingSourceXmgcDetection VIKINGDR4 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vikingSourceXmgcDetection VIKINGv20110714 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXmgcDetection VIKINGv20111019 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXmgcDetection VIKINGv20130417 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vikingSourceXmgcDetection VIKINGv20140402 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vikingSourceXmgcDetection VIKINGv20150421 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vikingSourceXmgcDetection VIKINGv20151230 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vikingSourceXmgcDetection VIKINGv20160406 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vikingSourceXmgcDetection VIKINGv20161202 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vikingSourceXmgcDetection VIKINGv20170715 The unique ID of the neighbour in MGC..mgcDetection (=MGCID) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_psc VIKINGDR2 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXtwomass_psc VIKINGDR3 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_psc VIKINGDR4 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_psc VIKINGv20110714 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXtwomass_psc VIKINGv20111019 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXtwomass_psc VIKINGv20130417 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_psc VIKINGv20140402 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_psc VIKINGv20150421 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_psc VIKINGv20151230 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_psc VIKINGv20160406 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_psc VIKINGv20161202 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_psc VIKINGv20170715 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_xsc VIKINGDR2 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXtwomass_xsc VIKINGDR3 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_xsc VIKINGDR4 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_xsc VIKINGv20110714 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXtwomass_xsc VIKINGv20111019 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXtwomass_xsc VIKINGv20130417 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_xsc VIKINGv20140402 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_xsc VIKINGv20150421 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_xsc VIKINGv20151230 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_xsc VIKINGv20160406 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_xsc VIKINGv20161202 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwomass_xsc VIKINGv20170715 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vikingSourceXtwompzPhotoz VIKINGv20161202 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vikingSourceXtwompzPhotoz VIKINGv20170715 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vikingSourceXwiseScosPhotoz VIKINGv20161202 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vikingSourceXwiseScosPhotoz VIKINGv20170715 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vikingSourceXwise_allskysc VIKINGDR3 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXwise_allskysc VIKINGDR4 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXwise_allskysc VIKINGv20130417 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXwise_allskysc VIKINGv20140402 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXwise_allskysc VIKINGv20150421 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXwise_allskysc VIKINGv20151230 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXwise_allskysc VIKINGv20160406 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXwise_allskysc VIKINGv20161202 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXwise_allskysc VIKINGv20170715 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vikingSourceXwise_prelimsc VIKINGDR2 The unique ID of the neighbour in WISE..wise_prelimsc (=cntr) bigint 8     meta.id;meta.dataset
slaveObjID vikingSourceXwise_prelimsc VIKINGv20111019 The unique ID of the neighbour in WISE..wise_prelimsc (=cntr) bigint 8     meta.id;meta.dataset
slaveObjID vmcProperMotionCatalogueXGDR1gaia_source, vmcPsfSourceXGDR1gaia_source, vmcSourceXGDR1gaia_source VMCv20240226 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXGDR1tgas_source, vmcPsfSourceXGDR1tgas_source, vmcSourceXGDR1tgas_source VMCv20240226 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXGDR2gaia_source, vmcPsfSourceXGDR2gaia_source, vmcSourceXGDR2gaia_source VMCv20240226 The unique ID of the neighbour in GAIADR2..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXGEDR3gaia_source, vmcPsfSourceXGEDR3gaia_source, vmcSourceXGEDR3gaia_source VMCv20240226 The unique ID of the neighbour in GAIAEDR3..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXSKYMAP_masterDR2, vmcPsfSourceXSKYMAP_masterDR2, vmcSourceXSKYMAP_masterDR2 VMCv20240226 The unique ID of the neighbour in SKYMAPPER..masterDR2 (=object_id) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXSSASource, vmcPsfSourceXSSASource, vmcSourceXSSASource VMCv20240226 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXakari_lmc_psa_v1, vmcPsfSourceXakari_lmc_psa_v1, vmcSourceXakari_lmc_psa_v1 VMCv20240226 The unique ID of the neighbour in AKARI..akari_lmc_psa_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXakari_lmc_psc_v1, vmcPsfSourceXakari_lmc_psc_v1, vmcSourceXakari_lmc_psc_v1 VMCv20240226 The unique ID of the neighbour in AKARI..akari_lmc_psc_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXallwise_sc, vmcPsfSourceXallwise_sc, vmcSourceXallwise_sc VMCv20240226 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXcatwise_2020, vmcPsfSourceXcatwise_2020, vmcSourceXcatwise_2020 VMCv20240226 The unique ID of the neighbour in WISE..catwise_2020 (=cntr) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXdenisDR3Source, vmcPsfSourceXdenisDR3Source, vmcSourceXdenisDR3Source VMCv20240226 The unique ID of the neighbour in DENIS..denisDR3Source (=seqNum) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXeros2LMCSource, vmcPsfSourceXeros2LMCSource, vmcSourceXeros2LMCSource VMCv20240226 The unique ID of the neighbour in EROS..eros2LMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXeros2SMCSource, vmcPsfSourceXeros2SMCSource, vmcSourceXeros2SMCSource VMCv20240226 The unique ID of the neighbour in EROS..eros2SMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXerosLMCSource, vmcPsfSourceXerosLMCSource, vmcSourceXerosLMCSource VMCv20240226 The unique ID of the neighbour in EROS..erosLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXerosSMCSource, vmcPsfSourceXerosSMCSource, vmcSourceXerosSMCSource VMCv20240226 The unique ID of the neighbour in EROS..erosSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXmachoLMCSource, vmcPsfSourceXmachoLMCSource, vmcSourceXmachoLMCSource VMCv20240226 The unique ID of the neighbour in MACHO..machoLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXmachoSMCSource, vmcPsfSourceXmachoSMCSource, vmcSourceXmachoSMCSource VMCv20240226 The unique ID of the neighbour in MACHO..machoSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXmcps_lmcSource, vmcPsfSourceXmcps_lmcSource, vmcSourceXmcps_lmcSource VMCv20240226 The unique ID of the neighbour in MCPS..mcps_lmcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXmcps_smcSource, vmcPsfSourceXmcps_smcSource, vmcSourceXmcps_smcSource VMCv20240226 The unique ID of the neighbour in MCPS..mcps_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXogle3LpvLmcSource, vmcPsfSourceXogle3LpvLmcSource, vmcSourceXogle3LpvLmcSource VMCv20240226 The unique ID of the neighbour in OGLE..ogle3LpvLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXogle3LpvSmcSource, vmcPsfSourceXogle3LpvSmcSource, vmcSourceXogle3LpvSmcSource VMCv20240226 The unique ID of the neighbour in OGLE..ogle3LpvSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXogle4CepLmcSource, vmcPsfSourceXogle4CepLmcSource, vmcSourceXogle4CepLmcSource VMCv20240226 The unique ID of the neighbour in OGLE..ogle4CepLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXogle4CepSmcSource, vmcPsfSourceXogle4CepSmcSource, vmcSourceXogle4CepSmcSource VMCv20240226 The unique ID of the neighbour in OGLE..ogle4CepSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXogle4RRLyrLmcSource, vmcPsfSourceXogle4RRLyrLmcSource, vmcSourceXogle4RRLyrLmcSource VMCv20240226 The unique ID of the neighbour in OGLE..ogle4RRLyrLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXogle4RRLyrSmcSource, vmcPsfSourceXogle4RRLyrSmcSource, vmcSourceXogle4RRLyrSmcSource VMCv20240226 The unique ID of the neighbour in OGLE..ogle4RRLyrSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXravedr5Source, vmcPsfSourceXravedr5Source, vmcSourceXravedr5Source VMCv20240226 The unique ID of the neighbour in RAVE..ravedr5Source (=SourceID) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXsage_lmcIracSource, vmcPsfSourceXsage_lmcIracSource, vmcSourceXsage_lmcIracSource VMCv20240226 The unique ID of the neighbour in SPITZER..sage_lmcIracSource (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXsage_lmcMips160Source, vmcPsfSourceXsage_lmcMips160Source, vmcSourceXsage_lmcMips160Source VMCv20240226 The unique ID of the neighbour in SPITZER..sage_lmcMips160Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXsage_lmcMips24Source, vmcPsfSourceXsage_lmcMips24Source, vmcSourceXsage_lmcMips24Source VMCv20240226 The unique ID of the neighbour in SPITZER..sage_lmcMips24Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXsage_lmcMips70Source, vmcPsfSourceXsage_lmcMips70Source, vmcSourceXsage_lmcMips70Source VMCv20240226 The unique ID of the neighbour in SPITZER..sage_lmcMips70Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXspitzer_smcSource, vmcPsfSourceXspitzer_smcSource, vmcSourceXspitzer_smcSource VMCv20240226 The unique ID of the neighbour in SPITZER..spitzer_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXtwomass_psc, vmcPsfSourceXtwomass_psc, vmcSourceXtwomass_psc VMCv20240226 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXtwomass_sixx2_psc, vmcPsfSourceXtwomass_sixx2_psc, vmcSourceXtwomass_sixx2_psc VMCv20240226 The unique ID of the neighbour in TWOMASS..twomass_sixx2_psc (=seqNum) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXtwomass_sixx2_xsc, vmcPsfSourceXtwomass_sixx2_xsc, vmcSourceXtwomass_sixx2_xsc VMCv20240226 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXtwomass_xsc, vmcPsfSourceXtwomass_xsc, vmcSourceXtwomass_xsc VMCv20240226 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXtwompzPhotoz, vmcPsfSourceXtwompzPhotoz, vmcSourceXtwompzPhotoz VMCv20240226 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXwiseScosPhotoz, vmcPsfSourceXwiseScosPhotoz, vmcSourceXwiseScosPhotoz VMCv20240226 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vmcProperMotionCatalogueXwise_allskysc, vmcPsfSourceXwise_allskysc, vmcSourceXwise_allskysc VMCv20240226 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXGDR1gaia_source VMCv20170411 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXGDR1gaia_source VMCv20171101 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXGDR1tgas_source VMCv20170411 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXGDR1tgas_source VMCv20171101 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXSSASource VMCDR4 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXSSASource VMCv20160822 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXSSASource VMCv20170109 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXSSASource VMCv20170411 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXSSASource VMCv20171101 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXakari_lmc_psa_v1 VMCDR4 The unique ID of the neighbour in AKARI..akari_lmc_psa_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXakari_lmc_psa_v1 VMCv20160822 The unique ID of the neighbour in AKARI..akari_lmc_psa_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXakari_lmc_psa_v1 VMCv20170109 The unique ID of the neighbour in AKARI..akari_lmc_psa_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXakari_lmc_psa_v1 VMCv20170411 The unique ID of the neighbour in AKARI..akari_lmc_psa_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXakari_lmc_psa_v1 VMCv20171101 The unique ID of the neighbour in AKARI..akari_lmc_psa_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXakari_lmc_psc_v1 VMCDR4 The unique ID of the neighbour in AKARI..akari_lmc_psc_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXakari_lmc_psc_v1 VMCv20160822 The unique ID of the neighbour in AKARI..akari_lmc_psc_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXakari_lmc_psc_v1 VMCv20170109 The unique ID of the neighbour in AKARI..akari_lmc_psc_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXakari_lmc_psc_v1 VMCv20170411 The unique ID of the neighbour in AKARI..akari_lmc_psc_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXakari_lmc_psc_v1 VMCv20171101 The unique ID of the neighbour in AKARI..akari_lmc_psc_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXallwise_sc VMCDR4 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXallwise_sc VMCv20160822 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXallwise_sc VMCv20170109 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXallwise_sc VMCv20170411 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXallwise_sc VMCv20171101 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXdenisDR3Source VMCDR4 The unique ID of the neighbour in DENIS..denisDR3Source (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXdenisDR3Source VMCv20160822 The unique ID of the neighbour in DENIS..denisDR3Source (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXdenisDR3Source VMCv20170109 The unique ID of the neighbour in DENIS..denisDR3Source (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXdenisDR3Source VMCv20170411 The unique ID of the neighbour in DENIS..denisDR3Source (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXdenisDR3Source VMCv20171101 The unique ID of the neighbour in DENIS..denisDR3Source (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXeros2LMCSource VMCDR4 The unique ID of the neighbour in EROS..eros2LMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXeros2LMCSource VMCv20160822 The unique ID of the neighbour in EROS..eros2LMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXeros2LMCSource VMCv20170109 The unique ID of the neighbour in EROS..eros2LMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXeros2LMCSource VMCv20170411 The unique ID of the neighbour in EROS..eros2LMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXeros2LMCSource VMCv20171101 The unique ID of the neighbour in EROS..eros2LMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXeros2SMCSource VMCDR4 The unique ID of the neighbour in EROS..eros2SMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXeros2SMCSource VMCv20160822 The unique ID of the neighbour in EROS..eros2SMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXeros2SMCSource VMCv20170109 The unique ID of the neighbour in EROS..eros2SMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXeros2SMCSource VMCv20170411 The unique ID of the neighbour in EROS..eros2SMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXeros2SMCSource VMCv20171101 The unique ID of the neighbour in EROS..eros2SMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXerosLMCSource VMCDR4 The unique ID of the neighbour in EROS..erosLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXerosLMCSource VMCv20160822 The unique ID of the neighbour in EROS..erosLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXerosLMCSource VMCv20170109 The unique ID of the neighbour in EROS..erosLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXerosLMCSource VMCv20170411 The unique ID of the neighbour in EROS..erosLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXerosLMCSource VMCv20171101 The unique ID of the neighbour in EROS..erosLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXerosSMCSource VMCDR4 The unique ID of the neighbour in EROS..erosSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXerosSMCSource VMCv20160822 The unique ID of the neighbour in EROS..erosSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXerosSMCSource VMCv20170109 The unique ID of the neighbour in EROS..erosSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXerosSMCSource VMCv20170411 The unique ID of the neighbour in EROS..erosSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXerosSMCSource VMCv20171101 The unique ID of the neighbour in EROS..erosSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmachoLMCSource VMCDR4 The unique ID of the neighbour in MACHO..machoLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmachoLMCSource VMCv20160822 The unique ID of the neighbour in MACHO..machoLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmachoLMCSource VMCv20170109 The unique ID of the neighbour in MACHO..machoLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmachoLMCSource VMCv20170411 The unique ID of the neighbour in MACHO..machoLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmachoLMCSource VMCv20171101 The unique ID of the neighbour in MACHO..machoLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmachoSMCSource VMCDR4 The unique ID of the neighbour in MACHO..machoSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmachoSMCSource VMCv20160822 The unique ID of the neighbour in MACHO..machoSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmachoSMCSource VMCv20170109 The unique ID of the neighbour in MACHO..machoSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmachoSMCSource VMCv20170411 The unique ID of the neighbour in MACHO..machoSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmachoSMCSource VMCv20171101 The unique ID of the neighbour in MACHO..machoSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmcps_lmcSource VMCDR4 The unique ID of the neighbour in MCPS..mcps_lmcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmcps_lmcSource VMCv20160822 The unique ID of the neighbour in MCPS..mcps_lmcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmcps_lmcSource VMCv20170109 The unique ID of the neighbour in MCPS..mcps_lmcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmcps_lmcSource VMCv20170411 The unique ID of the neighbour in MCPS..mcps_lmcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmcps_lmcSource VMCv20171101 The unique ID of the neighbour in MCPS..mcps_lmcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmcps_smcSource VMCDR4 The unique ID of the neighbour in MCPS..mcps_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmcps_smcSource VMCv20160822 The unique ID of the neighbour in MCPS..mcps_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmcps_smcSource VMCv20170109 The unique ID of the neighbour in MCPS..mcps_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmcps_smcSource VMCv20170411 The unique ID of the neighbour in MCPS..mcps_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXmcps_smcSource VMCv20171101 The unique ID of the neighbour in MCPS..mcps_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle3LpvLmcSource VMCv20160822 The unique ID of the neighbour in OGLE..ogle3LpvLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle3LpvLmcSource VMCv20170109 The unique ID of the neighbour in OGLE..ogle3LpvLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle3LpvLmcSource VMCv20170411 The unique ID of the neighbour in OGLE..ogle3LpvLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle3LpvLmcSource VMCv20171101 The unique ID of the neighbour in OGLE..ogle3LpvLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle3LpvSmcSource VMCv20160822 The unique ID of the neighbour in OGLE..ogle3LpvSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle3LpvSmcSource VMCv20170109 The unique ID of the neighbour in OGLE..ogle3LpvSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle3LpvSmcSource VMCv20170411 The unique ID of the neighbour in OGLE..ogle3LpvSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle3LpvSmcSource VMCv20171101 The unique ID of the neighbour in OGLE..ogle3LpvSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4CepLmcSource VMCv20160822 The unique ID of the neighbour in OGLE..ogle4CepLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4CepLmcSource VMCv20170109 The unique ID of the neighbour in OGLE..ogle4CepLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4CepLmcSource VMCv20170411 The unique ID of the neighbour in OGLE..ogle4CepLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4CepLmcSource VMCv20171101 The unique ID of the neighbour in OGLE..ogle4CepLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4CepSmcSource VMCv20160822 The unique ID of the neighbour in OGLE..ogle4CepSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4CepSmcSource VMCv20170109 The unique ID of the neighbour in OGLE..ogle4CepSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4CepSmcSource VMCv20170411 The unique ID of the neighbour in OGLE..ogle4CepSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4CepSmcSource VMCv20171101 The unique ID of the neighbour in OGLE..ogle4CepSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4RRLyrLmcSource VMCv20160822 The unique ID of the neighbour in OGLE..ogle4RRLyrLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4RRLyrLmcSource VMCv20170109 The unique ID of the neighbour in OGLE..ogle4RRLyrLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4RRLyrLmcSource VMCv20170411 The unique ID of the neighbour in OGLE..ogle4RRLyrLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4RRLyrLmcSource VMCv20171101 The unique ID of the neighbour in OGLE..ogle4RRLyrLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4RRLyrSmcSource VMCv20160822 The unique ID of the neighbour in OGLE..ogle4RRLyrSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4RRLyrSmcSource VMCv20170109 The unique ID of the neighbour in OGLE..ogle4RRLyrSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4RRLyrSmcSource VMCv20170411 The unique ID of the neighbour in OGLE..ogle4RRLyrSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXogle4RRLyrSmcSource VMCv20171101 The unique ID of the neighbour in OGLE..ogle4RRLyrSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcIracSource VMCDR4 The unique ID of the neighbour in SPITZER..sage_lmcIracSource (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcIracSource VMCv20160822 The unique ID of the neighbour in SPITZER..sage_lmcIracSource (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcIracSource VMCv20170109 The unique ID of the neighbour in SPITZER..sage_lmcIracSource (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcIracSource VMCv20170411 The unique ID of the neighbour in SPITZER..sage_lmcIracSource (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcIracSource VMCv20171101 The unique ID of the neighbour in SPITZER..sage_lmcIracSource (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips160Source VMCDR4 The unique ID of the neighbour in SPITZER..sage_lmcMips160Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips160Source VMCv20160822 The unique ID of the neighbour in SPITZER..sage_lmcMips160Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips160Source VMCv20170109 The unique ID of the neighbour in SPITZER..sage_lmcMips160Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips160Source VMCv20170411 The unique ID of the neighbour in SPITZER..sage_lmcMips160Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips160Source VMCv20171101 The unique ID of the neighbour in SPITZER..sage_lmcMips160Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips24Source VMCDR4 The unique ID of the neighbour in SPITZER..sage_lmcMips24Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips24Source VMCv20160822 The unique ID of the neighbour in SPITZER..sage_lmcMips24Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips24Source VMCv20170109 The unique ID of the neighbour in SPITZER..sage_lmcMips24Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips24Source VMCv20170411 The unique ID of the neighbour in SPITZER..sage_lmcMips24Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips24Source VMCv20171101 The unique ID of the neighbour in SPITZER..sage_lmcMips24Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips70Source VMCDR4 The unique ID of the neighbour in SPITZER..sage_lmcMips70Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips70Source VMCv20160822 The unique ID of the neighbour in SPITZER..sage_lmcMips70Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips70Source VMCv20170109 The unique ID of the neighbour in SPITZER..sage_lmcMips70Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips70Source VMCv20170411 The unique ID of the neighbour in SPITZER..sage_lmcMips70Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXsage_lmcMips70Source VMCv20171101 The unique ID of the neighbour in SPITZER..sage_lmcMips70Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXspitzer_smcSource VMCDR4 The unique ID of the neighbour in SPITZER..spitzer_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXspitzer_smcSource VMCv20160822 The unique ID of the neighbour in SPITZER..spitzer_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXspitzer_smcSource VMCv20170109 The unique ID of the neighbour in SPITZER..spitzer_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXspitzer_smcSource VMCv20170411 The unique ID of the neighbour in SPITZER..spitzer_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXspitzer_smcSource VMCv20171101 The unique ID of the neighbour in SPITZER..spitzer_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_psc VMCDR4 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_psc VMCv20160822 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_psc VMCv20170109 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_psc VMCv20170411 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_psc VMCv20171101 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_sixx2_psc VMCDR4 The unique ID of the neighbour in TWOMASS..twomass_sixx2_psc (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_sixx2_psc VMCv20160822 The unique ID of the neighbour in TWOMASS..twomass_sixx2_psc (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_sixx2_psc VMCv20170109 The unique ID of the neighbour in TWOMASS..twomass_sixx2_psc (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_sixx2_psc VMCv20170411 The unique ID of the neighbour in TWOMASS..twomass_sixx2_psc (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_sixx2_psc VMCv20171101 The unique ID of the neighbour in TWOMASS..twomass_sixx2_psc (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_sixx2_xsc VMCDR4 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_sixx2_xsc VMCv20160822 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_sixx2_xsc VMCv20170109 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_sixx2_xsc VMCv20170411 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_sixx2_xsc VMCv20171101 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_xsc VMCDR4 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_xsc VMCv20160822 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_xsc VMCv20170109 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_xsc VMCv20170411 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwomass_xsc VMCv20171101 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwompzPhotoz VMCv20160822 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwompzPhotoz VMCv20170109 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwompzPhotoz VMCv20170411 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXtwompzPhotoz VMCv20171101 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXwiseScosPhotoz VMCv20160822 The unique ID of the neighbour in WISExSCOS..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXwiseScosPhotoz VMCv20170109 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXwiseScosPhotoz VMCv20170411 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXwiseScosPhotoz VMCv20171101 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXwise_allskysc VMCDR4 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXwise_allskysc VMCv20160822 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXwise_allskysc VMCv20170109 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXwise_allskysc VMCv20170411 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfCatalogueXwise_allskysc VMCv20171101 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXGDR1gaia_source VMCv20180702 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXGDR1gaia_source VMCv20181120 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXGDR1tgas_source VMCv20180702 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXGDR1tgas_source VMCv20181120 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXGDR2gaia_source VMCv20180702 The unique ID of the neighbour in GAIADR2..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXGDR2gaia_source VMCv20181120 The unique ID of the neighbour in GAIADR2..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXSSASource VMCv20180702 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXSSASource VMCv20181120 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXakari_lmc_psa_v1 VMCv20180702 The unique ID of the neighbour in AKARI..akari_lmc_psa_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXakari_lmc_psa_v1 VMCv20181120 The unique ID of the neighbour in AKARI..akari_lmc_psa_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXakari_lmc_psc_v1 VMCv20180702 The unique ID of the neighbour in AKARI..akari_lmc_psc_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXakari_lmc_psc_v1 VMCv20181120 The unique ID of the neighbour in AKARI..akari_lmc_psc_v1 (=SEQNUM) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXallwise_sc VMCv20180702 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXallwise_sc VMCv20181120 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXdenisDR3Source VMCv20180702 The unique ID of the neighbour in DENIS..denisDR3Source (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXdenisDR3Source VMCv20181120 The unique ID of the neighbour in DENIS..denisDR3Source (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXeros2LMCSource VMCv20180702 The unique ID of the neighbour in EROS..eros2LMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXeros2LMCSource VMCv20181120 The unique ID of the neighbour in EROS..eros2LMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXeros2SMCSource VMCv20180702 The unique ID of the neighbour in EROS..eros2SMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXeros2SMCSource VMCv20181120 The unique ID of the neighbour in EROS..eros2SMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXerosLMCSource VMCv20180702 The unique ID of the neighbour in EROS..erosLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXerosLMCSource VMCv20181120 The unique ID of the neighbour in EROS..erosLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXerosSMCSource VMCv20180702 The unique ID of the neighbour in EROS..erosSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXerosSMCSource VMCv20181120 The unique ID of the neighbour in EROS..erosSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXmachoLMCSource VMCv20180702 The unique ID of the neighbour in MACHO..machoLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXmachoLMCSource VMCv20181120 The unique ID of the neighbour in MACHO..machoLMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXmachoSMCSource VMCv20180702 The unique ID of the neighbour in MACHO..machoSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXmachoSMCSource VMCv20181120 The unique ID of the neighbour in MACHO..machoSMCSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXmcps_lmcSource VMCv20180702 The unique ID of the neighbour in MCPS..mcps_lmcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXmcps_lmcSource VMCv20181120 The unique ID of the neighbour in MCPS..mcps_lmcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXmcps_smcSource VMCv20180702 The unique ID of the neighbour in MCPS..mcps_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXmcps_smcSource VMCv20181120 The unique ID of the neighbour in MCPS..mcps_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXogle3LpvLmcSource VMCv20180702 The unique ID of the neighbour in OGLE..ogle3LpvLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXogle3LpvLmcSource VMCv20181120 The unique ID of the neighbour in OGLE..ogle3LpvLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXogle3LpvSmcSource VMCv20180702 The unique ID of the neighbour in OGLE..ogle3LpvSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXogle3LpvSmcSource VMCv20181120 The unique ID of the neighbour in OGLE..ogle3LpvSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXogle4CepLmcSource VMCv20180702 The unique ID of the neighbour in OGLE..ogle4CepLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXogle4CepLmcSource VMCv20181120 The unique ID of the neighbour in OGLE..ogle4CepLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXogle4CepSmcSource VMCv20180702 The unique ID of the neighbour in OGLE..ogle4CepSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXogle4CepSmcSource VMCv20181120 The unique ID of the neighbour in OGLE..ogle4CepSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXogle4RRLyrLmcSource VMCv20180702 The unique ID of the neighbour in OGLE..ogle4RRLyrLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXogle4RRLyrLmcSource VMCv20181120 The unique ID of the neighbour in OGLE..ogle4RRLyrLmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXogle4RRLyrSmcSource VMCv20180702 The unique ID of the neighbour in OGLE..ogle4RRLyrSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXogle4RRLyrSmcSource VMCv20181120 The unique ID of the neighbour in OGLE..ogle4RRLyrSmcSource (=seqNo) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXravedr5Source VMCv20180702 The unique ID of the neighbour in RAVE..ravedr5Source (=RAVE_OBS_ID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXravedr5Source VMCv20181120 The unique ID of the neighbour in RAVE..ravedr5Source (=SourceID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXsage_lmcIracSource VMCv20180702 The unique ID of the neighbour in SPITZER..sage_lmcIracSource (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXsage_lmcIracSource VMCv20181120 The unique ID of the neighbour in SPITZER..sage_lmcIracSource (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXsage_lmcMips160Source VMCv20180702 The unique ID of the neighbour in SPITZER..sage_lmcMips160Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXsage_lmcMips160Source VMCv20181120 The unique ID of the neighbour in SPITZER..sage_lmcMips160Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXsage_lmcMips24Source VMCv20180702 The unique ID of the neighbour in SPITZER..sage_lmcMips24Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXsage_lmcMips24Source VMCv20181120 The unique ID of the neighbour in SPITZER..sage_lmcMips24Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXsage_lmcMips70Source VMCv20180702 The unique ID of the neighbour in SPITZER..sage_lmcMips70Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXsage_lmcMips70Source VMCv20181120 The unique ID of the neighbour in SPITZER..sage_lmcMips70Source (=globalSourceID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXspitzer_smcSource VMCv20180702 The unique ID of the neighbour in SPITZER..spitzer_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXspitzer_smcSource VMCv20181120 The unique ID of the neighbour in SPITZER..spitzer_smcSource (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXtwomass_psc VMCv20180702 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXtwomass_psc VMCv20181120 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXtwomass_sixx2_psc VMCv20180702 The unique ID of the neighbour in TWOMASS..twomass_sixx2_psc (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXtwomass_sixx2_psc VMCv20181120 The unique ID of the neighbour in TWOMASS..twomass_sixx2_psc (=seqNum) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXtwomass_sixx2_xsc VMCv20180702 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXtwomass_sixx2_xsc VMCv20181120 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXtwomass_xsc VMCv20180702 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXtwomass_xsc VMCv20181120 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXtwompzPhotoz VMCv20180702 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXtwompzPhotoz VMCv20181120 The unique ID of the neighbour in TWOMPZ..twompzPhotoz (=twomassID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXwiseScosPhotoz VMCv20180702 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXwiseScosPhotoz VMCv20181120 The unique ID of the neighbour in WISExSCOSPZ..wiseScosPhotoz (=wiseID) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXwise_allskysc VMCv20180702 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfDetectionsXwise_allskysc VMCv20181120 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfSourceXSMASHDR2_deep, vmcSourceXSMASHDR2_deep VMCv20240226 The unique ID of the neighbour in SMASH..smashdr2_deep (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfSourceXSMASHDR2_object, vmcSourceXSMASHDR2_object VMCv20240226 The unique ID of the neighbour in SMASH..smashdr2_object (=cntr) bigint 8     meta.dataset
slaveObjID vmcPsfSourceXSMASHDR2_source, vmcSourceXSMASHDR2_source VMCv20240226 The unique ID of the neighbour in SMASH..smashdr2_source (=cntr) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCDR1 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vmcSourceNeighbours VMCDR2 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCDR3 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCDR4 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCDR5 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20110816 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vmcSourceNeighbours VMCv20110909 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vmcSourceNeighbours VMCv20120126 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vmcSourceNeighbours VMCv20121128 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20130304 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20130805 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20140428 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20140903 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20150309 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20151218 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20160311 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20160822 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20170109 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20170411 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20171101 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20180702 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20181120 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20191212 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20210708 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20230816 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceNeighbours VMCv20240226 The unique ID of the neighbour in vmcSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcSourceXMLClassificationCatalogue VMCv20240226 The unique ID of the neighbour in vmcMLClassificationCatalogue table (=vmcMlID) bigint 8     meta.dataset
slaveObjID vmcSourceXProperMotionCatalogue VMCv20240226 The unique ID of the neighbour in vmcProperMotionCatalogue table (=pmID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCDR2 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCDR3 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCDR4 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCv20121128 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCv20130304 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCv20130805 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCv20140428 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCv20140903 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCv20150309 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCv20151218 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCv20160311 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCv20160822 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCv20170109 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCv20170411 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfCatalogue VMCv20171101 The unique ID of the neighbour in vmcPsfCatalogue table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfDetections VMCv20180702 The unique ID of the neighbour in vmcPsfDetections table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfDetections VMCv20181120 The unique ID of the neighbour in vmcPsfDetections table (=psfID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfSource VMCDR5 The unique ID of the neighbour in vmcPsfSource table (=psfSourceID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfSource VMCv20180702 The unique ID of the neighbour in vmcPsfSource table (=psfSourceID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfSource VMCv20181120 The unique ID of the neighbour in vmcPsfSource table (=psfSourceID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfSource VMCv20191212 The unique ID of the neighbour in vmcPsfSource table (=psfSourceID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfSource VMCv20210708 The unique ID of the neighbour in vmcPsfSource table (=psfSourceID) bigint 8     meta.dataset
slaveObjID vmcSourceXPsfSource VMCv20240226 The unique ID of the neighbour in vmcPsfSource table (=psfSourceID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCDR1 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.id;meta.dataset
slaveObjID vmcSourceXSynopticSource VMCDR2 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCDR3 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCDR4 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCDR5 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20110816 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.id;meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20110909 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.id;meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20120126 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.id;meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20121128 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20130304 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20130805 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20140428 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20140903 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20150309 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20151218 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20160311 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20160822 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20170109 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20170411 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20171101 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20180702 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20181120 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20191212 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20210708 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20230816 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXSynopticSource VMCv20240226 The unique ID of the neighbour in vmcSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCDR2 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCDR3 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCDR4 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20121128 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20130304 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20130805 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20140428 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20140903 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20150309 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20151218 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20160311 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20160822 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20170109 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20170411 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20171101 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20180702 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20181120 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20191212 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20210708 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20230816 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXVariablesType VMCv20240226 The unique ID of the neighbour in vmcVariablesType table (=varID) bigint 8     meta.dataset
slaveObjID vmcSourceXwise_prelimsc VMCDR1 The unique ID of the neighbour in WISE..wise_prelimsc (=cntr) bigint 8     meta.id;meta.dataset
slaveObjID vmcSourceXwise_prelimsc VMCv20110816 The unique ID of the neighbour in WISE..wise_prelimsc (=cntr) bigint 8     meta.id;meta.dataset
slaveObjID vmcSourceXwise_prelimsc VMCv20110909 The unique ID of the neighbour in WISE..wise_prelimsc (=cntr) bigint 8     meta.id;meta.dataset
slaveObjID vmcSourceXwise_prelimsc VMCv20120126 The unique ID of the neighbour in WISE..wise_prelimsc (=cntr) bigint 8     meta.id;meta.dataset
slaveObjID vmcSourceXxmm3dr4 VMCv20140428 The unique ID of the neighbour in THREEXMM..xmm3dr4 (=DETID) bigint 8     meta.dataset
slaveObjID vmcdeepSourceNeighbours VMCDEEPv20230713 The unique ID of the neighbour in vmcdeepSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcdeepSourceNeighbours VMCDEEPv20240506 The unique ID of the neighbour in vmcdeepSource (=sourceID) bigint 8     meta.dataset
slaveObjID vmcdeepSourceXSSASource VMCDEEPv20230713 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vmcdeepSourceXSSASource VMCDEEPv20240506 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vmcdeepSourceXSynopticSource VMCDEEPv20230713 The unique ID of the neighbour in vmcdeepSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcdeepSourceXSynopticSource VMCDEEPv20240506 The unique ID of the neighbour in vmcdeepSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vmcdeepSourceXallwise_sc VMCDEEPv20230713 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vmcdeepSourceXallwise_sc VMCDEEPv20240506 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vmcdeepSourceXtwomass_psc VMCDEEPv20230713 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vmcdeepSourceXtwomass_psc VMCDEEPv20240506 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vmcdeepSourceXwise_allskysc VMCDEEPv20230713 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vmcdeepSourceXwise_allskysc VMCDEEPv20240506 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXDR11gpsSource, vvvPsfDophotZYJHKsSourceXDR11gpsSource, vvvSourceXDR11gpsSource VVVDR5 The unique ID of the neighbour in UKIDSSDR11PLUS..gpsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXDR8gpsSource, vvvPsfDophotZYJHKsSourceXDR8gpsSource, vvvSourceXDR8gpsSource VVVDR5 The unique ID of the neighbour in UKIDSSDR8PLUS..gpsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXGDR1gaia_source, vvvPsfDophotZYJHKsSourceXGDR1gaia_source, vvvSourceXGDR1gaia_source VVVDR5 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXGDR1tgas_source, vvvPsfDophotZYJHKsSourceXGDR1tgas_source, vvvSourceXGDR1tgas_source VVVDR5 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXGDR2gaia_source, vvvPsfDophotZYJHKsSourceXGDR2gaia_source, vvvSourceXGDR2gaia_source VVVDR5 The unique ID of the neighbour in GAIADR2..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXGEDR3gaia_source, vvvPsfDophotZYJHKsSourceXGEDR3gaia_source, vvvSourceXGEDR3gaia_source VVVDR5 The unique ID of the neighbour in GAIAEDR3..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXPS1DR2_objectThin, vvvPsfDophotZYJHKsSourceXPS1DR2_objectThin, vvvSourceXPS1DR2_objectThin VVVDR5 The unique ID of the neighbour in PS1DR2..objectThin (=objID) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXSSASource, vvvPsfDophotZYJHKsSourceXSSASource, vvvSourceXSSASource VVVDR5 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXallwise_sc, vvvPsfDophotZYJHKsSourceXallwise_sc, vvvSourceXallwise_sc VVVDR5 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXdecapsSource, vvvPsfDophotZYJHKsSourceXdecapsSource, vvvSourceXdecapsSource VVVDR5 The unique ID of the neighbour in DECAPS..decapsSource (=obj_id) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXglimpse1_hrc, vvvPsfDophotZYJHKsSourceXglimpse1_hrc, vvvSourceXglimpse1_hrc VVVDR5 The unique ID of the neighbour in GLIMPSE..glimpse1_hrc (=seqNo) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXglimpse1_mca, vvvPsfDophotZYJHKsSourceXglimpse1_mca, vvvSourceXglimpse1_mca VVVDR5 The unique ID of the neighbour in GLIMPSE..glimpse1_mca (=seqNo) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXglimpse2_hrc, vvvPsfDophotZYJHKsSourceXglimpse2_hrc, vvvSourceXglimpse2_hrc VVVDR5 The unique ID of the neighbour in GLIMPSE..glimpse2_hrc (=seqNo) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXglimpse2_mca, vvvPsfDophotZYJHKsSourceXglimpse2_mca, vvvSourceXglimpse2_mca VVVDR5 The unique ID of the neighbour in GLIMPSE..glimpse2_mca (=seqNo) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXiras_psc, vvvPsfDophotZYJHKsSourceXiras_psc, vvvSourceXiras_psc VVVDR5 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXtwomass_psc, vvvPsfDophotZYJHKsSourceXtwomass_psc, vvvSourceXtwomass_psc VVVDR5 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXtwomass_xsc, vvvPsfDophotZYJHKsSourceXtwomass_xsc, vvvSourceXtwomass_xsc VVVDR5 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXvphasDr3Source, vvvPsfDophotZYJHKsSourceXvphasDr3Source, vvvSourceXvphasDr3Source VVVDR5 The unique ID of the neighbour in VPHASDR3..vphasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXwise_allskysc, vvvPsfDophotZYJHKsSourceXwise_allskysc, vvvSourceXwise_allskysc VVVDR5 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vvvPsfDaophotJKsSourceXxmm3dr4, vvvPsfDophotZYJHKsSourceXxmm3dr4, vvvSourceXxmm3dr4 VVVDR5 The unique ID of the neighbour in THREEXMM..xmm3dr4 (=DETID) bigint 8     meta.dataset
slaveObjID vvvSourceNeighbours VVVDR1 The unique ID of the neighbour in vvvSource (=sourceID) bigint 8     meta.dataset
slaveObjID vvvSourceNeighbours VVVDR2 The unique ID of the neighbour in vvvSource (=sourceID) bigint 8     meta.dataset
slaveObjID vvvSourceNeighbours VVVDR5 The unique ID of the neighbour in vvvSource (=sourceID) bigint 8     meta.dataset
slaveObjID vvvSourceNeighbours VVVv20100531 The unique ID of the neighbour in vvvSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vvvSourceNeighbours VVVv20110718 The unique ID of the neighbour in vvvSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vvvSourceXDR4gpsSource VVVDR1 The unique ID of the neighbour in UKIDSSDR4PLUS..gpsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vvvSourceXDR4gpsSource VVVDR2 The unique ID of the neighbour in UKIDSSDR4PLUS..gpsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vvvSourceXDR4gpsSource VVVv20110718 The unique ID of the neighbour in UKIDSSDR4PLUS..gpsSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vvvSourceXDetection VVVDR1 The unique ID of the neighbour in vvvDetection table (=objID) bigint 8     meta.dataset
slaveObjID vvvSourceXDetection VVVDR2 The unique ID of the neighbour in vvvDetection table (=objID) bigint 8     meta.dataset
slaveObjID vvvSourceXDetection VVVDR5 The unique ID of the neighbour in vvvDetection table (=objID) bigint 8     meta.dataset
slaveObjID vvvSourceXDetection VVVv20100531 The unique ID of the neighbour in vvvDetection table (=objID) bigint 8     meta.id;meta.dataset
slaveObjID vvvSourceXParallaxCatalogue VVVDR5 The unique ID of the neighbour in vvvParallaxCatalogue table (=viracID) bigint 8     meta.dataset
slaveObjID vvvSourceXProperMotionCatalogue VVVDR5 The unique ID of the neighbour in vvvProperMotionCatalogue table (=viracID) bigint 8     meta.dataset
slaveObjID vvvSourceXPsfDaophotJKsSource VVVDR5 The unique ID of the neighbour in vvvPsfDaophotJKsSource table (=psfID) bigint 8     meta.dataset
slaveObjID vvvSourceXPsfDophotZYJHKsSource VVVDR5 The unique ID of the neighbour in vvvPsfDophotZYJHKsSource table (=psfID) bigint 8     meta.dataset
slaveObjID vvvSourceXSynopticSource VVVDR1 The unique ID of the neighbour in vvvSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vvvSourceXSynopticSource VVVDR2 The unique ID of the neighbour in vvvSynopticSource table (=synopticID) bigint 8     meta.dataset
slaveObjID vvvSourceXVivaCatalogue VVVDR5 The unique ID of the neighbour in vvvVivaCatalogue table (=vivaID) bigint 8     meta.dataset
slaveObjID vvvSourceXglimpse_hrc_inter VVVDR1 The unique ID of the neighbour in GLIMPSE..glimpse_hrc_inter (=seqNo) bigint 8     meta.dataset
slaveObjID vvvSourceXglimpse_hrc_inter VVVDR2 The unique ID of the neighbour in GLIMPSE..glimpse_hrc_inter (=seqNo) bigint 8     meta.dataset
slaveObjID vvvSourceXglimpse_hrc_inter VVVv20100531 The unique ID of the neighbour in GLIMPSE..glimpse_hrc_inter (=seqNo) bigint 8     meta.id;meta.dataset
slaveObjID vvvSourceXglimpse_hrc_inter VVVv20110718 The unique ID of the neighbour in GLIMPSE..glimpse_hrc_inter (=seqNo) bigint 8     meta.id;meta.dataset
slaveObjID vvvSourceXglimpse_mca_inter VVVDR1 The unique ID of the neighbour in GLIMPSE..glimpse_mca_inter (=seqNo) bigint 8     meta.dataset
slaveObjID vvvSourceXglimpse_mca_inter VVVDR2 The unique ID of the neighbour in GLIMPSE..glimpse_mca_inter (=seqNo) bigint 8     meta.dataset
slaveObjID vvvSourceXglimpse_mca_inter VVVv20100531 The unique ID of the neighbour in GLIMPSE..glimpse_mca_inter (=seqNo) bigint 8     meta.id;meta.dataset
slaveObjID vvvSourceXglimpse_mca_inter VVVv20110718 The unique ID of the neighbour in GLIMPSE..glimpse_mca_inter (=seqNo) bigint 8     meta.id;meta.dataset
slaveObjID vvvSourceXgpsSource VVVv20100531 The unique ID of the neighbour in UKIDSSDR4PLUS..gpsSource (=sourceID) bigint 8     meta.id;meta.dataset
slaveObjID vvvSourceXtwomass_sixx2_xsc VVVDR1 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vvvSourceXtwomass_sixx2_xsc VVVDR2 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.dataset
slaveObjID vvvSourceXtwomass_sixx2_xsc VVVv20110718 The unique ID of the neighbour in TWOMASS..twomass_sixx2_xsc (=cntr) bigint 8     meta.id;meta.dataset
slaveObjID vvvxSourceNeighbours VVVXDR1 The unique ID of the neighbour in vvvxSource (=sourceID) bigint 8     meta.dataset
slaveObjID vvvxSourceXDR11gpsSource VVVXDR1 The unique ID of the neighbour in UKIDSSDR11PLUS..gpsSource (=sourceID) bigint 8     meta.dataset
slaveObjID vvvxSourceXDetection VVVXDR1 The unique ID of the neighbour in vvvDetection table (=objID) bigint 8     meta.dataset
slaveObjID vvvxSourceXGDR1gaia_source VVVXDR1 The unique ID of the neighbour in GAIADR1..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vvvxSourceXGDR1tgas_source VVVXDR1 The unique ID of the neighbour in GAIADR1..tgas_source (=source_id) bigint 8     meta.dataset
slaveObjID vvvxSourceXGDR2gaia_source VVVXDR1 The unique ID of the neighbour in GAIADR2..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vvvxSourceXGEDR3gaia_source VVVXDR1 The unique ID of the neighbour in GAIAEDR3..gaia_source (=source_id) bigint 8     meta.dataset
slaveObjID vvvxSourceXPS1DR2_objectThin VVVXDR1 The unique ID of the neighbour in PS1DR2..objectThin (=objID) bigint 8     meta.dataset
slaveObjID vvvxSourceXSSASource VVVXDR1 The unique ID of the neighbour in SSA..Source (=objID) bigint 8     meta.dataset
slaveObjID vvvxSourceXVVVDR5vvvProperMotionCatalogue VVVXDR1 The unique ID of the neighbour in VVVDR5..vvvProperMotionCatalogue (=viracID) bigint 8     meta.dataset
slaveObjID vvvxSourceXVVVDR5vvvPsfDaophotJKsSource VVVXDR1 The unique ID of the neighbour in VVVDR5..vvvPsfDaophotJKsSource (=psfID) bigint 8     meta.dataset
slaveObjID vvvxSourceXVVVDR5vvvPsfDophotZYJHKsSource VVVXDR1 The unique ID of the neighbour in VVVDR5..vvvPsfDophotZYJHKsSource (=psfID) bigint 8     meta.dataset
slaveObjID vvvxSourceXVVVDR5vvvSource VVVXDR1 The unique ID of the neighbour in VVVDR5..vvvSource (=sourceID) bigint 8     meta.dataset
slaveObjID vvvxSourceXVVVDR5vvvVivaCatalogue VVVXDR1 The unique ID of the neighbour in VVVDR5..vvvVivaCatalogue (=viracID) bigint 8     meta.dataset
slaveObjID vvvxSourceXallwise_sc VVVXDR1 The unique ID of the neighbour in WISE..allwise_sc (=cntr) bigint 8     meta.dataset
slaveObjID vvvxSourceXcatwise_2020 VVVXDR1 The unique ID of the neighbour in WISE..catwise_2020 (=cntr) bigint 8     meta.dataset
slaveObjID vvvxSourceXdecapsSource VVVXDR1 The unique ID of the neighbour in DECAPS..decapsSource (=obj_id) bigint 8     meta.dataset
slaveObjID vvvxSourceXglimpse1_hrc VVVXDR1 The unique ID of the neighbour in GLIMPSE..glimpse1_hrc (=seqNo) bigint 8     meta.dataset
slaveObjID vvvxSourceXglimpse1_mca VVVXDR1 The unique ID of the neighbour in GLIMPSE..glimpse1_mca (=seqNo) bigint 8     meta.dataset
slaveObjID vvvxSourceXglimpse2_hrc VVVXDR1 The unique ID of the neighbour in GLIMPSE..glimpse2_hrc (=seqNo) bigint 8     meta.dataset
slaveObjID vvvxSourceXglimpse2_mca VVVXDR1 The unique ID of the neighbour in GLIMPSE..glimpse2_mca (=seqNo) bigint 8     meta.dataset
slaveObjID vvvxSourceXiras_psc VVVXDR1 The unique ID of the neighbour in IRAS..iras_psc (=seqNo) bigint 8     meta.dataset
slaveObjID vvvxSourceXtwomass_psc VVVXDR1 The unique ID of the neighbour in TWOMASS..twomass_psc (=pts_key) bigint 8     meta.dataset
slaveObjID vvvxSourceXtwomass_xsc VVVXDR1 The unique ID of the neighbour in TWOMASS..twomass_xsc (=ext_key) bigint 8     meta.dataset
slaveObjID vvvxSourceXvphasDr3Source VVVXDR1 The unique ID of the neighbour in VPHASDR3..vphasSource (=sourceID) bigint 8     meta.dataset
slaveObjID vvvxSourceXwise_allskysc VVVXDR1 The unique ID of the neighbour in WISE..wise_allskysc (=cntr) bigint 8     meta.dataset
slaveObjID vvvxSourceXxmm3dr4 VVVXDR1 The unique ID of the neighbour in THREEXMM..xmm3dr4 (=DETID) bigint 8     meta.dataset
sLevNum Multiframe SHARKSv20210222 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe SHARKSv20210421 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe ULTRAVISTADR4 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSDR1 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSDR2 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSDR3 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSDR4 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSDR5 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSDR6 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSv20120926 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSv20130417 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSv20140409 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSv20150108 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSv20160114 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSv20160507 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSv20170630 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSv20180419 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSv20201209 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSv20231101 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VHSv20240731 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIDEODR2 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIDEODR3 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIDEODR4 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIDEODR5 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIDEOv20100513 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIDEOv20111208 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIKINGDR2 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIKINGDR3 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIKINGDR4 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIKINGv20110714 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIKINGv20111019 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIKINGv20130417 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIKINGv20140402 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIKINGv20150421 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIKINGv20151230 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIKINGv20160406 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIKINGv20161202 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VIKINGv20170715 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCDEEPv20230713 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCDEEPv20240506 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCDR1 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCDR2 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCDR3 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCDR4 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCDR5 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20110816 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20110909 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20120126 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20121128 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20130304 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20130805 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20140428 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20140903 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20150309 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20151218 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20160311 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20160822 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20170109 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20170411 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20171101 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20180702 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20181120 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20191212 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20210708 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20230816 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VMCv20240226 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VVVDR1 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VVVDR2 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VVVDR5 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VVVXDR1 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VVVv20100531 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum Multiframe VVVv20110718 Level 0 sky {image primary HDU keyword: SLEV} tinyint 1   0  
sLevNum sharksMultiframe, ultravistaMultiframe, vhsMultiframe, videoMultiframe, vikingMultiframe, vmcMultiframe, vvvMultiframe VSAQC Level 0 sky tinyint 1   0  
SMAG grs_ngpSource, grs_ranSource, grs_sgpSource TWODFGRS Unmatched raw stellar mag (from APMCAL) real 4      
smoothing MultiframeDetector SHARKSv20210222 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector SHARKSv20210421 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector ULTRAVISTADR4 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSDR1 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSDR2 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSDR3 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSDR4 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSDR5 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSDR6 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSv20120926 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSv20130417 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSv20140409 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSv20150108 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSv20160114 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSv20160507 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSv20170630 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSv20180419 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSv20201209 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSv20231101 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VHSv20240731 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIDEODR2 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIDEODR3 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIDEODR4 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIDEODR5 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIDEOv20100513 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIDEOv20111208 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIKINGDR2 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIKINGDR3 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIKINGDR4 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIKINGv20110714 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIKINGv20111019 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIKINGv20130417 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIKINGv20140402 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIKINGv20150421 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIKINGv20151230 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIKINGv20160406 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIKINGv20161202 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VIKINGv20170715 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCDEEPv20230713 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCDEEPv20240506 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCDR1 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCDR2 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCDR3 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCDR4 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCDR5 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20110816 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20110909 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20120126 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20121128 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20130304 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20130805 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20140428 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20140903 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20150309 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20151218 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20160311 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20160822 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20170109 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20170411 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20171101 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20180702 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20181120 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20191212 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20210708 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20230816 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VMCv20240226 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VVVDR1 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VVVDR2 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VVVDR5 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VVVXDR1 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VVVv20100531 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing MultiframeDetector VVVv20110718 FWHM of the smoothing kernel {catalogue extension keyword:  FILTFWHM} real 4 pixels -0.9999995e9  
smoothing sharksMultiframeDetector, ultravistaMultiframeDetector, vhsMultiframeDetector, videoMultiframeDetector, vikingMultiframeDetector, vmcMultiframeDetector, vvvMultiframeDetector VSAQC FWHM of the smoothing kernel real 4 pixels -0.9999995e9  
smss_j masterDR2 SKYMAPPER SkyMapper Southern Survey designation of the form SMSS Jhhmmss.ss+/-ddmmss.s, derived from mean ICRS coordinates varchar 18     meta.id;meta.main
sn hipparcos_new_reduction GAIADR1 Solution type in the New Reduction int 4     meta.id;stat.fit
SN1 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Signal/Noise for band 1 flux real 4   -9.99  
SN160 sage_lmcMips160Source SPITZER Signal/Noise for band 160 real 4      
SN2 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Signal/Noise for band 2 flux real 4   -9.99  
SN24 sage_lmcMips24Source SPITZER Signal/Noise for band 24 real 4      
SN3 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Signal/Noise for band 3 flux real 4   -9.99  
SN3_6 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE 3.6um IRAC (Band 1) Signal/Noise real 4   -9.99  
SN3_6 sage_lmcIracSource SPITZER Signal/Noise for band 3.6 real 4      
SN3_6 sage_smcIRACv1_5Source SPITZER 3.6um IRAC (Band 1) Signal/Noise real 4      
SN4 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Signal/Noise for band 4 flux real 4   -9.99  
SN4_5 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE 4.5um IRAC (Band 2) Signal/Noise real 4   -9.99  
SN4_5 sage_lmcIracSource SPITZER Signal/Noise for band 4.5 real 4      
SN4_5 sage_smcIRACv1_5Source SPITZER 4.5um IRAC (Band 2) Signal/Noise real 4      
SN5_8 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE 5.8um IRAC (Band 3) Signal/Noise real 4   -9.99  
SN5_8 sage_lmcIracSource SPITZER Signal/Noise for band 5.8 real 4      
SN5_8 sage_smcIRACv1_5Source SPITZER 5.8um IRAC (Band 3) Signal/Noise real 4      
SN70 sage_lmcMips70Source SPITZER Signal/Noise for band 70 real 4      
SN8_0 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE 8.0um IRAC (Band 4) Signal/Noise real 4   -9.99  
SN8_0 sage_lmcIracSource SPITZER Signal/Noise for band 8.0 real 4      
SN8_0 sage_smcIRACv1_5Source SPITZER 8.0um IRAC (Band 4) Signal/Noise real 4      
SNH glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE 2MASS All-Sky PSC H Band Signal/Noise real 4   -9.99  
SNH sage_lmcIracSource SPITZER Signal/Noise for band H real 4      
SNH sage_smcIRACv1_5Source SPITZER 2MASS All-Sky PSC H Band Signal/Noise real 4      
SNJ glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE 2MASS All-Sky PSC J Band Signal/Noise real 4   -9.99  
SNJ sage_lmcIracSource SPITZER Signal/Noise for band J real 4      
SNJ sage_smcIRACv1_5Source SPITZER 2MASS All-Sky PSC J Band Signal/Noise real 4      
SNK sage_lmcIracSource SPITZER Signal/Noise for band K real 4      
SNK sage_smcIRACv1_5Source SPITZER 2MASS All-Sky PSC Ks Band Signal/Noise real 4      
SNKs glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE 2MASS All-Sky PSC Ks Band Signal/Noise real 4   -9.99  
SNR_K ravedr5Source RAVE (R+) Signal/Noise Ratio of Kordopatis Pipeline float 8     stat.snr
SNRfit vvvVivaCatalogue VVVDR5 The signal-to-noise value related with the best period estimation {catalogue TType keyword: SNRphase} float 8 ?? -9.999995e8  
so hipparcos_new_reduction GAIADR1 Solution type in the old reduction int 4     meta.id;stat.fit
softenParam MapFilterLupt SHARKSv20210222 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt SHARKSv20210421 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt ULTRAVISTADR4 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt VHSv20201209 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt VHSv20231101 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt VHSv20240731 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt VMCDEEPv20230713 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt VMCDEEPv20240506 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt VMCDR5 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt VMCv20191212 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt VMCv20210708 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt VMCv20230816 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt VMCv20240226 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt VVVDR5 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
softenParam MapFilterLupt VVVXDR1 the softening parameter used in the calculation of Luptitudes real 4   -9.999995e8  
solution_id aux_qso_icrf2_match, cepheid, ext_phot_zero_point, gaia_hip_tycho2_match, gaia_source, igsl_source, igsl_source_catalog_ids, phot_variable_time_series_g_fov, phot_variable_time_series_g_fov_statistical_parameters, rrlyrae, tgas_source, variable_summary GAIADR1 Solution identifier bigint 8     meta.id;meta.version
solution_id gaia_source GAIADR2 Solution identifier bigint 8     meta.id;meta.version
solution_id gaia_source GAIAEDR3 Solution identifier bigint 8     meta.id;meta.version
source_classification igsl_source GAIADR1 Source of the classification tinyint 1     meta.code
source_id allwise_sc WISE Unique source ID, formed from a combination of the Atlas Tile ID, coadd_id, and sequential extracted source number, src, within the Tile. varchar 28      
The source_id string has the form RRRRsDDD_[trev]-IIIIII where:
  • RRRRsDDD_[trev] = the coadd_id
  • IIIIII = six-digit, zero-filled, sequential extracted source number,src, within the Tile.

For example, the first source extracted in AllWISE Tile 3041m137_ac51 has a source_id of 3041m137_ac51-000001.

NOTE: AllWISE Catalog and Reject Table entries are cross-referenced with the Multiepoch Photometry (MEP) Database via the source_id identifier. The Catalog/Reject Table cntr value is referred to as source_id in the MEP Database.

source_id aux_qso_icrf2_match, cepheid, gaia_hip_tycho2_match, gaia_source, igsl_source, phot_variable_time_series_g_fov, phot_variable_time_series_g_fov_statistical_parameters, rrlyrae, tgas_source, variable_summary GAIADR1 Unique source identifier bigint 8     meta.id;meta.main
source_id catwise_2020, catwise_prelim WISE tile name + processing code + wphot index varchar 25      
source_id gaia_source GAIADR2 Unique source identifier (unique within a particular Data Release) bigint 8     meta.id
source_id gaia_source GAIAEDR3 Unique source identifier (unique within a particular Data Release) bigint 8     meta.id
source_id igsl_source_catalog_ids GAIADR1 Unique source identifier from IGSL2 bigint 8     meta.id;meta.main
source_id wise_allskysc WISE Unique source ID, formed from a combination of the Atlas Tile ID, coadd_id, and sequential extracted source number, src, within the Tile. char 28      
source_id wise_prelimsc WISE Unique source ID, formed from a combination of the Atlas Tile ID, coadd_id, and sequential extracted source number, src, within the Tile char 28      
source_mag_bj igsl_source GAIADR1 Source of the B magnitude tinyint 1     meta.code
source_mag_g igsl_source GAIADR1 Source of the G magnitude tinyint 1     meta.code
source_mag_grvs igsl_source GAIADR1 Source of the RVS G magnitude tinyint 1     meta.code
source_mag_rf igsl_source GAIADR1 Source of the R magnitude tinyint 1     meta.code
source_mu igsl_source GAIADR1 Source of the proper motions tinyint 1     meta.code
source_name catwise_2020, catwise_prelim WISE source hexagesimal designation varchar 21      
source_position igsl_source GAIADR1 Source of the position estimate tinyint 1     meta.code
SOURCE_R spectra SIXDF R source plate varchar 10      
SOURCE_V spectra SIXDF V source plate varchar 10      
sourceCatalog sage_lmcIracSource, sage_lmcMips160Source, sage_lmcMips24Source, sage_lmcMips70Source SPITZER Character string identifier for source catalogue varchar 8      
sourceCatalog sage_smcIRACv1_5Source SPITZER Character string identifier for source catalog varchar 8      
SourceID ravedr5Source RAVE Unique Identifier for RAVE objects, auto-incrementing integer int 4     meta.id
sourceID iras_asc IRAS Source ID varchar 15     meta.id
sourceID sharksSource SHARKSv20210421 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID sharksSource, sharksSourceXDetectionBestMatch, sharksVariability SHARKSv20210222 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID ultravistaSource, ultravistaSourceXDetectionBestMatch, ultravistaVariability ULTRAVISTADR4 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsListRemeasurement, vhsSource VHSDR1 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSDR2 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSDR3 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSDR4 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSDR5 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSDR6 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSv20120926 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSv20130417 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSv20140409 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSv20150108 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSv20160114 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSv20160507 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSv20170630 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSv20180419 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSv20201209 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSv20231101 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSource VHSv20240731 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vhsSourceRemeasurement VHSDR1 UID (unique over entire VSA via programme ID prefix) of this list remeasurement bigint 8     meta.id;meta.main
sourceID videoListRemeasurement, videoSource, videoSourceXDetectionBestMatch, videoVariability VIDEOv20100513 UID (unique over entire WSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID videoSourceRemeasurement VIDEOv20100513 UID (unique over entire WSA via programme ID prefix) of this list remeasurement bigint 8     meta.id;meta.main
sourceID vikingListRemeasurement VIKINGv20111019 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vikingListRemeasurement, vikingSource, vikingSourceXDetectionBestMatch, vikingVariability VIKINGv20110714 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vikingSourceRemeasurement VIKINGv20110714 UID (unique over entire VSA via programme ID prefix) of this list remeasurement bigint 8     meta.id;meta.main
sourceID vikingSourceRemeasurement VIKINGv20111019 UID (unique over entire VSA via programme ID prefix) of this list remeasurement bigint 8     meta.id;meta.main
sourceID vmcListRemeasurement VMCv20110909 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vmcListRemeasurement, vmcSource, vmcSourceXSynopticSourceBestMatch, vmcVariability VMCv20110816 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vmcSourceRemeasurement VMCv20110816 UID (unique over entire VSA via programme ID prefix) of this list remeasurement bigint 8     meta.id;meta.main
sourceID vmcSourceRemeasurement VMCv20110909 UID (unique over entire VSA via programme ID prefix) of this list remeasurement bigint 8     meta.id;meta.main
sourceID vmcdeepSource VMCDEEPv20240506 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vmcdeepSource, vmcdeepSourceXSynopticSourceBestMatch, vmcdeepVariability VMCDEEPv20230713 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vvvListRemeasurement VVVv20110718 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vvvListRemeasurement, vvvSource, vvvSourceXDetectionBestMatch, vvvVariability VVVv20100531 UID (unique over entire WSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceID vvvSourceRemeasurement VVVv20100531 UID (unique over entire WSA via programme ID prefix) of this list remeasurement bigint 8     meta.id;meta.main
sourceID vvvSourceRemeasurement VVVv20110718 UID (unique over entire VSA via programme ID prefix) of this list remeasurement bigint 8     meta.id;meta.main
sourceID vvvxSource, vvvxSourceExtinction, vvvxSourceXDetectionBestMatch, vvvxVariability VVVXDR1 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
sourceid smashdr2_source SMASH Unique ID for this source, the field name plus a running number varchar 20      
sourceIDName ExternalSurveyTable SHARKSv20210222 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable SHARKSv20210421 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable ULTRAVISTADR4 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSDR1 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSDR2 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSDR3 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSDR4 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSDR5 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSDR6 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSv20120926 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSv20130417 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSv20150108 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSv20160114 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSv20160507 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSv20170630 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSv20180419 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSv20201209 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSv20231101 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VHSv20240731 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIDEODR2 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIDEODR3 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIDEODR4 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIDEODR5 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIDEOv20100513 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIDEOv20111208 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIKINGDR2 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIKINGDR3 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIKINGDR4 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIKINGv20110714 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIKINGv20111019 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIKINGv20130417 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIKINGv20150421 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIKINGv20151230 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIKINGv20160406 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIKINGv20161202 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VIKINGv20170715 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCDEEPv20230713 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCDEEPv20240506 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCDR1 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCDR3 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCDR4 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCDR5 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20110816 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20110909 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20120126 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20121128 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20130304 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20130805 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20140428 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20140903 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20150309 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20151218 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20160311 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20160822 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20170109 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20170411 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20171101 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20180702 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20181120 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20191212 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20210708 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20230816 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VMCv20240226 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VSAQC The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VVVDR1 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VVVDR2 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VVVDR5 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VVVXDR1 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VVVv20100531 The source unique identifier in the table varchar 256     meta.id
sourceIDName ExternalSurveyTable VVVv20110718 The source unique identifier in the table varchar 256     meta.id
sourceIDName ProgrammeTable SHARKSv20210222 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable SHARKSv20210421 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable ULTRAVISTADR4 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSDR1 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSDR2 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSDR3 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSDR4 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSDR5 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSDR6 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSv20120926 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSv20130417 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSv20150108 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSv20160114 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSv20160507 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSv20170630 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSv20180419 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSv20201209 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSv20231101 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VHSv20240731 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIDEODR2 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIDEODR3 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIDEODR4 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIDEODR5 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIDEOv20100513 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIDEOv20111208 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIKINGDR2 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIKINGDR3 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIKINGDR4 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIKINGv20110714 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIKINGv20111019 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIKINGv20130417 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIKINGv20150421 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIKINGv20151230 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIKINGv20160406 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIKINGv20161202 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VIKINGv20170715 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCDEEPv20230713 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCDEEPv20240506 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCDR1 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCDR3 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCDR4 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCDR5 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20110816 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20110909 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20120126 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20121128 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20130304 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20130805 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20140428 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20140903 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20150309 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20151218 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20160311 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20160822 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20170109 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20170411 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20171101 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20180702 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20181120 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20191212 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20210708 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20230816 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VMCv20240226 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VSAQC the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VVVDR1 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VVVDR2 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VVVDR5 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VVVXDR1 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VVVv20100531 the name of the source varchar 256     meta.id
sourceIDName ProgrammeTable VVVv20110718 the name of the source varchar 256     meta.id
sourceMatched ExternalProduct SHARKSv20210222 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct SHARKSv20210421 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct ULTRAVISTADR4 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VHSDR3 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VHSDR4 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VHSDR5 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VHSDR6 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VHSv20150108 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VHSv20160114 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VHSv20160507 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VHSv20170630 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VHSv20180419 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VHSv20201209 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VHSv20231101 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VHSv20240731 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VIDEODR4 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VIDEODR5 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VIKINGDR4 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VIKINGv20150421 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VIKINGv20151230 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VIKINGv20160406 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VIKINGv20161202 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VIKINGv20170715 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCDEEPv20230713 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCDEEPv20240506 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCDR3 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCDR4 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCDR5 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20140428 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20140903 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20150309 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20151218 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20160311 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20160822 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20170109 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20170411 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20171101 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20180702 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20181120 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20191212 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20210708 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20230816 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VMCv20240226 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VVVDR5 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceMatched ExternalProduct VVVXDR1 Does the main ID of the table have an exact 1 - 1 match with the source table tinyint 1   0  
sourceProb first08Jul16Source FIRST probability that the source is spurious (most commonly because it is a sidelobe of of a nearby bright source.) Low values mean the source is unlikely to be spurious. float 8     meta.code
sourceProb firstSource12Feb16 FIRST probability that the source is spurious (most commonly because it is a sidelobe of of a nearby bright source.) Low values mean the source is unlikely to be spurious. real 4     meta.code
sourceProdType Programme SHARKSv20210222 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme SHARKSv20210421 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme ULTRAVISTADR4 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSDR1 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSDR2 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSDR3 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSDR4 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSDR5 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSDR6 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSv20120926 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSv20130417 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSv20150108 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSv20160114 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSv20160507 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSv20170630 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSv20180419 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSv20201209 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSv20231101 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VHSv20240731 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIDEODR2 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIDEODR3 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIDEODR4 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIDEODR5 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIDEOv20100513 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIDEOv20111208 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIKINGDR2 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIKINGDR3 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIKINGDR4 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIKINGv20110714 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIKINGv20111019 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIKINGv20130417 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIKINGv20150421 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIKINGv20151230 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIKINGv20160406 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIKINGv20161202 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VIKINGv20170715 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCDEEPv20230713 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCDEEPv20240506 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCDR1 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCDR3 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCDR4 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCDR5 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20110816 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20110909 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20120126 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20121128 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20130304 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20130805 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20140428 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20140903 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20150309 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20151218 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20160311 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20160822 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20170109 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20170411 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20171101 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20180702 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20181120 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20191212 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20210708 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20230816 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VMCv20240226 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VSAQC The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VVVDR1 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VVVDR2 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VVVDR5 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VVVXDR1 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VVVv20100531 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceProdType Programme VVVv20110718 The product type to be used to create the source table. (stack, tile, mosaic) varchar 16   NONE  
sourceRemeasTable Programme SHARKSv20210222 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme SHARKSv20210421 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme ULTRAVISTADR4 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSDR1 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSDR2 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSDR3 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSDR4 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSDR5 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSDR6 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSv20120926 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSv20130417 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSv20150108 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSv20160114 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSv20160507 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSv20170630 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSv20180419 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSv20201209 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSv20231101 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VHSv20240731 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIDEODR2 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIDEODR3 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIDEODR4 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIDEODR5 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIDEOv20100513 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIDEOv20111208 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIKINGDR2 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIKINGDR3 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIKINGDR4 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIKINGv20110714 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIKINGv20111019 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIKINGv20130417 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIKINGv20150421 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIKINGv20151230 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIKINGv20160406 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIKINGv20161202 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VIKINGv20170715 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCDEEPv20230713 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCDEEPv20240506 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCDR1 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCDR3 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCDR4 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCDR5 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20110816 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20110909 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20120126 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20121128 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20130304 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20130805 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20140428 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20140903 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20150309 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20151218 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20160311 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20160822 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20170109 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20170411 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20171101 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20180702 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20181120 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20191212 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20210708 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20230816 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VMCv20240226 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VSAQC [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VVVDR1 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VVVDR2 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VVVDR5 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VVVXDR1 [OBSOLETE] Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VVVv20100531 Table name of co-located list re-measurements varchar 64     ??
sourceRemeasTable Programme VVVv20110718 Table name of co-located list re-measurements varchar 64     ??
sourceTable Programme SHARKSv20210222 Table name of merged sources varchar 64     ??
sourceTable Programme SHARKSv20210421 Table name of merged sources varchar 64     ??
sourceTable Programme ULTRAVISTADR4 Table name of merged sources varchar 64     ??
sourceTable Programme VHSDR1 Table name of merged sources varchar 64     ??
sourceTable Programme VHSDR2 Table name of merged sources varchar 64     ??
sourceTable Programme VHSDR3 Table name of merged sources varchar 64     ??
sourceTable Programme VHSDR4 Table name of merged sources varchar 64     ??
sourceTable Programme VHSDR5 Table name of merged sources varchar 64     ??
sourceTable Programme VHSDR6 Table name of merged sources varchar 64     ??
sourceTable Programme VHSv20120926 Table name of merged sources varchar 64     ??
sourceTable Programme VHSv20130417 Table name of merged sources varchar 64     ??
sourceTable Programme VHSv20150108 Table name of merged sources varchar 64     ??
sourceTable Programme VHSv20160114 Table name of merged sources varchar 64     ??
sourceTable Programme VHSv20160507 Table name of merged sources varchar 64     ??
sourceTable Programme VHSv20170630 Table name of merged sources varchar 64     ??
sourceTable Programme VHSv20180419 Table name of merged sources varchar 64     ??
sourceTable Programme VHSv20201209 Table name of merged sources varchar 64     ??
sourceTable Programme VHSv20231101 Table name of merged sources varchar 64     ??
sourceTable Programme VHSv20240731 Table name of merged sources varchar 64     ??
sourceTable Programme VIDEODR2 Table name of merged sources varchar 64     ??
sourceTable Programme VIDEODR3 Table name of merged sources varchar 64     ??
sourceTable Programme VIDEODR4 Table name of merged sources varchar 64     ??
sourceTable Programme VIDEODR5 Table name of merged sources varchar 64     ??
sourceTable Programme VIDEOv20100513 Table name of merged sources varchar 64     ??
sourceTable Programme VIDEOv20111208 Table name of merged sources varchar 64     ??
sourceTable Programme VIKINGDR2 Table name of merged sources varchar 64     ??
sourceTable Programme VIKINGDR3 Table name of merged sources varchar 64     ??
sourceTable Programme VIKINGDR4 Table name of merged sources varchar 64     ??
sourceTable Programme VIKINGv20110714 Table name of merged sources varchar 64     ??
sourceTable Programme VIKINGv20111019 Table name of merged sources varchar 64     ??
sourceTable Programme VIKINGv20130417 Table name of merged sources varchar 64     ??
sourceTable Programme VIKINGv20150421 Table name of merged sources varchar 64     ??
sourceTable Programme VIKINGv20151230 Table name of merged sources varchar 64     ??
sourceTable Programme VIKINGv20160406 Table name of merged sources varchar 64     ??
sourceTable Programme VIKINGv20161202 Table name of merged sources varchar 64     ??
sourceTable Programme VIKINGv20170715 Table name of merged sources varchar 64     ??
sourceTable Programme VMCDEEPv20230713 Table name of merged sources varchar 64     ??
sourceTable Programme VMCDEEPv20240506 Table name of merged sources varchar 64     ??
sourceTable Programme VMCDR1 Table name of merged sources varchar 64     ??
sourceTable Programme VMCDR3 Table name of merged sources varchar 64     ??
sourceTable Programme VMCDR4 Table name of merged sources varchar 64     ??
sourceTable Programme VMCDR5 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20110816 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20110909 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20120126 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20121128 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20130304 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20130805 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20140428 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20140903 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20150309 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20151218 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20160311 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20160822 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20170109 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20170411 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20171101 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20180702 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20181120 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20191212 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20210708 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20230816 Table name of merged sources varchar 64     ??
sourceTable Programme VMCv20240226 Table name of merged sources varchar 64     ??
sourceTable Programme VSAQC Table name of merged sources varchar 64     ??
sourceTable Programme VVVDR1 Table name of merged sources varchar 64     ??
sourceTable Programme VVVDR2 Table name of merged sources varchar 64     ??
sourceTable Programme VVVDR5 Table name of merged sources varchar 64     ??
sourceTable Programme VVVXDR1 Table name of merged sources varchar 64     ??
sourceTable Programme VVVv20100531 Table name of merged sources varchar 64     ??
sourceTable Programme VVVv20110718 Table name of merged sources varchar 64     ??
SPEC_TYPE mgcGalaxyStruct MGC SPD's CONTINUUM type (1=El 15.0, 2=Sa 7.4, 3=SC 2.2) tinyint 1   0  
SPECID spectra SIXDF unique ID no., used to generate GIF image of spectrum bigint 8      
SPECTRA twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM The flag is set to True if this source has a spectrum made in at least one exposure. varchar 5      
SPECTRA xmm3dr4 XMM The flag is set to 1 if this source has a spectrum made in at least one exposure. bit 1      
specType ogle3LpvLmcSource, ogle3LpvSmcSource OGLE Spectral type (O - oxygen-rich, C - carbon-rich) varchar 1     src.spType
spos twomass_sixx2_psc, twomass_sixx2_xsc TWOMASS # of scans in which src position falls inside coverage area smallint 2      
spt_ind allwise_sc WISE Level 7 HTM spatial index key int 4      
SQF3_6 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Source Quality Flag for 3.6um IRAC (Band 1) int 4   -9  
sqf3_6 sage_lmcIracSource SPITZER Source Quality Flag for band 3.6 int 4      
sqf3_6 sage_smcIRACv1_5Source SPITZER Source Quality Flag for 3.6um IRAC (Band 1) (see SAGE-SMC_IRAC_colDescriptions footnote 1) int 4      
SQF4_5 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Source Quality Flag for 4.5um IRAC (Band 2) int 4   -9  
sqf4_5 sage_lmcIracSource SPITZER Source Quality Flag for band 4.5 int 4      
sqf4_5 sage_smcIRACv1_5Source SPITZER Source Quality Flag for 4.5um IRAC (Band 2) (see SAGE-SMC_IRAC_colDescriptions footnote 1) int 4      
SQF5_8 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Source Quality Flag for 5.8um IRAC (Band 3) int 4   -9  
sqf5_8 sage_lmcIracSource SPITZER Source Quality Flag for band 5.8 int 4      
sqf5_8 sage_smcIRACv1_5Source SPITZER Source Quality Flag for 5.8um IRAC (Band 3) (see SAGE-SMC_IRAC_colDescriptions footnote 1) int 4      
SQF8_0 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Source Quality Flag for 8.0um IRAC (Band 4) int 4   -9  
sqf8_0 sage_lmcIracSource SPITZER Source Quality Flag for band 8.0 int 4      
sqf8_0 sage_smcIRACv1_5Source SPITZER Source Quality Flag for 8.0um IRAC (Band 4) (see SAGE-SMC_IRAC_colDescriptions footnote 1) int 4      
SQFH glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE 2MASS All-Sky PSC H Band Source Quality Flag int 4   -9  
sqfH sage_lmcIracSource SPITZER Source Quality Flag for band H int 4      
sqfH sage_smcIRACv1_5Source SPITZER 2MASS All-Sky PSC H Band Source Quality Flag (see SAGE-SMC_IRAC_colDescriptions footnote 1) int 4      
SQFJ glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE 2MASS All-Sky PSC J Band Source Quality Flag int 4   -9  
sqfJ sage_lmcIracSource SPITZER Source Quality Flag for band J int 4      
sqfJ sage_smcIRACv1_5Source SPITZER 2MASS All-Sky PSC J Band Source Quality Flag (see SAGE-SMC_IRAC_colDescriptions footnote 1) int 4      
sqfK sage_lmcIracSource SPITZER Source Quality Flag for band K int 4      
sqfK sage_smcIRACv1_5Source SPITZER 2MASS All-Sky PSC Ks Band Source Quality Flag (see SAGE-SMC_IRAC_colDescriptions footnote 1) int 4      
SQFKs glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE 2MASS All-Sky PSC Ks Band Source Quality Flag int 4   -9  
SQL1 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Source Quality Flag for band 1 flux int 4   -9  
SQL2 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Source Quality Flag for band 2 flux int 4   -9  
SQL3 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Source Quality Flag for band 3 flux int 4   -9  
SQL4 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Source Quality Flag for band 4 flux int 4   -9  
sqlSchemaFile ExternalProduct SHARKSv20210222 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct SHARKSv20210421 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct ULTRAVISTADR4 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VHSDR3 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VHSDR4 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VHSDR5 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VHSDR6 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VHSv20150108 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VHSv20160114 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VHSv20160507 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VHSv20170630 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VHSv20180419 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VHSv20201209 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VHSv20231101 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VHSv20240731 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 64   'NONE'  
sqlSchemaFile ExternalProduct VIDEODR4 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VIDEODR5 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VIKINGDR4 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VIKINGv20150421 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VIKINGv20151230 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VIKINGv20160406 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VIKINGv20161202 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VIKINGv20170715 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCDEEPv20230713 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCDEEPv20240506 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 64   'NONE'  
sqlSchemaFile ExternalProduct VMCDR3 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCDR4 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCDR5 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20140428 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20140903 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20150309 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20151218 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20160311 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20160822 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20170109 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20170411 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20171101 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20180702 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20181120 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20191212 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20210708 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20230816 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VMCv20240226 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 64   'NONE'  
sqlSchemaFile ExternalProduct VVVDR5 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
sqlSchemaFile ExternalProduct VVVXDR1 Relative path of the schema file containing the table description that the data will be ingested into if necessary varchar 32   'NONE'  
src allwise_sc WISE Sequential number of the source extraction in the Atlas Tile from in which this source detected and measured, in approximate descending order of W1 source brightness. int 4      
src wise_allskysc WISE Sequential number of this source extraction in the Atlas Tile from which this source was extracted, in approximate descending order of W1 source brightness. bigint 8      
src wise_prelimsc WISE Sequential number of this source extraction in the Atlas Tile from which this source was extracted, in approximate descending order of W1 source brightness bigint 8      
SRC_NUM twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The (decimal) source number in the individual source list for this observation; in the hexadecimal system it identifies the source-specific product files belonging to this detection. int 4      
srcCps rosat_bsc, rosat_fsc ROSAT source countrate in the broad energy band, vignetting corrected real 4 counts/sec   phot.count;em.X-ray
srcdens1 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Local source density for band 1 real 4 #/sqamin -9.9  
srcdens2 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Local source density for band 2 real 4 #/sqamin -9.9  
srcdens3 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Local source density for band 3 real 4 #/sqamin -9.9  
srcdens3_6 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Local source density for 3.6um IRAC (Band 1) real 4 arcmin**-2 -9.9  
srcdens4 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Local source density for band 4 real 4 #/sqamin -9.9  
srcdens4_5 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Local source density for 4.5um IRAC (Band 2) real 4 arcmin**-2 -9.9  
srcdens5_8 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Local source density for 5.8um IRAC (Band 3) real 4 arcmin**-2 -9.9  
srcdens8_0 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Local source density for 8.0um IRAC (Band 4) real 4 arcmin**-2 -9.9  
srcDensity3_6 sage_lmcIracSource SPITZER Local source density for band 3.6 real 4 #/sq arcmin    
srcDensity3_6 sage_smcIRACv1_5Source SPITZER Local source density for 3.6um IRAC (Band 1). See section 4.1 of GLIMPSE Data Products (v1.5) document. real 4 #/sq arcmin    
srcDensity4_5 sage_lmcIracSource SPITZER Local source density for band 4.5 real 4 #/sq arcmin    
srcDensity4_5 sage_smcIRACv1_5Source SPITZER Local source density for 4.5um IRAC (Band 2). See section 4.1 of GLIMPSE Data Products (v1.5) document. real 4 #/sq arcmin    
srcDensity5_8 sage_lmcIracSource SPITZER Local source density for band 5.8 real 4 #/sq arcmin    
srcDensity5_8 sage_smcIRACv1_5Source SPITZER Local source density for 5.8um IRAC (Band 3). See section 4.1 of GLIMPSE Data Products (v1.5) document. real 4 #/sq arcmin    
srcDensity8_0 sage_lmcIracSource SPITZER Local source density for band 8.0 real 4 #/sq arcmin    
srcDensity8_0 sage_smcIRACv1_5Source SPITZER Local source density for 8.0um IRAC (Band 4). See section 4.1 of GLIMPSE Data Products (v1.5) document. real 4 #/sq arcmin    
SRCID twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM A unique number assigned to a group of catalogue entries which are assumed to be the same source. To identify members of the same group the distance in arcseconds between each pair of sources was compared on the two-sigma level of both positional errors. A maximum distance of 7" was assumed, which was reduced to 0.9 * DIST_NN (distance to the nearest neighbour) where necessary. int 4      
srcID rosat_bsc, rosat_fsc ROSAT SASS source number (MASOL number) in SASS field varchar 4     meta.id
SRCID_2XMMi twoxmmi_dr3_v1_0 XMM The unique source ID of the detection, DETID, in the 2XMMi catalogue. Due to the nature of the matching algorithm, some detections were re-assigned to a different source due to the presence of new detections. int 4      
SRCID_2XMMP twoxmm, twoxmm_v1_2 XMM The source ID of the 2XMMp unique source matched within radius of 3" and using the closest candidate. int 4      
srcl rosat_bsc, rosat_fsc ROSAT likelihood of source detection smallint 2     stat.likelihood
srcName glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE GLIMPSEI Highly Reliable Catalogue source name varchar 32     meta.id;meta.main
srcName glimpse_hrc_inter GLIMPSE GLIMPSE Highly Reliable Catalogue source name varchar 32     meta.id;meta.main
srcName glimpse_mca_inter GLIMPSE GLIMPSE More Complete Archive source name varchar 32     meta.id;meta.main
srcName rosat_bsc, rosat_fsc ROSAT ROSAT All-Sky Survey Catalogue source name varchar 16     meta.id;meta.main
stackRadius RequiredStack SHARKSv20210421 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack ULTRAVISTADR4 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSDR1 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSDR2 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSDR3 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSDR4 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSDR5 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSDR6 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSv20120926 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSv20130417 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSv20150108 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSv20160114 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSv20160507 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSv20170630 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSv20180419 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSv20201209 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSv20231101 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VHSv20240731 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIDEODR2 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIDEODR3 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIDEODR4 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIDEODR5 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIDEOv20100513 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIDEOv20111208 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIKINGDR2 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIKINGDR3 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIKINGDR4 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIKINGv20110714 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIKINGv20111019 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIKINGv20130417 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIKINGv20150421 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIKINGv20151230 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIKINGv20160406 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIKINGv20161202 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VIKINGv20170715 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCDEEPv20230713 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCDEEPv20240506 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCDR1 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCDR3 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCDR4 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCDR5 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20110816 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20110909 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20120126 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20121128 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20130304 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20130805 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20140428 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20140903 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20150309 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20151218 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20160311 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20160822 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20170109 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20170411 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20171101 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20180702 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20181120 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20191212 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20210708 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20230816 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VMCv20240226 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VSAQC radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VVVDR1 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VVVDR2 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VVVDR5 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VVVXDR1 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VVVv20100531 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack VVVv20110718 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
stackRadius RequiredStack, RequiredTile SHARKSv20210222 radius within which intermediate stacks are selected for this deep stack. real 4 deg -0.9999995e9  
starDensity twompzPhotoz TWOMPZ Coadd log(density) of stars with K<14 at this position {image primary HDU keyword: density} real 4   -0.9999995e9  
starProb vmcPsfSource VMCDR5 Discrete star probability 1=100% to be a star, 0=0% probability to be a star {catalogue TType keyword: Star_prob} real 4     stat.probability
starProb vmcPsfSource VMCv20180702 Discrete star probability 1=100% to be a star, 0=0% probability to be a star {catalogue TType keyword: Star_prob} real 4     stat.probability
starProb vmcPsfSource VMCv20181120 Discrete star probability 1=100% to be a star, 0=0% probability to be a star {catalogue TType keyword: Star_prob} real 4     stat.probability
starProb vmcPsfSource VMCv20191212 Discrete star probability 1=100% to be a star, 0=0% probability to be a star {catalogue TType keyword: Star_prob} real 4     stat.probability
starProb vmcPsfSource VMCv20210708 Discrete star probability 1=100% to be a star, 0=0% probability to be a star {catalogue TType keyword: Star_prob} real 4     stat.probability
starProb vmcPsfSource VMCv20230816 Discrete star probability 1=100% to be a star, 0=0% probability to be a star {catalogue TType keyword: Star_prob} real 4     stat.probability
starProb vmcPsfSource VMCv20240226 Discrete star probability 1=100% to be a star, 0=0% probability to be a star {catalogue TType keyword: Star_prob} real 4     stat.probability
startDate AstrCalVers SHARKSv20210222 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers SHARKSv20210421 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers ULTRAVISTADR4 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSDR1 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSDR2 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSDR3 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSDR4 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSDR5 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSDR6 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSv20120926 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSv20130417 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSv20150108 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSv20160114 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSv20160507 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSv20170630 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSv20180419 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSv20201209 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSv20231101 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VHSv20240731 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIDEODR2 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIDEODR3 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIDEODR4 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIDEODR5 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIDEOv20100513 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIDEOv20111208 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIKINGDR2 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIKINGDR3 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIKINGDR4 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIKINGv20110714 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIKINGv20111019 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIKINGv20130417 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIKINGv20150421 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIKINGv20151230 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIKINGv20160406 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIKINGv20161202 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VIKINGv20170715 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCDEEPv20230713 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCDEEPv20240506 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCDR1 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCDR3 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCDR4 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCDR5 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20110816 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20110909 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20120126 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20121128 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20130304 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20130805 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20140428 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20140903 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20150309 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20151218 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20160311 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20160822 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20170109 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20170411 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20171101 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20180702 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20181120 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20191212 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20210708 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20230816 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VMCv20240226 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VVVDR1 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VVVDR2 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VVVDR5 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VVVXDR1 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VVVv20100531 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate AstrCalVers VVVv20110718 MJD of the start time for this version of the calibration float 8 Julian days   time.epoch
startDate PhotCalVers SHARKSv20210222 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers SHARKSv20210421 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers ULTRAVISTADR4 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSDR1 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSDR2 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSDR3 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSDR4 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSDR5 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSDR6 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSv20120926 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSv20130417 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSv20150108 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSv20160114 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSv20160507 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSv20170630 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSv20180419 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSv20201209 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSv20231101 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VHSv20240731 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIDEODR2 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIDEODR3 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIDEODR4 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIDEODR5 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIDEOv20100513 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIDEOv20111208 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIKINGDR2 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIKINGDR3 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIKINGDR4 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIKINGv20110714 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIKINGv20111019 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIKINGv20130417 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIKINGv20150421 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIKINGv20151230 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIKINGv20160406 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIKINGv20161202 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VIKINGv20170715 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCDEEPv20230713 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCDEEPv20240506 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCDR1 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCDR3 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCDR4 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCDR5 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20110816 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20110909 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20120126 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20121128 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20130304 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20130805 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20140428 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20140903 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20150309 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20151218 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20160311 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20160822 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20170109 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20170411 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20171101 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20180702 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20181120 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20191212 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20210708 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20230816 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VMCv20240226 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VVVDR1 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VVVDR2 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VVVDR5 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VVVXDR1 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VVVv20100531 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
startDate PhotCalVers VVVv20110718 Date time of start time for this version of the calibration (MM-DD-YYYY) datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
status ProgrammeCurationHistory SHARKSv20210222 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory SHARKSv20210421 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory ULTRAVISTADR4 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSDR1 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSDR2 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSDR3 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSDR4 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSDR5 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSDR6 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSv20120926 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSv20130417 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSv20150108 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSv20160114 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSv20160507 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSv20170630 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSv20180419 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSv20201209 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSv20231101 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VHSv20240731 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIDEODR2 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIDEODR3 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIDEODR4 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIDEODR5 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIDEOv20100513 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIDEOv20111208 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIKINGDR2 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIKINGDR3 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIKINGDR4 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIKINGv20110714 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIKINGv20111019 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIKINGv20130417 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIKINGv20150421 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIKINGv20151230 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIKINGv20160406 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIKINGv20161202 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VIKINGv20170715 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCDEEPv20230713 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCDEEPv20240506 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCDR1 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCDR3 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCDR4 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCDR5 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20110816 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20110909 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20120126 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20121128 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20130304 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20130805 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20140428 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20140903 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20150309 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20151218 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20160311 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20160822 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20170109 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20170411 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20171101 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20180702 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20181120 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20191212 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20210708 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20230816 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VMCv20240226 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VSAQC successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VVVDR1 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VVVDR2 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VVVDR5 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VVVXDR1 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VVVv20100531 successful (1) or unsuccessful (0) tinyint 1     meta.code
status ProgrammeCurationHistory VVVv20110718 successful (1) or unsuccessful (0) tinyint 1     meta.code
std_dev phot_variable_time_series_g_fov_statistical_parameters GAIADR1 Square root of the unweighted variance of the G-band time series values float 8 mag   phot.mag;stat.stdev
stdCRms CurrentAstrometry SHARKSv20210222 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry SHARKSv20210421 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry ULTRAVISTADR4 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSDR1 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSDR2 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSDR3 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSDR4 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSDR5 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSDR6 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSv20120926 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSv20130417 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSv20140409 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSv20150108 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSv20160114 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSv20160507 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSv20170630 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSv20180419 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSv20201209 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSv20231101 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VHSv20240731 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIDEODR2 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIDEODR3 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIDEODR4 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIDEODR5 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIDEOv20100513 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIDEOv20111208 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIKINGDR2 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIKINGDR3 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIKINGDR4 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIKINGv20110714 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIKINGv20111019 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIKINGv20130417 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIKINGv20140402 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIKINGv20150421 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIKINGv20151230 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIKINGv20160406 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIKINGv20161202 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VIKINGv20170715 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCDEEPv20230713 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCDEEPv20240506 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCDR1 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCDR2 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCDR3 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCDR4 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCDR5 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20110816 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20110909 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20120126 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20121128 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20130304 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20130805 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20140428 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20140903 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20150309 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20151218 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20160311 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20160822 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20170109 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20170411 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20171101 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20180702 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20181120 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20191212 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20210708 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20230816 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VMCv20240226 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VVVDR1 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VVVDR2 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VVVDR5 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VVVXDR1 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VVVv20100531 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms CurrentAstrometry VVVv20110718 RMS residual of fit to astrometric standards {image extension keyword: STDCRMS} float 8   -0.9999995e9 stat.fit.residual
stdCRms sharksCurrentAstrometry, ultravistaCurrentAstrometry, vhsCurrentAstrometry, videoCurrentAstrometry, vikingCurrentAstrometry, vmcCurrentAstrometry, vvvCurrentAstrometry VSAQC RMS residual of fit to astrometric standards float 8   -0.9999995e9 stat.fit.residual
StdDev_HRV ravedr5Source RAVE Standard deviation in HRV from 10 resampled spectra float 8 km/s   stat.stddev;spect.dopplerVeloc;pos.heliocentric
StdDev_logg_K ravedr5Source RAVE Standard deviation of surface gravity from 10 resampled spectra float 8 dex   stat.stddev;phys.gravity
StdDev_Met_K ravedr5Source RAVE Standard deviation in Met_K from 10 resampled spectra float 8 dex   stat.stddev;phys.abund.Z
StdDev_Teff_K ravedr5Source RAVE Standard deviation in Teff_K from 10 resampled spectra float 8 K   stat.stddev;phys.temperature.effective
STEL mgcDetection MGC Stellaricity real 4      
stellardets vvvParallaxCatalogue, vvvProperMotionCatalogue VVVDR5 the number of pawprint sets in which the source had a stellar modal morphological classification. {catalogue TType keyword: stellardets} int 4   -99999999  
stellarity combo17CDFSSource COMBO17 stellarity index from SExtractor real 4      
STN_SPARV ravedr5Source RAVE (R+) Signal/Noise Ratio of SPARV Pipeline V 5.x float 8     stat.snr
Strip denisDR3Source DENIS DENIS strip number int 4      
strprms MultiframeDetector SHARKSv20210222 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector SHARKSv20210421 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector ULTRAVISTADR4 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSDR1 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSDR2 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSDR3 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSDR4 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSDR5 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSDR6 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSv20120926 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSv20130417 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSv20140409 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSv20150108 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSv20160114 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSv20160507 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSv20170630 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSv20180419 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSv20201209 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSv20231101 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VHSv20240731 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIDEODR2 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIDEODR3 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIDEODR4 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIDEODR5 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIDEOv20100513 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIDEOv20111208 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIKINGDR2 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIKINGDR3 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIKINGDR4 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIKINGv20110714 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIKINGv20111019 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIKINGv20130417 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIKINGv20140402 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIKINGv20150421 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIKINGv20151230 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIKINGv20160406 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIKINGv20161202 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VIKINGv20170715 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCDEEPv20230713 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCDEEPv20240506 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCDR1 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCDR2 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCDR3 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCDR4 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCDR5 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20110816 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20110909 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20120126 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20121128 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20130304 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20130805 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20140428 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20140903 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20150309 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20151218 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20160311 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20160822 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20170109 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20170411 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20171101 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20180702 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20181120 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20191212 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20210708 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20230816 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VMCv20240226 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VVVDR1 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VVVDR2 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VVVDR5 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VVVXDR1 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VVVv20100531 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms MultiframeDetector VVVv20110718 RMS of stripe pattern removed {image extension keyword: STRPRMS} real 4   -0.9999995e9  
strprms sharksMultiframeDetector, ultravistaMultiframeDetector, vhsMultiframeDetector, videoMultiframeDetector, vikingMultiframeDetector, vmcMultiframeDetector, vvvMultiframeDetector VSAQC RMS of stripe pattern removed real 4   -0.9999995e9  
subType ogle3LpvLmcSource, ogle3LpvSmcSource OGLE Subtype of LPVs (Mira, SRV, OSARG) varchar 5     meta.type
subtype ogle4RRLyrLmcSource, ogle4RRLyrSmcSource OGLE Subtype of RR Lyr star (RRab, RRc, RRd, RRe) varchar 5     meta.type
SUM_FLAG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM The summary flag of the source is derived from EP_FLAG. It is 0 if none of the nine flags was set; it is set to 1 if at least one of the warning flags (flag 1, 2, 3, 9) was set but no possible-spurious-detection flag (flag 7, 8); it is set to 2 if at least one of the possible-spurious-detection flags (flag 7, 8) was set but not the manual flag (flag 11); it is set to 3 if the manual flag (flag 11) was set but no possible-spurious-detection flags (flag 7, 8); it is set to 4 if the manual flag (flag 11) as well as one of the possible-spurious-detection flags (flag 7, 8) is set. The meaning is thus: 0 = good, 1 = source parameters may be affected, 2 = possibly spurious, 3 = located in a area where spurious detection may occur, 4 = located in a area where spurious detection may occur and possibly spurious. . int 4      
SUM_FLAG xmm3dr4 XMM The summary flag of the source is derived from EP_FLAG. It is 0 if none of the nine flags was set; it is set to 1 if at least one of the warning flags (flag 1, 2, 3, 9) was set but no possible-spurious-detection flag (flag 7, 8); it is set to 2 if at least one of the possible-spurious-detection flags (flag 7, 8) was set but not the manual flag (flag 11); it is set to 3 if the manual flag (flag 11) was set but no possible-spurious-detection flags (flag 7, 8); it is set to 4 if the manual flag (flag 11) as well as one of the possible-spurious-detection flags (flag 7, 8) is set. The meaning is thus: 0 = good, 1 = source parameters may be affected, 2 = possibly spurious, 3 = located in a area where spurious detection may occur, 4 = located in a area where spurious detection may occur and possibly spurious. . smallint 2      
sumWeight ultravistaMapRemeasAver ULTRAVISTADR4 Normalised (conf=100 in a pawprint=1) sum of all the weights, giving estimate of depth real 4      
sumWeight vikingMapRemeasAver VIKINGZYSELJv20160909 Normalised (conf=100 in a pawprint=1) sum of all the weights, giving extimate of depth real 4      
sumWeight vikingMapRemeasAver VIKINGZYSELJv20170124 Normalised (conf=100 in a pawprint=1) sum of all the weights, giving extimate of depth real 4      
sup_ba twomass_sixx2_xsc TWOMASS minor/major axis ratio fit to 3-sig. super-coadd isophote real 4      
sup_ba twomass_xsc TWOMASS Minor/major axis ratio fit to 3-sig. super-coadd isophote. real 4     phys.size.axisRatio
sup_chif_ellf twomass_xsc TWOMASS super-coadd % chi-fraction for ellip. fit to 3-sig isophote. real 4     stat.fit.param
sup_dec twomass_xsc TWOMASS Super-coadd centroid Dec (J2000 decimal deg). float 8 degrees   pos.eq.dec;meta.main
sup_phi twomass_sixx2_xsc TWOMASS super-coadd angle to major axis (E of N) smallint 2 deg    
sup_phi twomass_xsc TWOMASS Super-coadd angle to major axis (E of N). smallint 2 degrees   pos.posAng
sup_r_3sig twomass_xsc TWOMASS Super-coadd 3-sigma isophotal semi-major axis radius. real 4 arcsec   stat.error
sup_ra twomass_xsc TWOMASS Super-coadd centroid RA (J2000 decimal deg). float 8 degrees   pos.eq.ra;meta.main
supDec twompzPhotoz TWOMPZ Super co-add centroid Dec. (J2000) {image primary HDU keyword: supDEdeg} float 8 Degrees -0.9999995e9 pos.eq.dec
supRa twompzPhotoz TWOMPZ Super co-add centroid R.A. (J2000) {image primary HDU keyword: supRAdeg} float 8 Degrees -0.9999995e9 pos.eq.ra
surveyID Detection, StackObjectThin PS1DR2 Survey identifier. Details in the Survey table. tinyint 1      
surveyID ExternalSurvey SHARKSv20210421 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey ULTRAVISTADR4 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSDR1 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSDR2 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSDR3 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSDR4 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSDR5 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSDR6 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSv20120926 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSv20130417 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSv20150108 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSv20160114 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSv20160507 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSv20170630 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSv20180419 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSv20201209 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSv20231101 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VHSv20240731 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIDEODR2 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIDEODR3 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIDEODR4 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIDEODR5 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIDEOv20100513 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIDEOv20111208 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIKINGDR2 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIKINGDR3 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIKINGDR4 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIKINGv20110714 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIKINGv20111019 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIKINGv20130417 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIKINGv20150421 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIKINGv20151230 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIKINGv20160406 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIKINGv20161202 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VIKINGv20170715 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCDEEPv20230713 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCDEEPv20240506 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCDR1 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCDR3 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCDR4 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCDR5 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20110816 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20110909 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20120126 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20121128 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20130304 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20130805 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20140428 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20140903 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20150309 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20151218 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20160311 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20160822 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20170109 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20170411 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20171101 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20180702 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20181120 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20191212 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20210708 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20230816 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VMCv20240226 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VSAQC the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VVVDR1 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VVVDR2 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VVVDR5 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VVVXDR1 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VVVv20100531 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey VVVv20110718 the unique identifier for the survey int 4     meta.id
surveyID ExternalSurvey, ExternalSurveyTable, MapSurveyTables, Release, RequiredNeighbours SHARKSv20210222 the unique identifier for the survey int 4     meta.id
surveyID ObjectThin PS1DR2 Survey identifier. Details in the Survey table. tinyint 1     meta.id
surveyID RequiredListDrivenProduct VHSDR1 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VHSDR2 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VHSv20120926 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VHSv20130417 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VIDEODR2 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VIDEODR3 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VIDEOv20100513 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VIDEOv20111208 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VIKINGDR2 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VIKINGDR3 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VIKINGv20110714 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VIKINGv20111019 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VIKINGv20130417 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VMCDR1 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VMCv20110816 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VMCv20110909 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VMCv20120126 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VMCv20121128 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VMCv20130304 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VMCv20130805 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VVVDR1 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VVVv20100531 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID RequiredListDrivenProduct VVVv20110718 the unique ID of the external survey (if applicable) int 4   -99999999 meta.id
surveyID Survey SHARKSv20210421 The unique identifier for the curated survey int 4     meta.id
surveyID Survey ULTRAVISTADR4 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSDR1 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSDR2 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSDR3 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSDR4 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSDR5 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSDR6 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSv20120926 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSv20130417 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSv20150108 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSv20160114 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSv20160507 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSv20170630 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSv20180419 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSv20201209 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSv20231101 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VHSv20240731 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIDEODR2 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIDEODR3 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIDEODR4 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIDEODR5 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIDEOv20100513 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIDEOv20111208 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIKINGDR2 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIKINGDR3 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIKINGDR4 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIKINGv20110714 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIKINGv20111019 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIKINGv20130417 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIKINGv20150421 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIKINGv20151230 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIKINGv20160406 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIKINGv20161202 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VIKINGv20170715 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCDEEPv20230713 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCDEEPv20240506 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCDR1 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCDR3 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCDR4 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCDR5 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20110816 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20110909 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20120126 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20121128 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20130304 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20130805 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20140428 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20140903 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20150309 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20151218 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20160311 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20160822 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20170109 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20170411 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20171101 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20180702 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20181120 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20191212 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20210708 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20230816 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VMCv20240226 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VSAQC The unique identifier for the curated survey int 4     meta.id
surveyID Survey VVVDR1 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VVVDR2 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VVVDR5 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VVVXDR1 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VVVv20100531 The unique identifier for the curated survey int 4     meta.id
surveyID Survey VVVv20110718 The unique identifier for the curated survey int 4     meta.id
surveyID Survey, SurveyProgrammes SHARKSv20210222 The unique identifier for the curated survey int 4     meta.id
surveyIDString Multiframe SHARKSv20210222 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe SHARKSv20210421 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe ULTRAVISTADR4 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSDR1 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSDR2 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSDR3 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSDR4 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSDR5 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSDR6 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSv20120926 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSv20130417 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSv20140409 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSv20150108 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSv20160114 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSv20160507 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSv20170630 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSv20180419 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSv20201209 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSv20231101 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VHSv20240731 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIDEODR2 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIDEODR3 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIDEODR4 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIDEODR5 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIDEOv20111208 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIKINGDR2 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIKINGDR3 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIKINGDR4 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIKINGv20110714 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIKINGv20111019 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIKINGv20130417 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIKINGv20140402 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIKINGv20150421 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIKINGv20151230 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIKINGv20160406 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIKINGv20161202 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VIKINGv20170715 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCDEEPv20230713 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCDEEPv20240506 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCDR1 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCDR2 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCDR3 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCDR4 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCDR5 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20110816 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20110909 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20120126 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20121128 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20130304 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20130805 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20140428 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20140903 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20150309 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20151218 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20160311 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20160822 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20170109 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20170411 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20171101 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20180702 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20181120 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20191212 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20210708 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20230816 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VMCv20240226 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VVVDR1 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VVVDR2 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VVVDR5 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VVVXDR1 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString Multiframe VVVv20110718 SADT survey ID {image primary HDU keyword: HIERARCH ESO OCS SADT ID} varchar 64   NONE  
surveyIDString sharksMultiframe, ultravistaMultiframe, vhsMultiframe, videoMultiframe, vikingMultiframe, vmcMultiframe, vvvMultiframe VSAQC SADT survey ID varchar 64   NONE  
surveyName ExternalSurvey SHARKSv20210222 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey SHARKSv20210421 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey ULTRAVISTADR4 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSDR1 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSDR2 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSDR3 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSDR4 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSDR5 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSDR6 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSv20120926 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSv20130417 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSv20150108 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSv20160114 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSv20160507 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSv20170630 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSv20180419 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSv20201209 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSv20231101 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VHSv20240731 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIDEODR2 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIDEODR3 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIDEODR4 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIDEODR5 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIDEOv20100513 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIDEOv20111208 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIKINGDR2 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIKINGDR3 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIKINGDR4 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIKINGv20110714 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIKINGv20111019 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIKINGv20130417 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIKINGv20150421 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIKINGv20151230 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIKINGv20160406 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIKINGv20161202 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VIKINGv20170715 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCDEEPv20230713 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCDEEPv20240506 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCDR1 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCDR3 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCDR4 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCDR5 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20110816 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20110909 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20120126 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20121128 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20130304 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20130805 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20140428 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20140903 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20150309 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20151218 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20160311 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20160822 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20170109 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20170411 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20171101 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20180702 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20181120 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20191212 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20210708 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20230816 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VMCv20240226 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VSAQC The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VVVDR1 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VVVDR2 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VVVDR5 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VVVXDR1 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VVVv20100531 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
surveyName ExternalSurvey VVVv20110718 The short name of the survey, eg. 2MASS, GLIMPSE etc. varchar 32     ??
SVMClass wiseScosSvm WISExSCOSPZ SVM classification {image primary HDU keyword: SVMClass} smallint 2   -9999  
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCDR1 the UID of the relevant frame set bigint 8     obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCDR2 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCDR3 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCDR4 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCDR5 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20110816 the UID of the relevant frame set bigint 8     obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20110909 the UID of the relevant frame set bigint 8     obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20120126 the UID of the relevant frame set bigint 8     obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20121128 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20130304 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20130805 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20140428 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20140903 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20150309 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20151218 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20160311 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20160822 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20170109 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20170411 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20171101 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20180702 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20181120 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20191212 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20210708 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20230816 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSourceXSynopticSourceBestMatch VMCv20240226 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcSynopticMergeLog VMCDR1 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCDR2 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCDR3 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCDR4 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCDR5 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20110816 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20110909 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20120126 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20121128 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20130304 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20130805 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20140428 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20140903 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20150309 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20151218 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20160311 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20160822 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20170109 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20170411 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20171101 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20180702 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20181120 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20191212 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20210708 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20230816 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticMergeLog VMCv20240226 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCDR1 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCDR2 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCDR3 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCDR4 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCDR5 UID of the set of frames that this merged source comes from bigint 8     meta.id
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20110816 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20110909 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20120126 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20121128 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20130304 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20130805 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20140428 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20140903 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20150309 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20151218 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20160311 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20160822 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20170109 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20170411 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20171101 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20180702 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20181120 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20191212 UID of the set of frames that this merged source comes from bigint 8     meta.id
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20210708 UID of the set of frames that this merged source comes from bigint 8     meta.id
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20230816 UID of the set of frames that this merged source comes from bigint 8     meta.id
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcSynopticSource VMCv20240226 UID of the set of frames that this merged source comes from bigint 8     meta.id
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcdeepSourceXSynopticSourceBestMatch VMCDEEPv20230713 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcdeepSourceXSynopticSourceBestMatch VMCDEEPv20240506 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vmcdeepSynopticMergeLog VMCDEEPv20230713 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcdeepSynopticMergeLog VMCDEEPv20240506 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcdeepSynopticSource VMCDEEPv20230713 UID of the set of frames that this merged source comes from bigint 8     meta.id
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vmcdeepSynopticSource VMCDEEPv20240506 UID of the set of frames that this merged source comes from bigint 8     meta.id
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vvvSourceXSynopticSourceBestMatch VVVDR1 the UID of the relevant frame set bigint 8     meta.id;obs.field
synFrameSetID vvvSynopticMergeLog VVVDR1 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vvvSynopticMergeLog VVVDR2 frame set ID, unique over the whole VSA via programme ID prefix, assigned by merging procedure bigint 8     meta.id;obs.field
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vvvSynopticSource VVVDR1 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synFrameSetID vvvSynopticSource VVVDR2 UID of the set of frames that this merged source comes from bigint 8     meta.bib
Each merged source in the merged source tables come from a set of individual passband frames (with different filters and/or different epochs of observation). In the WSA, a frame is generally the image provided by one detector (dither-stacked and interlaced as appropriate); hence a frame set comprises a set of individual detector frames in different passbands and/or at different observation epochs. Each frame set is uniquely identified by the attribute frameSetID, and this references a row in the corresponding merge log for the source table (for example, vhsSource.frameSetID references whsMergeLog.frameSetID. The merge log in turn references the full set of image descriptive data held in the tables MultiframeDetector and ultimately Multiframe (these two tables map directly onto the multi-extension FITS file hierarchy of extension FITS headers beneath a single primary HDU FITS header - primary HDU FITS keys will be found in Multiframe, while the corresponding extension FITS keys for each primary set will be found in table MultiframeDetector). In this way, you can trace the provenance of a merged source record right back to the individual image frames from which it is derived.
synopticBestMatchTable Programme SHARKSv20210222 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme SHARKSv20210421 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme ULTRAVISTADR4 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSDR1 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSDR2 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSDR3 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSDR4 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSDR5 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSDR6 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSv20120926 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSv20130417 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSv20150108 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSv20160114 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSv20160507 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSv20170630 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSv20180419 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSv20201209 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSv20231101 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VHSv20240731 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIDEODR2 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIDEODR3 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIDEODR4 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIDEODR5 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIDEOv20100513 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIDEOv20111208 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIKINGDR2 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIKINGDR3 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIKINGDR4 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIKINGv20110714 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIKINGv20111019 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIKINGv20130417 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIKINGv20150421 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIKINGv20151230 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIKINGv20160406 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIKINGv20161202 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VIKINGv20170715 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCDEEPv20230713 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCDEEPv20240506 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCDR1 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCDR3 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCDR4 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCDR5 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20110816 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20110909 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20120126 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20121128 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20130304 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20130805 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20140428 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20140903 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20150309 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20151218 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20160311 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20160822 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20170109 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20170411 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20171101 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20180702 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20181120 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20191212 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20210708 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20230816 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VMCv20240226 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VSAQC Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VVVDR1 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VVVDR2 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VVVDR5 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VVVXDR1 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VVVv20100531 Table name of merged variable sources varchar 64   'NONE' ??
synopticBestMatchTable Programme VVVv20110718 Table name of merged variable sources varchar 64   'NONE' ??
synopticID vmcSynopticSource VMCDR1 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCDR2 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCDR3 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCDR4 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCDR5 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20110816 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20110909 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20120126 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20121128 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20130304 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20130805 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20140428 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20140903 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20150309 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20151218 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20160311 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20160822 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20170109 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20170411 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20171101 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20180702 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20181120 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20191212 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20210708 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20230816 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcSynopticSource VMCv20240226 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcdeepSynopticSource VMCDEEPv20230713 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vmcdeepSynopticSource VMCDEEPv20240506 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vvvSynopticSource VVVDR1 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticID vvvSynopticSource VVVDR2 UID (unique over entire VSA via programme ID prefix) of this merged detection as assigned by merge algorithm bigint 8     meta.id;meta.main
synopticSetUp Programme SHARKSv20210222 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme SHARKSv20210421 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme ULTRAVISTADR4 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSDR1 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSDR2 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSDR3 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSDR4 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSDR5 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSDR6 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSv20120926 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSv20130417 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSv20150108 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSv20160114 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSv20160507 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSv20170630 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSv20180419 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSv20201209 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSv20231101 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VHSv20240731 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIDEODR2 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIDEODR3 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIDEODR4 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIDEODR5 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIDEOv20111208 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIKINGDR2 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIKINGDR3 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIKINGDR4 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIKINGv20110714 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIKINGv20111019 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIKINGv20130417 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIKINGv20150421 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIKINGv20151230 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIKINGv20160406 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIKINGv20161202 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VIKINGv20170715 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCDEEPv20230713 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCDEEPv20240506 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCDR1 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCDR3 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCDR4 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCDR5 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20110816 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20110909 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20120126 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20121128 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20130304 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20130805 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20140428 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20140903 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20150309 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20151218 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20160311 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20160822 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20170109 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20170411 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20171101 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20180702 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20181120 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20191212 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20210708 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20230816 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VMCv20240226 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VSAQC A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VVVDR1 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VVVDR2 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VVVDR5 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VVVXDR1 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSetUp Programme VVVv20110718 A string describing the synoptic setup for more complicated surveys varchar 64   NONE ??
synopticSourceTable Programme SHARKSv20210222 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme SHARKSv20210421 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme ULTRAVISTADR4 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSDR1 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSDR2 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSDR3 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSDR4 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSDR5 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSDR6 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSv20120926 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSv20130417 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSv20150108 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSv20160114 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSv20160507 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSv20170630 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSv20180419 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSv20201209 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSv20231101 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VHSv20240731 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIDEODR2 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIDEODR3 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIDEODR4 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIDEODR5 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIDEOv20100513 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIDEOv20111208 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIKINGDR2 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIKINGDR3 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIKINGDR4 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIKINGv20110714 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIKINGv20111019 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIKINGv20130417 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIKINGv20150421 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIKINGv20151230 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIKINGv20160406 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIKINGv20161202 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VIKINGv20170715 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCDEEPv20230713 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCDEEPv20240506 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCDR1 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCDR3 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCDR4 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCDR5 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20110816 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20110909 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20120126 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20121128 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20130304 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20130805 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20140428 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20140903 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20150309 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20151218 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20160311 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20160822 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20170109 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20170411 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20171101 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20180702 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20181120 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20191212 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20210708 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20230816 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VMCv20240226 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VSAQC Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VVVDR1 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VVVDR2 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VVVDR5 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VVVXDR1 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VVVv20100531 Table name of merged variable sources varchar 64   'NONE' ??
synopticSourceTable Programme VVVv20110718 Table name of merged variable sources varchar 64   'NONE' ??
synSeqNum vmcSourceXSynopticSourceBestMatch VMCDR2 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCDR3 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCDR4 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCDR5 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.id
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20110816 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.id
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20110909 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.id
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20120126 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.id
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20121128 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20130304 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20130805 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20140428 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20140903 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20150309 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20151218 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20160311 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20160822 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20170109 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20170411 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20171101 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20180702 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20181120 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20191212 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.id
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20210708 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.id
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20230816 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.id
synSeqNum vmcSourceXSynopticSourceBestMatch VMCv20240226 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.id
synSeqNum vmcSourceXSynopticSourceBestMatch, vmcSynopticSource VMCDR1 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.id
synSeqNum vmcdeepSourceXSynopticSourceBestMatch VMCDEEPv20240506 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.id
synSeqNum vmcdeepSourceXSynopticSourceBestMatch, vmcdeepSynopticSource VMCDEEPv20230713 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.id
synSeqNum vvvSourceXSynopticSourceBestMatch, vvvSynopticSource VVVDR1 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
synSeqNum vvvSynopticSource VVVDR2 the running number of this source {catalogue TType keyword: Sequence_number}
The running number in this frameSet for ease of reference, in order of matching.
int 4     meta.number
sys_flg twomass_xsc TWOMASS system flag: 0=no system, 1=nearby galaxy flux incl. in mag. smallint 2     meta.code
SYSERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM The systematic 1 σ error on the detection position in arcseconds. It is set to be 0.35 arcsec if the SAS task eposcorr results in a statistically reliable cross-correlation with USNO B1.0 optical catalogue. Otherwise the error is 1.0 arsec. real 4 arcsec    
SYSERR xmm3dr4 XMM The estimated 1 σ error arising from the field rectification process (in arcseconds). If the SAS task catcorr results in a statistically reliable cross-correlation with the USNO B1.0, 2MASS or SDSS (DR8) optical/IR catalogues, SYSERRCC combines the errors on the translational shifts in the RA (rashift_error) and DEC (decshift_error) directions, together with the rotational error component, derived from from the catalogue that yields the 'best' solution, as follows: SYSERRCC = SQRT ( rashift_error² + decshift_error² + (r * thetarot_error)² ) where r is the radial off-axis angle of the detection from the spacecraft boresight in arcsecs and thetarot_error is the error on the rotational correction (in radians). Where catcorr fails to obtain a statistically reliable result, SYSERRCC is 1.5 arcseconds (see Sec. 3XMM-DR4 UG, Sec. 3.4 for details). Note that rashift_error, decshift_error and thetarot_error are not provided separately in the catalogue. real 4 arcsec    
sysErrJ vmcPsfSource VMCDR5 Local photometric systematic error in J, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_J} real 4 mag   stat.error;phot.mag;em.IR.J
sysErrJ vmcPsfSource VMCv20180702 Local photometric systematic error in J, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_J} real 4 mag   stat.error;phot.mag;em.IR.J
sysErrJ vmcPsfSource VMCv20181120 Local photometric systematic error in J, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_J} real 4 mag   stat.error;phot.mag;em.IR.J
sysErrJ vmcPsfSource VMCv20191212 Local photometric systematic error in J, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_J} real 4 mag   stat.error;phot.mag;em.IR.J
sysErrJ vmcPsfSource VMCv20210708 Local photometric systematic error in J, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_J} real 4 mag   stat.error;phot.mag;em.IR.J
sysErrJ vmcPsfSource VMCv20230816 Local photometric systematic error in J, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_J} real 4 mag   stat.error;phot.mag;em.IR.J
sysErrJ vmcPsfSource VMCv20240226 Local photometric systematic error in J, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_J} real 4 mag   stat.error;phot.mag;em.IR.J
sysErrKs vmcPsfSource VMCDR5 Local photometric systematic error in Ks, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Ks} real 4 mag   stat.error;phot.mag;em.IR.K
sysErrKs vmcPsfSource VMCv20180702 Local photometric systematic error in Ks, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Ks} real 4 mag   stat.error;phot.mag;em.IR.K
sysErrKs vmcPsfSource VMCv20181120 Local photometric systematic error in Ks, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Ks} real 4 mag   stat.error;phot.mag;em.IR.K
sysErrKs vmcPsfSource VMCv20191212 Local photometric systematic error in Ks, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Ks} real 4 mag   stat.error;phot.mag;em.IR.K
sysErrKs vmcPsfSource VMCv20210708 Local photometric systematic error in Ks, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Ks} real 4 mag   stat.error;phot.mag;em.IR.K
sysErrKs vmcPsfSource VMCv20230816 Local photometric systematic error in Ks, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Ks} real 4 mag   stat.error;phot.mag;em.IR.K
sysErrKs vmcPsfSource VMCv20240226 Local photometric systematic error in Ks, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Ks} real 4 mag   stat.error;phot.mag;em.IR.K
sysErrY vmcPsfSource VMCDR5 Local photometric systematic error in Y, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Y} real 4 mag   stat.error;phot.mag;em.IR.NIR
sysErrY vmcPsfSource VMCv20180702 Local photometric systematic error in Y, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Y} real 4 mag   stat.error;phot.mag;em.IR.NIR
sysErrY vmcPsfSource VMCv20181120 Local photometric systematic error in Y, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Y} real 4 mag   stat.error;phot.mag;em.IR.NIR
sysErrY vmcPsfSource VMCv20191212 Local photometric systematic error in Y, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Y} real 4 mag   stat.error;phot.mag;em.IR.NIR
sysErrY vmcPsfSource VMCv20210708 Local photometric systematic error in Y, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Y} real 4 mag   stat.error;phot.mag;em.IR.NIR
sysErrY vmcPsfSource VMCv20230816 Local photometric systematic error in Y, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Y} real 4 mag   stat.error;phot.mag;em.IR.NIR
sysErrY vmcPsfSource VMCv20240226 Local photometric systematic error in Y, calculated on bins of +/-0.05 magnitude on a ring of radius 0.025 degrees {catalogue TType keyword: syserr_Y} real 4 mag   stat.error;phot.mag;em.IR.NIR



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09/12/2024