K 
Name  Schema Table  Database  Description  Type  Length  Unit  Default Value  Unified Content Descriptor 
K 
twomass 
SIXDF 
K magnitude (corrected) used for K selection 
real 
4 
mag 


k_2mrat 
twomass_scn 
2MASS 
Ksband average 2nd image moment ratio. 
real 
4 


stat.fit.param 
k_2mrat 
twomass_sixx2_scn 
2MASS 
K band average 2nd image moment ratio for scan 
real 
4 



k_5sig_ba 
twomass_xsc 
2MASS 
K minor/major axis ratio fit to the 5sigma isophote. 
real 
4 


phys.size.axisRatio 
k_5sig_phi 
twomass_xsc 
2MASS 
K angle to 5sigma major axis (E of N). 
smallint 
2 
degrees 

stat.error 
k_5surf 
twomass_xsc 
2MASS 
K central surface brightness (r<=5). 
real 
4 
mag 

phot.mag.sb 
k_ba 
twomass_sixx2_xsc 
2MASS 
K minor/major axis ratio fit to the 3sigma isophote 
real 
4 



k_ba 
twomass_xsc 
2MASS 
K minor/major axis ratio fit to the 3sigma isophote. 
real 
4 


phys.size.axisRatio 
k_back 
twomass_xsc 
2MASS 
K coadd median background. 
real 
4 


meta.code 
k_bisym_chi 
twomass_xsc 
2MASS 
K bisymmetric crosscorrelation chi. 
real 
4 


stat.fit.param 
k_bisym_rat 
twomass_xsc 
2MASS 
K bisymmetric flux ratio. 
real 
4 


phot.flux;arith.ratio 
k_bndg_amp 
twomass_xsc 
2MASS 
K banding maximum FT amplitude on this side of coadd. 
real 
4 
DN 

stat.fit.param 
k_bndg_per 
twomass_xsc 
2MASS 
K banding Fourier Transf. period on this side of coadd. 
int 
4 
arcsec 

stat.fit.param 
k_chif_ellf 
twomass_xsc 
2MASS 
K % chifraction for elliptical fit to 3sig isophote. 
real 
4 


stat.fit.param 
k_cmsig 
twomass_psc 
2MASS 
Corrected photometric uncertainty for the default Ksband magnitude. 
real 
4 
mag 
Ksband 
phot.flux 
k_con_indx 
twomass_xsc 
2MASS 
K concentration index r_75%/r_25%. 
real 
4 


phys.size;arith.ratio 
k_d_area 
twomass_xsc 
2MASS 
K 5sigma to 3sigma differential area. 
smallint 
2 


stat.fit.residual 
k_flg_10 
twomass_xsc 
2MASS 
K confusion flag for 10 arcsec circular ap. mag. 
smallint 
2 


meta.code 
k_flg_15 
twomass_xsc 
2MASS 
K confusion flag for 15 arcsec circular ap. mag. 
smallint 
2 


meta.code 
k_flg_20 
twomass_xsc 
2MASS 
K confusion flag for 20 arcsec circular ap. mag. 
smallint 
2 


meta.code 
k_flg_25 
twomass_xsc 
2MASS 
K confusion flag for 25 arcsec circular ap. mag. 
smallint 
2 


meta.code 
k_flg_30 
twomass_xsc 
2MASS 
K confusion flag for 30 arcsec circular ap. mag. 
smallint 
2 


meta.code 
k_flg_40 
twomass_xsc 
2MASS 
K confusion flag for 40 arcsec circular ap. mag. 
smallint 
2 


meta.code 
k_flg_5 
twomass_xsc 
2MASS 
K confusion flag for 5 arcsec circular ap. mag. 
smallint 
2 


meta.code 
k_flg_50 
twomass_xsc 
2MASS 
K confusion flag for 50 arcsec circular ap. mag. 
smallint 
2 


meta.code 
k_flg_60 
twomass_xsc 
2MASS 
K confusion flag for 60 arcsec circular ap. mag. 
smallint 
2 


meta.code 
k_flg_7 
twomass_sixx2_xsc 
2MASS 
K confusion flag for 7 arcsec circular ap. mag 
smallint 
2 



k_flg_7 
twomass_xsc 
2MASS 
K confusion flag for 7 arcsec circular ap. mag. 
smallint 
2 


meta.code 
k_flg_70 
twomass_xsc 
2MASS 
K confusion flag for 70 arcsec circular ap. mag. 
smallint 
2 


meta.code 
k_flg_c 
twomass_xsc 
2MASS 
K confusion flag for Kron circular mag. 
smallint 
2 


meta.code 
k_flg_e 
twomass_xsc 
2MASS 
K confusion flag for Kron elliptical mag. 
smallint 
2 


meta.code 
k_flg_fc 
twomass_xsc 
2MASS 
K confusion flag for fiducial Kron circ. mag. 
smallint 
2 


meta.code 
k_flg_fe 
twomass_xsc 
2MASS 
K confusion flag for fiducial Kron ell. mag. 
smallint 
2 


meta.code 
k_flg_i20c 
twomass_xsc 
2MASS 
K confusion flag for 20mag/sq." iso. circ. mag. 
smallint 
2 


meta.code 
k_flg_i20e 
twomass_xsc 
2MASS 
K confusion flag for 20mag/sq." iso. ell. mag. 
smallint 
2 


meta.code 
k_flg_i21c 
twomass_xsc 
2MASS 
K confusion flag for 21mag/sq." iso. circ. mag. 
smallint 
2 


meta.code 
k_flg_i21e 
twomass_xsc 
2MASS 
K confusion flag for 21mag/sq." iso. ell. mag. 
smallint 
2 


meta.code 
k_flg_j21fc 
twomass_xsc 
2MASS 
K confusion flag for 21mag/sq." iso. fid. circ. mag. 
smallint 
2 


meta.code 
k_flg_j21fe 
twomass_xsc 
2MASS 
K confusion flag for 21mag/sq." iso. fid. ell. mag. 
smallint 
2 


meta.code 
k_flg_k20fc 
twomass_xsc 
2MASS 
K confusion flag for 20mag/sq." iso. fid. circ. mag. 
smallint 
2 


meta.code 
k_flg_k20fe 
twomass_sixx2_xsc 
2MASS 
K confusion flag for 20mag/sq.″ iso. fid. ell. mag 
smallint 
2 



k_flg_k20fe 
twomass_xsc 
2MASS 
K confusion flag for 20mag/sq." iso. fid. ell. mag. 
smallint 
2 


meta.code 
k_m 
twomass_psc 
2MASS 
Default Ksband magnitude 
real 
4 
mag 

phot.flux 
k_m 
twomass_sixx2_psc 
2MASS 
K selected "default" magnitude 
real 
4 
mag 


k_m_10 
twomass_xsc 
2MASS 
K 10 arcsec radius circular aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_15 
twomass_xsc 
2MASS 
K 15 arcsec radius circular aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_20 
twomass_xsc 
2MASS 
K 20 arcsec radius circular aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_25 
twomass_xsc 
2MASS 
K 25 arcsec radius circular aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_2mass 
allwise_sc 
WISE 
2MASS K_{s}band magnitude of the associated 2MASS PSC source. This column is "null" if there is no associated 2MASS PSC source or if the 2MASS PSC K_{s}band magnitude entry is "null". 
float 
8 
mag 


k_m_2mass 
wise_allskysc 
WISE 
2MASS Ksband magnitude or magnitude upper limit of the associated 2MASS PSC source. This column is default if there is no associated 2MASS PSC source or if the 2MASS PSC Ksband magnitude entry is default. 
real 
4 
mag 
0.9999995e9 

k_m_2mass 
wise_prelimsc 
WISE 
2MASS Ksband magnitude or magnitude upper limit of the associated 2MASS PSC source This column is default if there is no associated 2MASS PSC source or if the 2MASS PSC Ksband magnitude entry is default 
real 
4 
mag 
0.9999995e9 

k_m_30 
twomass_xsc 
2MASS 
K 30 arcsec radius circular aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_40 
twomass_xsc 
2MASS 
K 40 arcsec radius circular aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_5 
twomass_xsc 
2MASS 
K 5 arcsec radius circular aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_50 
twomass_xsc 
2MASS 
K 50 arcsec radius circular aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_60 
twomass_xsc 
2MASS 
K 60 arcsec radius circular aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_7 
twomass_sixx2_xsc 
2MASS 
K 7 arcsec radius circular aperture magnitude 
real 
4 
mag 


k_m_7 
twomass_xsc 
2MASS 
K 7 arcsec radius circular aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_70 
twomass_xsc 
2MASS 
K 70 arcsec radius circular aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_c 
twomass_xsc 
2MASS 
K Kron circular aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_e 
twomass_xsc 
2MASS 
K Kron elliptical aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_ext 
twomass_sixx2_xsc 
2MASS 
K mag from fit extrapolation 
real 
4 
mag 


k_m_ext 
twomass_xsc 
2MASS 
K mag from fit extrapolation. 
real 
4 
mag 

phot.flux 
k_m_fc 
twomass_xsc 
2MASS 
K fiducial Kron circular magnitude. 
real 
4 
mag 

phot.flux 
k_m_fe 
twomass_xsc 
2MASS 
K fiducial Kron ell. mag aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_i20c 
twomass_xsc 
2MASS 
K 20mag/sq." isophotal circular ap. magnitude. 
real 
4 
mag 

phot.flux 
k_m_i20e 
twomass_xsc 
2MASS 
K 20mag/sq." isophotal elliptical ap. magnitude. 
real 
4 
mag 

phot.flux 
k_m_i21c 
twomass_xsc 
2MASS 
K 21mag/sq." isophotal circular ap. magnitude. 
real 
4 
mag 

phot.flux 
k_m_i21e 
twomass_xsc 
2MASS 
K 21mag/sq." isophotal elliptical ap. magnitude. 
real 
4 
mag 

phot.flux 
k_m_j21fc 
twomass_xsc 
2MASS 
K 21mag/sq." isophotal fiducial circ. ap. mag. 
real 
4 
mag 

phot.flux 
k_m_j21fe 
twomass_xsc 
2MASS 
K 21mag/sq." isophotal fiducial ell. ap. magnitude. 
real 
4 
mag 

phot.flux 
k_m_k20fc 
twomass_xsc 
2MASS 
K 20mag/sq." isophotal fiducial circ. ap. mag. 
real 
4 
mag 

phot.flux 
K_M_K20FE 
twomass 
SIXDF 
K 20mag/sq." isophotal fiducial ell. ap. magnitude 
real 
4 
mag 


k_m_k20fe 
twomass_sixx2_xsc 
2MASS 
K 20mag/sq.″ isophotal fiducial ell. ap. magnitude 
real 
4 
mag 


k_m_k20fe 
twomass_xsc 
2MASS 
K 20mag/sq." isophotal fiducial ell. ap. magnitude. 
real 
4 
mag 

phot.flux 
k_m_stdap 
twomass_psc 
2MASS 
Ksband "standard" aperture magnitude. 
real 
4 
mag 

phot.flux 
k_m_sys 
twomass_xsc 
2MASS 
K system photometry magnitude. 
real 
4 
mag 

phot.flux 
k_mnsurfb_eff 
twomass_xsc 
2MASS 
K mean surface brightness at the halflight radius. 
real 
4 
mag 

phot.mag.sb 
k_msig 
twomass_sixx2_psc 
2MASS 
K "default" mag uncertainty 
real 
4 
mag 


k_msig_10 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 10 arcsec circular ap. mag. 
real 
4 
mag 

stat.error 
k_msig_15 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 15 arcsec circular ap. mag. 
real 
4 
mag 

stat.error 
k_msig_20 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 20 arcsec circular ap. mag. 
real 
4 
mag 

stat.error 
k_msig_25 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 25 arcsec circular ap. mag. 
real 
4 
mag 

stat.error 
k_msig_2mass 
allwise_sc 
WISE 
2MASS K_{s}band corrected photometric uncertainty of the associated 2MASS PSC source. This column is "null" if there is no associated 2MASS PSC source or if the 2MASS PSC K_{s}band uncertainty entry is "null". 
float 
8 
mag 


k_msig_2mass 
wise_allskysc 
WISE 
2MASS Ksband corrected photometric uncertainty of the associated 2MASS PSC source. This column is default if there is no associated 2MASS PSC source or if the 2MASS PSC Ksband uncertainty entry is default. 
real 
4 
mag 
0.9999995e9 

k_msig_2mass 
wise_prelimsc 
WISE 
2MASS Ksband corrected photometric uncertainty of the associated 2MASS PSC source This column is default if there is no associated 2MASS PSC source or if the 2MASS PSC Ksband uncertainty entry is default 
real 
4 
mag 
0.9999995e9 

k_msig_30 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 30 arcsec circular ap. mag. 
real 
4 
mag 

stat.error 
k_msig_40 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 40 arcsec circular ap. mag. 
real 
4 
mag 

stat.error 
k_msig_5 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 5 arcsec circular ap. mag. 
real 
4 
mag 

stat.error 
k_msig_50 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 50 arcsec circular ap. mag. 
real 
4 
mag 

stat.error 
k_msig_60 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 60 arcsec circular ap. mag. 
real 
4 
mag 

stat.error 
k_msig_7 
twomass_sixx2_xsc 
2MASS 
K 1sigma uncertainty in 7 arcsec circular ap. mag 
real 
4 
mag 


k_msig_7 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 7 arcsec circular ap. mag. 
real 
4 
mag 

stat.error 
k_msig_70 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 70 arcsec circular ap. mag. 
real 
4 
mag 

stat.error 
k_msig_c 
twomass_xsc 
2MASS 
K 1sigma uncertainty in Kron circular mag. 
real 
4 
mag 

stat.error 
k_msig_e 
twomass_xsc 
2MASS 
K 1sigma uncertainty in Kron elliptical mag. 
real 
4 
mag 

stat.error 
k_msig_ext 
twomass_sixx2_xsc 
2MASS 
K 1sigma uncertainty in mag from fit extrapolation 
real 
4 
mag 


k_msig_ext 
twomass_xsc 
2MASS 
K 1sigma uncertainty in mag from fit extrapolation. 
real 
4 
mag 

stat.error 
k_msig_fc 
twomass_xsc 
2MASS 
K 1sigma uncertainty in fiducial Kron circ. mag. 
real 
4 
mag 

stat.error 
k_msig_fe 
twomass_xsc 
2MASS 
K 1sigma uncertainty in fiducial Kron ell. mag. 
real 
4 
mag 

stat.error 
k_msig_i20c 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 20mag/sq." iso. circ. mag. 
real 
4 
mag 

stat.error 
k_msig_i20e 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 20mag/sq." iso. ell. mag. 
real 
4 
mag 

stat.error 
k_msig_i21c 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 21mag/sq." iso. circ. mag. 
real 
4 
mag 

stat.error 
k_msig_i21e 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 21mag/sq." iso. ell. mag. 
real 
4 
mag 

stat.error 
k_msig_j21fc 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 21mag/sq." iso.fid.circ.mag. 
real 
4 
mag 

stat.error 
k_msig_j21fe 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 21mag/sq." iso.fid.ell.mag. 
real 
4 
mag 

stat.error 
k_msig_k20fc 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 20mag/sq." iso.fid.circ. mag. 
real 
4 
mag 

stat.error 
k_msig_k20fe 
twomass_sixx2_xsc 
2MASS 
K 1sigma uncertainty in 20mag/sq.″ iso.fid.ell.mag 
real 
4 
mag 


k_msig_k20fe 
twomass_xsc 
2MASS 
K 1sigma uncertainty in 20mag/sq." iso.fid.ell.mag. 
real 
4 
mag 

stat.error 
k_msig_stdap 
twomass_psc 
2MASS 
Uncertainty in the Ksband standard aperture magnitude. 
real 
4 
mag 

phot.flux 
k_msig_sys 
twomass_xsc 
2MASS 
K 1sigma uncertainty in system photometry mag. 
real 
4 
mag 

stat.error 
k_msigcom 
twomass_psc 
2MASS 
Combined, or total photometric uncertainty for the default Ksband magnitude. 
real 
4 
mag 
Ksband 
phot.flux 
k_msigcom 
twomass_sixx2_psc 
2MASS 
combined (total) K band photometric uncertainty 
real 
4 
mag 


k_msnr10 
twomass_scn 
2MASS 
The estimated Ksband magnitude at which SNR=10 is achieved for this scan. 
real 
4 
mag 

phot.flux 
k_msnr10 
twomass_sixx2_scn 
2MASS 
K mag at which SNR=10 is achieved, from k_psp and k_zp_ap 
real 
4 
mag 


k_n_snr10 
twomass_scn 
2MASS 
Number of point sources at Ksband with SNR>10 (instrumental mag <=14.3) 
int 
4 


meta.number 
k_n_snr10 
twomass_sixx2_scn 
2MASS 
number of K point sources with SNR>10 (instrumental m<=14.3) 
int 
4 



k_pchi 
twomass_xsc 
2MASS 
K chi^2 of fit to rad. profile (LCSB: alpha scale len). 
real 
4 


stat.fit.param 
k_peak 
twomass_xsc 
2MASS 
K peak pixel brightness. 
real 
4 
mag 

phot.mag.sb 
k_perc_darea 
twomass_xsc 
2MASS 
K 5sigma to 3sigma percent area change. 
smallint 
2 


FIT_PARAM 
k_phi 
twomass_sixx2_xsc 
2MASS 
K angle to 3sigma major axis (E of N) 
smallint 
2 
deg 


k_phi 
twomass_xsc 
2MASS 
K angle to 3sigma major axis (E of N). 
smallint 
2 
degrees 

pos.posAng 
k_psfchi 
twomass_psc 
2MASS 
Reduced chisquared goodnessoffit value for the Ksband profilefit photometry made on the 1.3 s "Read_2" exposures. 
real 
4 


stat.fit.param 
k_psp 
twomass_scn 
2MASS 
Ksband photometric sensitivity paramater (PSP). 
real 
4 


instr.sensitivity 
k_psp 
twomass_sixx2_scn 
2MASS 
K photometric sensitivity param: k_shape_avg*(k_fbg_avg^.29) 
real 
4 



k_pts_noise 
twomass_scn 
2MASS 
Base10 logarithm of the mode of the noise distribution for all point source detections in the scan, where the noise is estimated from the measured Ksband photometric errors and is expressed in units of mJy. 
real 
4 


instr.det.noise 
k_pts_noise 
twomass_sixx2_scn 
2MASS 
log10 of K band modal point src noise estimate 
real 
4 
logmJy 


k_r_c 
twomass_xsc 
2MASS 
K Kron circular aperture radius. 
real 
4 
arcsec 

phys.angSize;src 
k_r_e 
twomass_xsc 
2MASS 
K Kron elliptical aperture semimajor axis. 
real 
4 
arcsec 

phys.angSize;src 
k_r_eff 
twomass_xsc 
2MASS 
K halflight (integrated halfflux point) radius. 
real 
4 
arcsec 

phys.angSize;src 
k_r_i20c 
twomass_xsc 
2MASS 
K 20mag/sq." isophotal circular aperture radius. 
real 
4 
arcsec 

phys.angSize;src 
k_r_i20e 
twomass_xsc 
2MASS 
K 20mag/sq." isophotal elliptical ap. semimajor axis. 
real 
4 
arcsec 

phys.angSize;src 
k_r_i21c 
twomass_xsc 
2MASS 
K 21mag/sq." isophotal circular aperture radius. 
real 
4 
arcsec 

phys.angSize;src 
k_r_i21e 
twomass_xsc 
2MASS 
K 21mag/sq." isophotal elliptical ap. semimajor axis. 
real 
4 
arcsec 

phys.angSize;src 
k_resid_ann 
twomass_xsc 
2MASS 
K residual annulus background median. 
real 
4 
DN 

meta.code 
k_sc_1mm 
twomass_xsc 
2MASS 
K 1st moment (score) (LCSB: super blk 2,4,8 SNR). 
real 
4 


meta.code 
k_sc_2mm 
twomass_xsc 
2MASS 
K 2nd moment (score) (LCSB: SNRMAX  super SNR max). 
real 
4 


meta.code 
k_sc_msh 
twomass_xsc 
2MASS 
K median shape score. 
real 
4 


meta.code 
k_sc_mxdn 
twomass_xsc 
2MASS 
K mxdn (score) (LCSB: BSNR  block/smoothed SNR). 
real 
4 


meta.code 
k_sc_r1 
twomass_xsc 
2MASS 
K r1 (score). 
real 
4 


meta.code 
k_sc_r23 
twomass_xsc 
2MASS 
K r23 (score) (LCSB: TSNR  integrated SNR for r=15). 
real 
4 


meta.code 
k_sc_sh 
twomass_xsc 
2MASS 
K shape (score). 
real 
4 


meta.code 
k_sc_vint 
twomass_xsc 
2MASS 
K vint (score). 
real 
4 


meta.code 
k_sc_wsh 
twomass_xsc 
2MASS 
K wsh (score) (LCSB: PSNR  peak raw SNR). 
real 
4 


meta.code 
k_seetrack 
twomass_xsc 
2MASS 
K band seetracking score. 
real 
4 


meta.code 
k_sh0 
twomass_xsc 
2MASS 
K ridge shape (LCSB: BSNR limit). 
real 
4 


FIT_PARAM 
k_shape_avg 
twomass_scn 
2MASS 
Ksband average seeing shape for scan. 
real 
4 


instr.obsty.seeing 
k_shape_avg 
twomass_sixx2_scn 
2MASS 
K band average seeing shape for scan 
real 
4 



k_shape_rms 
twomass_scn 
2MASS 
RMSerror of Ksband average seeing shape. 
real 
4 


instr.obsty.seeing 
k_shape_rms 
twomass_sixx2_scn 
2MASS 
rms of K band avg seeing shape for scan 
real 
4 



k_sig_sh0 
twomass_xsc 
2MASS 
K ridge shape sigma (LCSB: B2SNR limit). 
real 
4 


FIT_PARAM 
k_snr 
twomass_psc 
2MASS 
Ksband "scan" signaltonoise ratio. 
real 
4 
mag 

instr.det.noise 
k_snr 
twomass_sixx2_psc 
2MASS 
K band "scan" signaltonoise ratio 
real 
4 



k_subst2 
twomass_xsc 
2MASS 
K residual background #2 (score). 
real 
4 


meta.code 
k_zp_ap 
twomass_scn 
2MASS 
Photometric zeropoint for Ksband aperture photometry. 
real 
4 
mag 

phot.mag;arith.zp 
k_zp_ap 
twomass_sixx2_scn 
2MASS 
K band ap. calibration photometric zeropoint for scan 
real 
4 
mag 


k_zperr_ap 
twomass_scn 
2MASS 
RMSerror of zeropoint for Ksband aperture photometry 
real 
4 
mag 

stat.error 
k_zperr_ap 
twomass_sixx2_scn 
2MASS 
K band ap. calibration rms error of zeropoint for scan 
real 
4 
mag 


KBESTR 
spectra 
SIXDF 
crosscorrelation template 
int 
4 



KEXT 
twomass 
SIXDF 
KEXT magnitude 
real 
4 
mag 


KEXT_K 
twomass 
SIXDF 
KEXT minus K (corrected) 
real 
4 
mag 


Kmag 
mcps_lmcSource, mcps_smcSource 
MCPS 
The K' band magnitude (from 2MASS) (0.00 if star not detected.) 
real 
4 
mag 


kMag 
ukirtFSstars 
SVNGC253v20100429 
K band total magnitude on the MKO(UFTI) system 
real 
4 
mag 

phot.mag 
kMag 
ukirtFSstars 
SVORIONv20100429 
K band total magnitude on the MKO(UFTI) system 
real 
4 
mag 

phot.mag 
kMag 
ukirtFSstars 
ULTRAVISTAv20100429 
K band total magnitude on the MKO(UFTI) system 
real 
4 
mag 

phot.mag 
kMag 
ukirtFSstars 
VIDEOv20100513 
K band total magnitude on the MKO(UFTI) system 
real 
4 
mag 

phot.mag 
kMag 
ukirtFSstars 
VIKINGv20110714 
K band total magnitude on the MKO(UFTI) system 
real 
4 
mag 

phot.mag 
kMag 
ukirtFSstars 
VVVv20100531 
K band total magnitude on the MKO(UFTI) system 
real 
4 
mag 

phot.mag 
Kmag2MASS 
spitzer_smcSource 
SPITZER 
The 2MASS K band magnitude. 
real 
4 
mag 


kMagErr 
ukirtFSstars 
SVNGC253v20100429 
K band magnitude error 
real 
4 
mag 

stat.error 
kMagErr 
ukirtFSstars 
SVORIONv20100429 
K band magnitude error 
real 
4 
mag 

stat.error 
kMagErr 
ukirtFSstars 
ULTRAVISTAv20100429 
K band magnitude error 
real 
4 
mag 

stat.error 
kMagErr 
ukirtFSstars 
VIDEOv20100513 
K band magnitude error 
real 
4 
mag 

stat.error 
kMagErr 
ukirtFSstars 
VIKINGv20110714 
K band magnitude error 
real 
4 
mag 

stat.error 
kMagErr 
ukirtFSstars 
VVVv20100531 
K band magnitude error 
real 
4 
mag 

stat.error 
kronFlux 
svNgc253Detection 
SVNGC253v20100429 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
svOrionDetection 
SVORIONv20100429 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
ultravistaDetection 
ULTRAVISTAv20100429 
flux within Kron radius circular aperture (SE: FLUX_AUTO) {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
vhsDetection 
VHSDR1 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
vhsDetection 
VHSDR2 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
vhsDetection 
VHSDR3 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vhsDetection 
VHSv20120926 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vhsDetection 
VHSv20130417 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vhsDetection 
VHSv20140409 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vhsDetection 
VHSv20150108 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
videoDetection 
VIDEODR2 
flux within Kron radius circular aperture (SE: FLUX_AUTO) {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
videoDetection 
VIDEODR3 
flux within Kron radius circular aperture (SE: FLUX_AUTO) {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
videoDetection 
VIDEODR4 
flux within Kron radius circular aperture (SE: FLUX_AUTO) {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
videoDetection 
VIDEOv20100513 
flux within Kron radius circular aperture (SE: FLUX_AUTO) {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
videoDetection 
VIDEOv20111208 
flux within Kron radius circular aperture (SE: FLUX_AUTO) {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
vikingDetection 
VIKINGDR2 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
vikingDetection 
VIKINGDR3 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vikingDetection 
VIKINGDR4 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vikingDetection 
VIKINGv20110714 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
vikingDetection 
VIKINGv20111019 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
vikingDetection 
VIKINGv20130417 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vikingDetection 
VIKINGv20140402 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vikingDetection 
VIKINGv20150421 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vmcDetection 
VMCDR1 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
vmcDetection 
VMCDR2 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vmcDetection 
VMCDR3 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vmcDetection 
VMCv20110816 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
vmcDetection 
VMCv20110909 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
vmcDetection 
VMCv20120126 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
vmcDetection 
VMCv20121128 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vmcDetection 
VMCv20130304 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vmcDetection 
VMCv20130805 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vmcDetection 
VMCv20140428 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vmcDetection 
VMCv20140903 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vmcDetection 
VMCv20150309 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vvvDetection 
VVVDR1 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vvvDetection 
VVVDR2 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count 
kronFlux 
vvvDetection, vvvListRemeasurement 
VVVv20100531 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFlux 
vvvListRemeasurement 
VVVv20110718 
flux within circular aperture to k × r_k ; k = 2 {catalogue TType keyword: Kron_flux} 
real 
4 
ADU 

phot.count;em.opt 
kronFluxErr 
svNgc253Detection 
SVNGC253v20100429 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
svOrionDetection 
SVORIONv20100429 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
ultravistaDetection 
ULTRAVISTAv20100429 
error on Kron flux (SE: FLUXERR_AUTO) {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vhsDetection 
VHSDR1 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vhsDetection 
VHSDR2 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vhsDetection 
VHSDR3 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vhsDetection 
VHSv20120926 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vhsDetection 
VHSv20130417 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vhsDetection 
VHSv20140409 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vhsDetection 
VHSv20150108 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
videoDetection 
VIDEODR2 
error on Kron flux (SE: FLUXERR_AUTO) {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
videoDetection 
VIDEODR3 
error on Kron flux (SE: FLUXERR_AUTO) {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
videoDetection 
VIDEODR4 
error on Kron flux (SE: FLUXERR_AUTO) {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
videoDetection 
VIDEOv20100513 
error on Kron flux (SE: FLUXERR_AUTO) {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
videoDetection 
VIDEOv20111208 
error on Kron flux (SE: FLUXERR_AUTO) {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vikingDetection 
VIKINGDR2 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vikingDetection 
VIKINGDR3 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vikingDetection 
VIKINGDR4 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vikingDetection 
VIKINGv20110714 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vikingDetection 
VIKINGv20111019 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vikingDetection 
VIKINGv20130417 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vikingDetection 
VIKINGv20140402 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vikingDetection 
VIKINGv20150421 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vmcDetection 
VMCDR1 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vmcDetection 
VMCDR2 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vmcDetection 
VMCDR3 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vmcDetection 
VMCv20110816 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vmcDetection 
VMCv20110909 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vmcDetection 
VMCv20120126 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vmcDetection 
VMCv20121128 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vmcDetection 
VMCv20130304 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vmcDetection 
VMCv20130805 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vmcDetection 
VMCv20140428 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vmcDetection 
VMCv20140903 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vmcDetection 
VMCv20150309 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vvvDetection 
VVVDR1 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vvvDetection 
VVVDR2 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vvvDetection, vvvListRemeasurement 
VVVv20100531 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronFluxErr 
vvvListRemeasurement 
VVVv20110718 
error on Kron flux {catalogue TType keyword: Kron_flux_err} 
real 
4 
ADU 

stat.error 
kronMag 
svNgc253Detection 
SVNGC253v20100429 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
svOrionDetection 
SVORIONv20100429 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
ultravistaDetection 
ULTRAVISTAv20100429 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vhsDetection 
VHSDR1 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vhsDetection 
VHSDR2 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vhsDetection 
VHSDR3 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vhsDetection 
VHSv20120926 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vhsDetection 
VHSv20130417 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vhsDetection 
VHSv20140409 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vhsDetection 
VHSv20150108 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
videoDetection 
VIDEODR2 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
videoDetection 
VIDEODR3 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
videoDetection 
VIDEODR4 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
videoDetection 
VIDEOv20100513 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
videoDetection 
VIDEOv20111208 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vikingDetection 
VIKINGDR2 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vikingDetection 
VIKINGDR3 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vikingDetection 
VIKINGDR4 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vikingDetection 
VIKINGv20110714 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vikingDetection 
VIKINGv20111019 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vikingDetection 
VIKINGv20130417 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vikingDetection 
VIKINGv20140402 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vikingDetection 
VIKINGv20150421 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vmcDetection 
VMCDR1 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vmcDetection 
VMCDR2 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vmcDetection 
VMCDR3 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vmcDetection 
VMCv20110816 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vmcDetection 
VMCv20110909 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vmcDetection 
VMCv20120126 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vmcDetection 
VMCv20121128 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vmcDetection 
VMCv20130304 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vmcDetection 
VMCv20130805 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vmcDetection 
VMCv20140428 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vmcDetection 
VMCv20140903 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vmcDetection 
VMCv20150309 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vvvDetection 
VVVDR1 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vvvDetection 
VVVDR2 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vvvDetection, vvvListRemeasurement 
VVVv20100531 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMag 
vvvListRemeasurement 
VVVv20110718 
Calibrated Kron magnitude within circular aperture r_k 
real 
4 
mag 

phot.mag 
kronMagErr 
svNgc253Detection 
SVNGC253v20100429 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
svOrionDetection 
SVORIONv20100429 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
ultravistaDetection 
ULTRAVISTAv20100429 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vhsDetection 
VHSDR1 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vhsDetection 
VHSDR2 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vhsDetection 
VHSDR3 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vhsDetection 
VHSv20120926 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vhsDetection 
VHSv20130417 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vhsDetection 
VHSv20140409 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vhsDetection 
VHSv20150108 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error;phot.mag 
kronMagErr 
videoDetection 
VIDEODR2 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
videoDetection 
VIDEODR3 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
videoDetection 
VIDEODR4 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error;phot.mag 
kronMagErr 
videoDetection 
VIDEOv20100513 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
videoDetection 
VIDEOv20111208 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vikingDetection 
VIKINGDR2 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vikingDetection 
VIKINGDR3 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vikingDetection 
VIKINGDR4 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vikingDetection 
VIKINGv20110714 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vikingDetection 
VIKINGv20111019 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vikingDetection 
VIKINGv20130417 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vikingDetection 
VIKINGv20140402 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vikingDetection 
VIKINGv20150421 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error;phot.mag 
kronMagErr 
vmcDetection 
VMCDR1 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vmcDetection 
VMCDR2 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vmcDetection 
VMCDR3 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error;phot.mag 
kronMagErr 
vmcDetection 
VMCv20110816 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vmcDetection 
VMCv20110909 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vmcDetection 
VMCv20120126 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vmcDetection 
VMCv20121128 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vmcDetection 
VMCv20130304 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vmcDetection 
VMCv20130805 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vmcDetection 
VMCv20140428 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vmcDetection 
VMCv20140903 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error;phot.mag 
kronMagErr 
vmcDetection 
VMCv20150309 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error;phot.mag 
kronMagErr 
vvvDetection 
VVVDR1 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vvvDetection 
VVVDR2 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vvvDetection, vvvListRemeasurement 
VVVv20100531 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronMagErr 
vvvListRemeasurement 
VVVv20110718 
error on calibrated Kron magnitude 
real 
4 
mag 

stat.error 
kronRad 
svNgc253Detection 
SVNGC253v20100429 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
kronRad 
svOrionDetection 
SVORIONv20100429 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
kronRad 
ultravistaDetection 
ULTRAVISTAv20100429 
Kron radius as defined in SE by Graham and Driver (2005) (SE: KRON_RADIUS*A_IMAGE) {catalogue TType keyword: Kron_radius} r_k = ∑R² I(R) / ∑R I(R) 
real 
4 
pixels 

phys.angSize;src 
Since <FLUX>_RADIUS is expressed in multiples of the major axis, <FLUX>_RADIUS is multiplied by A_IMAGE to convert to pixels. 
kronRad 
vhsDetection 
VHSDR1 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
kronRad 
vhsDetection 
VHSDR2 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
kronRad 
vhsDetection 
VHSDR3 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vhsDetection 
VHSv20120926 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vhsDetection 
VHSv20130417 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vhsDetection 
VHSv20140409 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vhsDetection 
VHSv20150108 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
videoDetection 
VIDEODR2 
Kron radius as defined in SE by Graham and Driver (2005) (SE: KRON_RADIUS*A_IMAGE) {catalogue TType keyword: Kron_radius} r_k = ∑R² I(R) / ∑R I(R) 
real 
4 
pixels 

phys.angSize;src 
Since <FLUX>_RADIUS is expressed in multiples of the major axis, <FLUX>_RADIUS is multiplied by A_IMAGE to convert to pixels. 
kronRad 
videoDetection 
VIDEODR3 
Kron radius as defined in SE by Graham and Driver (2005) (SE: KRON_RADIUS*A_IMAGE) {catalogue TType keyword: Kron_radius} r_k = ∑R² I(R) / ∑R I(R) 
real 
4 
pixels 

phys.angSize 
Since <FLUX>_RADIUS is expressed in multiples of the major axis, <FLUX>_RADIUS is multiplied by A_IMAGE to convert to pixels. 
kronRad 
videoDetection 
VIDEODR4 
Kron radius as defined in SE by Graham and Driver (2005) (SE: KRON_RADIUS*A_IMAGE) {catalogue TType keyword: Kron_radius} r_k = ∑R² I(R) / ∑R I(R) 
real 
4 
pixels 

phys.angSize 
Since <FLUX>_RADIUS is expressed in multiples of the major axis, <FLUX>_RADIUS is multiplied by A_IMAGE to convert to pixels. 
kronRad 
videoDetection 
VIDEOv20100513 
Kron radius as defined in SE by Graham and Driver (2005) (SE: KRON_RADIUS*A_IMAGE) {catalogue TType keyword: Kron_radius} r_k = ∑R² I(R) / ∑R I(R) 
real 
4 
pixels 

phys.angSize;src 
Since <FLUX>_RADIUS is expressed in multiples of the major axis, <FLUX>_RADIUS is multiplied by A_IMAGE to convert to pixels. 
kronRad 
videoDetection 
VIDEOv20111208 
Kron radius as defined in SE by Graham and Driver (2005) (SE: KRON_RADIUS*A_IMAGE) {catalogue TType keyword: Kron_radius} r_k = ∑R² I(R) / ∑R I(R) 
real 
4 
pixels 

phys.angSize;src 
Since <FLUX>_RADIUS is expressed in multiples of the major axis, <FLUX>_RADIUS is multiplied by A_IMAGE to convert to pixels. 
kronRad 
vikingDetection 
VIKINGDR2 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
kronRad 
vikingDetection 
VIKINGDR3 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vikingDetection 
VIKINGDR4 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vikingDetection 
VIKINGv20110714 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
kronRad 
vikingDetection 
VIKINGv20111019 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
kronRad 
vikingDetection 
VIKINGv20130417 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vikingDetection 
VIKINGv20140402 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vikingDetection 
VIKINGv20150421 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vmcDetection 
VMCDR1 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
kronRad 
vmcDetection 
VMCDR2 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vmcDetection 
VMCDR3 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vmcDetection 
VMCv20110816 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
kronRad 
vmcDetection 
VMCv20110909 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
kronRad 
vmcDetection 
VMCv20120126 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
kronRad 
vmcDetection 
VMCv20121128 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vmcDetection 
VMCv20130304 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vmcDetection 
VMCv20130805 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vmcDetection 
VMCv20140428 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vmcDetection 
VMCv20140903 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vmcDetection 
VMCv20150309 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vvvDetection 
VVVDR1 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vvvDetection 
VVVDR2 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize 
kronRad 
vvvDetection, vvvListRemeasurement 
VVVv20100531 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
kronRad 
vvvListRemeasurement 
VVVv20110718 
r_k as defined in Bertin and Arnouts 1996 A&A Supp 117 393 {catalogue TType keyword: Kron_radius} 
real 
4 
pixels 

phys.angSize;src 
ksAmpl 
vmcCepheidVariables 
VMCDR3 
Amplitude of Ks band magnitude variation {catalogue TType keyword: A(Ks)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.K 
ksAmpl 
vmcCepheidVariables 
VMCv20121128 
Amplitude of Ks band magnitude variation {catalogue TType keyword: A(Ks)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.NIR 
ksAmpl 
vmcCepheidVariables 
VMCv20140428 
Amplitude of Ks band magnitude variation {catalogue TType keyword: A(Ks)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.K 
ksAmpl 
vmcCepheidVariables 
VMCv20140903 
Amplitude of Ks band magnitude variation {catalogue TType keyword: A(Ks)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.K 
ksAmpl 
vmcCepheidVariables 
VMCv20150309 
Amplitude of Ks band magnitude variation {catalogue TType keyword: A(Ks)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.K 
ksAperMag1 
vmcSynopticSource 
VMCDR1 
Extended source Ks aperture corrected mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag1 
vmcSynopticSource 
VMCDR2 
Extended source Ks aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag1 
vmcSynopticSource 
VMCDR3 
Extended source Ks aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag1 
vmcSynopticSource 
VMCv20110816 
Extended source Ks aperture corrected mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag1 
vmcSynopticSource 
VMCv20110909 
Extended source Ks aperture corrected mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag1 
vmcSynopticSource 
VMCv20120126 
Extended source Ks aperture corrected mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag1 
vmcSynopticSource 
VMCv20121128 
Extended source Ks aperture corrected mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag1 
vmcSynopticSource 
VMCv20130304 
Extended source Ks aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag1 
vmcSynopticSource 
VMCv20130805 
Extended source Ks aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag1 
vmcSynopticSource 
VMCv20140428 
Extended source Ks aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag1 
vmcSynopticSource 
VMCv20140903 
Extended source Ks aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag1 
vmcSynopticSource 
VMCv20150309 
Extended source Ks aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag1 
vvvSource 
VVVDR1 
Extended source Ks aperture corrected mag (0.7 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag1 
vvvSource 
VVVv20100531 
Extended source Ks aperture corrected mag (0.7 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag1 
vvvSource 
VVVv20110718 
Extended source Ks aperture corrected mag (0.7 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag1 
vvvSource, vvvSynopticSource 
VVVDR2 
Extended source Ks aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag1Err 
vmcSynopticSource 
VMCDR1 
Error in extended source Ks mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag1Err 
vmcSynopticSource 
VMCDR2 
Error in extended source Ks mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag1Err 
vmcSynopticSource 
VMCDR3 
Error in extended source Ks mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag1Err 
vmcSynopticSource 
VMCv20110816 
Error in extended source Ks mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag1Err 
vmcSynopticSource 
VMCv20110909 
Error in extended source Ks mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag1Err 
vmcSynopticSource 
VMCv20120126 
Error in extended source Ks mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag1Err 
vmcSynopticSource 
VMCv20121128 
Error in extended source Ks mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag1Err 
vmcSynopticSource 
VMCv20130304 
Error in extended source Ks mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag1Err 
vmcSynopticSource 
VMCv20130805 
Error in extended source Ks mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag1Err 
vmcSynopticSource 
VMCv20140428 
Error in extended source Ks mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag1Err 
vmcSynopticSource 
VMCv20140903 
Error in extended source Ks mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag1Err 
vmcSynopticSource 
VMCv20150309 
Error in extended source Ks mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag1Err 
vvvSource 
VVVDR1 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag1Err 
vvvSource 
VVVv20100531 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag1Err 
vvvSource 
VVVv20110718 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag1Err 
vvvSource, vvvSynopticSource 
VVVDR2 
Error in extended source Ks mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag2 
vmcSynopticSource 
VMCDR1 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag2 
vmcSynopticSource 
VMCDR2 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag2 
vmcSynopticSource 
VMCDR3 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag2 
vmcSynopticSource 
VMCv20110816 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag2 
vmcSynopticSource 
VMCv20110909 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag2 
vmcSynopticSource 
VMCv20120126 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag2 
vmcSynopticSource 
VMCv20121128 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag2 
vmcSynopticSource 
VMCv20130304 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag2 
vmcSynopticSource 
VMCv20130805 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag2 
vmcSynopticSource 
VMCv20140428 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag2 
vmcSynopticSource 
VMCv20140903 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag2 
vmcSynopticSource 
VMCv20150309 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag2 
vvvSynopticSource 
VVVDR1 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag2 
vvvSynopticSource 
VVVDR2 
Extended source Ks aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag2Err 
vmcSynopticSource 
VMCDR1 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag2Err 
vmcSynopticSource 
VMCDR2 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag2Err 
vmcSynopticSource 
VMCDR3 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag2Err 
vmcSynopticSource 
VMCv20110816 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag2Err 
vmcSynopticSource 
VMCv20110909 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag2Err 
vmcSynopticSource 
VMCv20120126 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag2Err 
vmcSynopticSource 
VMCv20121128 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag2Err 
vmcSynopticSource 
VMCv20130304 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag2Err 
vmcSynopticSource 
VMCv20130805 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag2Err 
vmcSynopticSource 
VMCv20140428 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag2Err 
vmcSynopticSource 
VMCv20140903 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag2Err 
vmcSynopticSource 
VMCv20150309 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag2Err 
vvvSynopticSource 
VVVDR1 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag2Err 
vvvSynopticSource 
VVVDR2 
Error in extended source Ks mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3 
svNgc253Source 
SVNGC253v20100429 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
svOrionSource 
SVORIONv20100429 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
ultravistaSource 
ULTRAVISTAv20100429 
Default point/extended source Ks mag, no aperture correction applied If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vhsSource 
VHSDR1 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vhsSource 
VHSDR2 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vhsSource 
VHSDR3 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vhsSource 
VHSv20120926 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vhsSource 
VHSv20130417 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vhsSource 
VHSv20140409 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vhsSource 
VHSv20150108 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
videoSource 
VIDEODR2 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
videoSource 
VIDEODR3 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
videoSource 
VIDEODR4 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
videoSource 
VIDEOv20100513 
Default point/extended source Ks mag, no aperture correction applied If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
videoSource 
VIDEOv20111208 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vikingSource 
VIKINGDR2 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vikingSource 
VIKINGDR3 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vikingSource 
VIKINGDR4 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vikingSource 
VIKINGv20110714 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vikingSource 
VIKINGv20111019 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vikingSource 
VIKINGv20130417 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vikingSource 
VIKINGv20140402 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vikingSource 
VIKINGv20150421 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vmcSource 
VMCDR1 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vmcSource 
VMCDR2 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vmcSource 
VMCDR3 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vmcSource 
VMCv20110816 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vmcSource 
VMCv20110909 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vmcSource 
VMCv20120126 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vmcSource 
VMCv20121128 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vmcSource 
VMCv20130304 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vmcSource 
VMCv20130805 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vmcSource 
VMCv20140428 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vmcSource 
VMCv20140903 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vmcSource 
VMCv20150309 
Default point source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vmcSynopticSource 
VMCDR1 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vmcSynopticSource 
VMCDR2 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vmcSynopticSource 
VMCDR3 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vmcSynopticSource 
VMCv20110816 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vmcSynopticSource 
VMCv20110909 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vmcSynopticSource 
VMCv20120126 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vmcSynopticSource 
VMCv20121128 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vmcSynopticSource 
VMCv20130304 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vmcSynopticSource 
VMCv20130805 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vmcSynopticSource 
VMCv20140428 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vmcSynopticSource 
VMCv20140903 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vmcSynopticSource 
VMCv20150309 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vvvSource 
VVVDR1 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vvvSource 
VVVDR2 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3 
vvvSource 
VVVv20100531 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vvvSource 
VVVv20110718 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vvvSynopticSource 
VVVDR1 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag3 
vvvSynopticSource 
VVVDR2 
Default point/extended source Ks aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag3Err 
svNgc253Source 
SVNGC253v20100429 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
svOrionSource 
SVORIONv20100429 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
ultravistaSource 
ULTRAVISTAv20100429 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vhsSource 
VHSDR1 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vhsSource 
VHSDR2 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vhsSource 
VHSDR3 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag3Err 
vhsSource 
VHSv20120926 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vhsSource 
VHSv20130417 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vhsSource 
VHSv20140409 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag3Err 
vhsSource 
VHSv20150108 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag3Err 
videoSource 
VIDEODR2 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
videoSource 
VIDEODR3 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
videoSource 
VIDEODR4 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag3Err 
videoSource 
VIDEOv20100513 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
videoSource 
VIDEOv20111208 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vikingSource 
VIKINGDR2 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vikingSource 
VIKINGDR3 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vikingSource 
VIKINGDR4 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag3Err 
vikingSource 
VIKINGv20110714 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vikingSource 
VIKINGv20111019 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vikingSource 
VIKINGv20130417 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vikingSource 
VIKINGv20140402 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vikingSource 
VIKINGv20150421 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag3Err 
vmcSource 
VMCDR2 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vmcSource 
VMCDR3 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag3Err 
vmcSource 
VMCv20110816 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vmcSource 
VMCv20110909 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vmcSource 
VMCv20120126 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vmcSource 
VMCv20121128 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vmcSource 
VMCv20130304 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vmcSource 
VMCv20130805 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vmcSource 
VMCv20140428 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag3Err 
vmcSource 
VMCv20140903 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag3Err 
vmcSource 
VMCv20150309 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag3Err 
vmcSource, vmcSynopticSource 
VMCDR1 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vvvSource 
VVVDR2 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vvvSource 
VVVv20100531 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vvvSource 
VVVv20110718 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag3Err 
vvvSource, vvvSynopticSource 
VVVDR1 
Error in default point/extended source Ks mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4 
svNgc253Source 
SVNGC253v20100429 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
svOrionSource 
SVORIONv20100429 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
ultravistaSource 
ULTRAVISTAv20100429 
Extended source Ks mag, no aperture correction applied 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vhsSource 
VHSDR1 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vhsSource 
VHSDR2 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vhsSource 
VHSDR3 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vhsSource 
VHSv20120926 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vhsSource 
VHSv20130417 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vhsSource 
VHSv20140409 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vhsSource 
VHSv20150108 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
videoSource 
VIDEODR2 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
videoSource 
VIDEODR3 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
videoSource 
VIDEODR4 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
videoSource 
VIDEOv20100513 
Extended source Ks mag, no aperture correction applied 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
videoSource 
VIDEOv20111208 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vikingSource 
VIKINGDR2 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vikingSource 
VIKINGDR3 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vikingSource 
VIKINGDR4 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vikingSource 
VIKINGv20110714 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vikingSource 
VIKINGv20111019 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vikingSource 
VIKINGv20130417 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vikingSource 
VIKINGv20140402 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vikingSource 
VIKINGv20150421 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vmcSource 
VMCDR1 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vmcSource 
VMCDR2 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vmcSource 
VMCDR3 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vmcSource 
VMCv20110816 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vmcSource 
VMCv20110909 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vmcSource 
VMCv20120126 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vmcSource 
VMCv20121128 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vmcSource 
VMCv20130304 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vmcSource 
VMCv20130805 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vmcSource 
VMCv20140428 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vmcSource 
VMCv20140903 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vmcSource 
VMCv20150309 
Point source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vmcSynopticSource 
VMCDR1 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vmcSynopticSource 
VMCDR2 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vmcSynopticSource 
VMCDR3 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vmcSynopticSource 
VMCv20110816 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vmcSynopticSource 
VMCv20110909 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vmcSynopticSource 
VMCv20120126 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vmcSynopticSource 
VMCv20121128 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vmcSynopticSource 
VMCv20130304 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vmcSynopticSource 
VMCv20130805 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vmcSynopticSource 
VMCv20140428 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vmcSynopticSource 
VMCv20140903 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vmcSynopticSource 
VMCv20150309 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vvvSource 
VVVDR2 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag4 
vvvSource 
VVVv20100531 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vvvSource 
VVVv20110718 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4 
vvvSource, vvvSynopticSource 
VVVDR1 
Extended source Ks aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag4Err 
svNgc253Source 
SVNGC253v20100429 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
svOrionSource 
SVORIONv20100429 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
ultravistaSource 
ULTRAVISTAv20100429 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vhsSource 
VHSDR1 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vhsSource 
VHSDR2 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vhsSource 
VHSDR3 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag4Err 
vhsSource 
VHSv20120926 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vhsSource 
VHSv20130417 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vhsSource 
VHSv20140409 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag4Err 
vhsSource 
VHSv20150108 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag4Err 
videoSource 
VIDEODR2 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
videoSource 
VIDEODR3 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
videoSource 
VIDEODR4 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag4Err 
videoSource 
VIDEOv20100513 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
videoSource 
VIDEOv20111208 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vikingSource 
VIKINGDR2 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vikingSource 
VIKINGDR3 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vikingSource 
VIKINGDR4 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag4Err 
vikingSource 
VIKINGv20110714 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vikingSource 
VIKINGv20111019 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vikingSource 
VIKINGv20130417 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vikingSource 
VIKINGv20140402 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vikingSource 
VIKINGv20150421 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag4Err 
vmcSource 
VMCDR1 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSource 
VMCDR2 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSource 
VMCDR3 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag4Err 
vmcSource 
VMCv20110816 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSource 
VMCv20110909 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSource 
VMCv20120126 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSource 
VMCv20121128 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSource 
VMCv20130304 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSource 
VMCv20130805 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSource 
VMCv20140428 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag4Err 
vmcSource 
VMCv20140903 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag4Err 
vmcSource 
VMCv20150309 
Error in point/extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag4Err 
vmcSynopticSource 
VMCDR1 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSynopticSource 
VMCDR2 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSynopticSource 
VMCDR3 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag4Err 
vmcSynopticSource 
VMCv20110816 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSynopticSource 
VMCv20110909 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSynopticSource 
VMCv20120126 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSynopticSource 
VMCv20121128 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSynopticSource 
VMCv20130304 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSynopticSource 
VMCv20130805 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vmcSynopticSource 
VMCv20140428 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag4Err 
vmcSynopticSource 
VMCv20140903 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag4Err 
vmcSynopticSource 
VMCv20150309 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag4Err 
vvvSource 
VVVDR2 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vvvSource 
VVVv20100531 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vvvSource 
VVVv20110718 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag4Err 
vvvSource, vvvSynopticSource 
VVVDR1 
Error in extended source Ks mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag5 
vmcSynopticSource 
VMCDR1 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag5 
vmcSynopticSource 
VMCDR2 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag5 
vmcSynopticSource 
VMCDR3 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag5 
vmcSynopticSource 
VMCv20110816 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag5 
vmcSynopticSource 
VMCv20110909 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag5 
vmcSynopticSource 
VMCv20120126 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag5 
vmcSynopticSource 
VMCv20121128 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag5 
vmcSynopticSource 
VMCv20130304 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag5 
vmcSynopticSource 
VMCv20130805 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag5 
vmcSynopticSource 
VMCv20140428 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag5 
vmcSynopticSource 
VMCv20140903 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag5 
vmcSynopticSource 
VMCv20150309 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag5 
vvvSynopticSource 
VVVDR1 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag5 
vvvSynopticSource 
VVVDR2 
Extended source Ks aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag5Err 
vmcSynopticSource 
VMCDR1 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag5Err 
vmcSynopticSource 
VMCDR2 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag5Err 
vmcSynopticSource 
VMCDR3 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag5Err 
vmcSynopticSource 
VMCv20110816 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag5Err 
vmcSynopticSource 
VMCv20110909 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag5Err 
vmcSynopticSource 
VMCv20120126 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag5Err 
vmcSynopticSource 
VMCv20121128 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag5Err 
vmcSynopticSource 
VMCv20130304 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag5Err 
vmcSynopticSource 
VMCv20130805 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag5Err 
vmcSynopticSource 
VMCv20140428 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag5Err 
vmcSynopticSource 
VMCv20140903 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag5Err 
vmcSynopticSource 
VMCv20150309 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag5Err 
vvvSynopticSource 
VVVDR1 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag5Err 
vvvSynopticSource 
VVVDR2 
Error in extended source Ks mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6 
svNgc253Source 
SVNGC253v20100429 
Extended source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
svOrionSource 
SVORIONv20100429 
Extended source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
ultravistaSource 
ULTRAVISTAv20100429 
Extended source Ks mag, no aperture correction applied 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vhsSource 
VHSDR1 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vhsSource 
VHSDR2 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vhsSource 
VHSDR3 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6 
vhsSource 
VHSv20120926 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vhsSource 
VHSv20130417 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vhsSource 
VHSv20140409 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6 
vhsSource 
VHSv20150108 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6 
videoSource 
VIDEODR2 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
videoSource 
VIDEODR3 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
videoSource 
VIDEODR4 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6 
videoSource 
VIDEOv20100513 
Extended source Ks mag, no aperture correction applied 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
videoSource 
VIDEOv20111208 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vikingSource 
VIKINGDR2 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vikingSource 
VIKINGDR3 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vikingSource 
VIKINGDR4 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6 
vikingSource 
VIKINGv20110714 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vikingSource 
VIKINGv20111019 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vikingSource 
VIKINGv20130417 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vikingSource 
VIKINGv20140402 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6 
vikingSource 
VIKINGv20150421 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6 
vmcSource 
VMCDR1 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vmcSource 
VMCDR2 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6 
vmcSource 
VMCDR3 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6 
vmcSource 
VMCv20110816 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vmcSource 
VMCv20110909 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vmcSource 
VMCv20120126 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vmcSource 
VMCv20121128 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vmcSource 
VMCv20130304 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMag6 
vmcSource 
VMCv20130805 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6 
vmcSource 
VMCv20140428 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6 
vmcSource 
VMCv20140903 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6 
vmcSource 
VMCv20150309 
Point source Ks aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMag6Err 
svNgc253Source 
SVNGC253v20100429 
Error in extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
svOrionSource 
SVORIONv20100429 
Error in extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
ultravistaSource 
ULTRAVISTAv20100429 
Error in extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vhsSource 
VHSDR1 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vhsSource 
VHSDR2 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vhsSource 
VHSDR3 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag6Err 
vhsSource 
VHSv20120926 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vhsSource 
VHSv20130417 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vhsSource 
VHSv20140409 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag6Err 
vhsSource 
VHSv20150108 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag6Err 
videoSource 
VIDEODR2 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
videoSource 
VIDEODR3 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
videoSource 
VIDEODR4 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag6Err 
videoSource 
VIDEOv20100513 
Error in extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
videoSource 
VIDEOv20111208 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vikingSource 
VIKINGDR2 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vikingSource 
VIKINGDR3 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vikingSource 
VIKINGDR4 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag6Err 
vikingSource 
VIKINGv20110714 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vikingSource 
VIKINGv20111019 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vikingSource 
VIKINGv20130417 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vikingSource 
VIKINGv20140402 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vikingSource 
VIKINGv20150421 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag6Err 
vmcSource 
VMCDR1 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vmcSource 
VMCDR2 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vmcSource 
VMCDR3 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag6Err 
vmcSource 
VMCv20110816 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vmcSource 
VMCv20110909 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vmcSource 
VMCv20120126 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vmcSource 
VMCv20121128 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vmcSource 
VMCv20130304 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vmcSource 
VMCv20130805 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
ksAperMag6Err 
vmcSource 
VMCv20140428 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksAperMag6Err 
vmcSource 
VMCv20140903 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMag6Err 
vmcSource 
VMCv20150309 
Error in point/extended source Ks mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksAperMagNoAperCorr3 
vhsSource 
VHSDR1 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vhsSource 
VHSDR2 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vhsSource 
VHSDR3 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr3 
vhsSource 
VHSv20120926 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vhsSource 
VHSv20130417 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vhsSource 
VHSv20140409 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr3 
vhsSource 
VHSv20150108 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr3 
videoSource 
VIDEODR2 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
videoSource 
VIDEODR3 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
videoSource 
VIDEODR4 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr3 
videoSource 
VIDEOv20111208 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vikingSource 
VIKINGDR2 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vikingSource 
VIKINGDR3 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vikingSource 
VIKINGDR4 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr3 
vikingSource 
VIKINGv20110714 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vikingSource 
VIKINGv20111019 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vikingSource 
VIKINGv20130417 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vikingSource 
VIKINGv20140402 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr3 
vikingSource 
VIKINGv20150421 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr3 
vmcSource 
VMCDR1 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vmcSource 
VMCDR2 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr3 
vmcSource 
VMCDR3 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr3 
vmcSource 
VMCv20110816 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vmcSource 
VMCv20110909 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vmcSource 
VMCv20120126 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vmcSource 
VMCv20121128 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vmcSource 
VMCv20130304 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr3 
vmcSource 
VMCv20130805 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr3 
vmcSource 
VMCv20140428 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr3 
vmcSource 
VMCv20140903 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr3 
vmcSource 
VMCv20150309 
Default extended source Ks aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
vhsSource 
VHSDR1 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vhsSource 
VHSDR2 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vhsSource 
VHSDR3 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
vhsSource 
VHSv20120926 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vhsSource 
VHSv20130417 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vhsSource 
VHSv20140409 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
vhsSource 
VHSv20150108 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
videoSource 
VIDEODR2 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
videoSource 
VIDEODR3 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
videoSource 
VIDEODR4 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
videoSource 
VIDEOv20111208 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vikingSource 
VIKINGDR2 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vikingSource 
VIKINGDR3 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vikingSource 
VIKINGDR4 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
vikingSource 
VIKINGv20110714 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vikingSource 
VIKINGv20111019 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vikingSource 
VIKINGv20130417 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vikingSource 
VIKINGv20140402 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
vikingSource 
VIKINGv20150421 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
vmcSource 
VMCDR1 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vmcSource 
VMCDR2 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
vmcSource 
VMCDR3 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
vmcSource 
VMCv20110816 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vmcSource 
VMCv20110909 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vmcSource 
VMCv20120126 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vmcSource 
VMCv20121128 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vmcSource 
VMCv20130304 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr4 
vmcSource 
VMCv20130805 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
vmcSource 
VMCv20140428 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
vmcSource 
VMCv20140903 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr4 
vmcSource 
VMCv20150309 
Extended source Ks aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
vhsSource 
VHSDR1 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vhsSource 
VHSDR2 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vhsSource 
VHSDR3 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
vhsSource 
VHSv20120926 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vhsSource 
VHSv20130417 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vhsSource 
VHSv20140409 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
vhsSource 
VHSv20150108 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
videoSource 
VIDEODR2 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
videoSource 
VIDEODR3 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
videoSource 
VIDEODR4 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
videoSource 
VIDEOv20111208 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vikingSource 
VIKINGDR2 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vikingSource 
VIKINGDR3 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vikingSource 
VIKINGDR4 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
vikingSource 
VIKINGv20110714 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vikingSource 
VIKINGv20111019 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vikingSource 
VIKINGv20130417 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vikingSource 
VIKINGv20140402 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
vikingSource 
VIKINGv20150421 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
vmcSource 
VMCDR1 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vmcSource 
VMCDR2 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
vmcSource 
VMCDR3 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
vmcSource 
VMCv20110816 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vmcSource 
VMCv20110909 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vmcSource 
VMCv20120126 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vmcSource 
VMCv20121128 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vmcSource 
VMCv20130304 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksAperMagNoAperCorr6 
vmcSource 
VMCv20130805 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
vmcSource 
VMCv20140428 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
vmcSource 
VMCv20140903 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksAperMagNoAperCorr6 
vmcSource 
VMCv20150309 
Extended source Ks aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksaStratAst 
videoVarFrameSetInfo 
VIDEODR2 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
videoVarFrameSetInfo 
VIDEODR3 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
videoVarFrameSetInfo 
VIDEODR4 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
videoVarFrameSetInfo 
VIDEOv20100513 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
videoVarFrameSetInfo 
VIDEOv20111208 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vikingVarFrameSetInfo 
VIKINGDR2 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vikingVarFrameSetInfo 
VIKINGv20110714 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vikingVarFrameSetInfo 
VIKINGv20111019 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vmcVarFrameSetInfo 
VMCDR1 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vmcVarFrameSetInfo 
VMCDR2 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vmcVarFrameSetInfo 
VMCDR3 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vmcVarFrameSetInfo 
VMCv20110816 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vmcVarFrameSetInfo 
VMCv20110909 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vmcVarFrameSetInfo 
VMCv20120126 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vmcVarFrameSetInfo 
VMCv20121128 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vmcVarFrameSetInfo 
VMCv20130304 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vmcVarFrameSetInfo 
VMCv20130805 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vmcVarFrameSetInfo 
VMCv20140428 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vmcVarFrameSetInfo 
VMCv20140903 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vmcVarFrameSetInfo 
VMCv20150309 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vvvVarFrameSetInfo 
VVVDR1 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vvvVarFrameSetInfo 
VVVDR2 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vvvVarFrameSetInfo 
VVVv20100531 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratAst 
vvvVarFrameSetInfo 
VVVv20110718 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksaStratPht 
videoVarFrameSetInfo 
VIDEODR2 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
videoVarFrameSetInfo 
VIDEODR3 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
videoVarFrameSetInfo 
VIDEODR4 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
videoVarFrameSetInfo 
VIDEOv20100513 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
videoVarFrameSetInfo 
VIDEOv20111208 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vikingVarFrameSetInfo 
VIKINGDR2 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vikingVarFrameSetInfo 
VIKINGv20110714 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vikingVarFrameSetInfo 
VIKINGv20111019 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vmcVarFrameSetInfo 
VMCDR1 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vmcVarFrameSetInfo 
VMCDR2 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vmcVarFrameSetInfo 
VMCDR3 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vmcVarFrameSetInfo 
VMCv20110816 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vmcVarFrameSetInfo 
VMCv20110909 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vmcVarFrameSetInfo 
VMCv20120126 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vmcVarFrameSetInfo 
VMCv20121128 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vmcVarFrameSetInfo 
VMCv20130304 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vmcVarFrameSetInfo 
VMCv20130805 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vmcVarFrameSetInfo 
VMCv20140428 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vmcVarFrameSetInfo 
VMCv20140903 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vmcVarFrameSetInfo 
VMCv20150309 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vvvVarFrameSetInfo 
VVVDR1 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vvvVarFrameSetInfo 
VVVDR2 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vvvVarFrameSetInfo 
VVVv20100531 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksaStratPht 
vvvVarFrameSetInfo 
VVVv20110718 
Strateva parameter, a, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksAverageConf 
svNgc253Source 
SVNGC253v20100429 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
meta.code 
ksAverageConf 
svOrionSource 
SVORIONv20100429 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
meta.code 
ksAverageConf 
vhsSource 
VHSDR1 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
meta.code 
ksAverageConf 
vhsSource 
VHSDR2 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
meta.code 
ksAverageConf 
vhsSource 
VHSDR3 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.K 
ksAverageConf 
vhsSource 
VHSv20120926 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
stat.likelihood;em.IR.NIR 
ksAverageConf 
vhsSource 
VHSv20130417 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
ksAverageConf 
vhsSource 
VHSv20140409 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.K 
ksAverageConf 
vhsSource 
VHSv20150108 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.K 
ksAverageConf 
vikingSource 
VIKINGDR2 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
meta.code 
ksAverageConf 
vikingSource 
VIKINGDR3 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
stat.likelihood;em.IR.NIR 
ksAverageConf 
vikingSource 
VIKINGDR4 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.K 
ksAverageConf 
vikingSource 
VIKINGv20110714 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
meta.code 
ksAverageConf 
vikingSource 
VIKINGv20111019 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
meta.code 
ksAverageConf 
vikingSource 
VIKINGv20130417 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
ksAverageConf 
vikingSource 
VIKINGv20140402 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
ksAverageConf 
vikingSource 
VIKINGv20150421 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.K 
ksAverageConf 
vmcSource 
VMCDR2 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
ksAverageConf 
vmcSource 
VMCDR3 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.K 
ksAverageConf 
vmcSource 
VMCv20110816 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
meta.code 
ksAverageConf 
vmcSource 
VMCv20110909 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
meta.code 
ksAverageConf 
vmcSource 
VMCv20120126 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
meta.code 
ksAverageConf 
vmcSource 
VMCv20121128 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
stat.likelihood;em.IR.NIR 
ksAverageConf 
vmcSource 
VMCv20130304 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
ksAverageConf 
vmcSource 
VMCv20130805 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
ksAverageConf 
vmcSource 
VMCv20140428 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.K 
ksAverageConf 
vmcSource 
VMCv20140903 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.K 
ksAverageConf 
vmcSource 
VMCv20150309 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.K 
ksAverageConf 
vmcSource, vmcSynopticSource 
VMCDR1 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
meta.code 
ksAverageConf 
vvvSource 
VVVDR2 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
ksAverageConf 
vvvSource, vvvSynopticSource 
VVVDR1 
average confidence in 2 arcsec diameter default aperture (aper3) Ks 
real 
4 

99999999 
stat.likelihood;em.IR.NIR 
ksbestAper 
videoVariability 
VIDEODR2 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
videoVariability 
VIDEODR3 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
videoVariability 
VIDEODR4 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 
meta.code.class;em.IR.K 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
videoVariability 
VIDEOv20100513 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
videoVariability 
VIDEOv20111208 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vikingVariability 
VIKINGDR2 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vikingVariability 
VIKINGv20110714 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vikingVariability 
VIKINGv20111019 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vmcVariability 
VMCDR1 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vmcVariability 
VMCDR2 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vmcVariability 
VMCDR3 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 
meta.code.class;em.IR.K 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vmcVariability 
VMCv20110816 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vmcVariability 
VMCv20110909 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vmcVariability 
VMCv20120126 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vmcVariability 
VMCv20121128 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vmcVariability 
VMCv20130304 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vmcVariability 
VMCv20130805 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vmcVariability 
VMCv20140428 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 
meta.code.class;em.IR.K 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vmcVariability 
VMCv20140903 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 
meta.code.class;em.IR.K 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vmcVariability 
VMCv20150309 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 
meta.code.class;em.IR.K 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vvvVariability 
VVVDR1 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vvvVariability 
VVVDR2 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vvvVariability 
VVVv20100531 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbestAper 
vvvVariability 
VVVv20110718 
Best aperture (16) for photometric statistics in the Ks band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ksbStratAst 
videoVarFrameSetInfo 
VIDEODR2 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
videoVarFrameSetInfo 
VIDEODR3 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
videoVarFrameSetInfo 
VIDEODR4 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
videoVarFrameSetInfo 
VIDEOv20100513 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
videoVarFrameSetInfo 
VIDEOv20111208 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vikingVarFrameSetInfo 
VIKINGDR2 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vikingVarFrameSetInfo 
VIKINGv20110714 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vikingVarFrameSetInfo 
VIKINGv20111019 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vmcVarFrameSetInfo 
VMCDR1 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vmcVarFrameSetInfo 
VMCDR2 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vmcVarFrameSetInfo 
VMCDR3 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vmcVarFrameSetInfo 
VMCv20110816 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vmcVarFrameSetInfo 
VMCv20110909 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vmcVarFrameSetInfo 
VMCv20120126 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vmcVarFrameSetInfo 
VMCv20121128 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vmcVarFrameSetInfo 
VMCv20130304 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vmcVarFrameSetInfo 
VMCv20130805 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vmcVarFrameSetInfo 
VMCv20140428 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vmcVarFrameSetInfo 
VMCv20140903 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vmcVarFrameSetInfo 
VMCv20150309 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vvvVarFrameSetInfo 
VVVDR1 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vvvVarFrameSetInfo 
VVVDR2 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vvvVarFrameSetInfo 
VVVv20100531 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratAst 
vvvVarFrameSetInfo 
VVVv20110718 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ksbStratPht 
videoVarFrameSetInfo 
VIDEODR2 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
videoVarFrameSetInfo 
VIDEODR3 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
videoVarFrameSetInfo 
VIDEODR4 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
videoVarFrameSetInfo 
VIDEOv20100513 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
videoVarFrameSetInfo 
VIDEOv20111208 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vikingVarFrameSetInfo 
VIKINGDR2 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vikingVarFrameSetInfo 
VIKINGv20110714 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vikingVarFrameSetInfo 
VIKINGv20111019 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vmcVarFrameSetInfo 
VMCDR1 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vmcVarFrameSetInfo 
VMCDR2 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vmcVarFrameSetInfo 
VMCDR3 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vmcVarFrameSetInfo 
VMCv20110816 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vmcVarFrameSetInfo 
VMCv20110909 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vmcVarFrameSetInfo 
VMCv20120126 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vmcVarFrameSetInfo 
VMCv20121128 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vmcVarFrameSetInfo 
VMCv20130304 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vmcVarFrameSetInfo 
VMCv20130805 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vmcVarFrameSetInfo 
VMCv20140428 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vmcVarFrameSetInfo 
VMCv20140903 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vmcVarFrameSetInfo 
VMCv20150309 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vvvVarFrameSetInfo 
VVVDR1 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vvvVarFrameSetInfo 
VVVDR2 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vvvVarFrameSetInfo 
VVVv20100531 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksbStratPht 
vvvVarFrameSetInfo 
VVVv20110718 
Strateva parameter, b, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqAst 
videoVarFrameSetInfo 
VIDEODR2 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
videoVarFrameSetInfo 
VIDEODR3 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
videoVarFrameSetInfo 
VIDEODR4 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
videoVarFrameSetInfo 
VIDEOv20100513 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
videoVarFrameSetInfo 
VIDEOv20111208 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vikingVarFrameSetInfo 
VIKINGDR2 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vikingVarFrameSetInfo 
VIKINGv20110714 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vikingVarFrameSetInfo 
VIKINGv20111019 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vmcVarFrameSetInfo 
VMCDR1 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vmcVarFrameSetInfo 
VMCDR2 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vmcVarFrameSetInfo 
VMCDR3 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vmcVarFrameSetInfo 
VMCv20110816 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vmcVarFrameSetInfo 
VMCv20110909 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vmcVarFrameSetInfo 
VMCv20120126 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vmcVarFrameSetInfo 
VMCv20121128 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vmcVarFrameSetInfo 
VMCv20130304 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vmcVarFrameSetInfo 
VMCv20130805 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vmcVarFrameSetInfo 
VMCv20140428 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vmcVarFrameSetInfo 
VMCv20140903 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vmcVarFrameSetInfo 
VMCv20150309 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vvvVarFrameSetInfo 
VVVDR1 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vvvVarFrameSetInfo 
VVVDR2 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vvvVarFrameSetInfo 
VVVv20100531 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqAst 
vvvVarFrameSetInfo 
VVVv20110718 
Goodness of fit of Strateva function to astrometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kschiSqpd 
videoVariability 
VIDEODR2 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
videoVariability 
VIDEODR3 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
videoVariability 
VIDEODR4 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
videoVariability 
VIDEOv20100513 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
videoVariability 
VIDEOv20111208 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vikingVariability 
VIKINGDR2 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vikingVariability 
VIKINGv20110714 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vikingVariability 
VIKINGv20111019 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vmcVariability 
VMCDR1 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vmcVariability 
VMCDR2 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vmcVariability 
VMCDR3 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vmcVariability 
VMCv20110816 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vmcVariability 
VMCv20110909 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vmcVariability 
VMCv20120126 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vmcVariability 
VMCv20121128 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vmcVariability 
VMCv20130304 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vmcVariability 
VMCv20130805 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vmcVariability 
VMCv20140428 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vmcVariability 
VMCv20140903 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vmcVariability 
VMCv20150309 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vvvVariability 
VVVDR1 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vvvVariability 
VVVDR2 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vvvVariability 
VVVv20100531 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqpd 
vvvVariability 
VVVv20110718 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
kschiSqPht 
videoVarFrameSetInfo 
VIDEODR2 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
videoVarFrameSetInfo 
VIDEODR3 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
videoVarFrameSetInfo 
VIDEODR4 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
videoVarFrameSetInfo 
VIDEOv20100513 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
videoVarFrameSetInfo 
VIDEOv20111208 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vikingVarFrameSetInfo 
VIKINGDR2 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vikingVarFrameSetInfo 
VIKINGv20110714 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vikingVarFrameSetInfo 
VIKINGv20111019 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vmcVarFrameSetInfo 
VMCDR1 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vmcVarFrameSetInfo 
VMCDR2 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vmcVarFrameSetInfo 
VMCDR3 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vmcVarFrameSetInfo 
VMCv20110816 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vmcVarFrameSetInfo 
VMCv20110909 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vmcVarFrameSetInfo 
VMCv20120126 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vmcVarFrameSetInfo 
VMCv20121128 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vmcVarFrameSetInfo 
VMCv20130304 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vmcVarFrameSetInfo 
VMCv20130805 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vmcVarFrameSetInfo 
VMCv20140428 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vmcVarFrameSetInfo 
VMCv20140903 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vmcVarFrameSetInfo 
VMCv20150309 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vvvVarFrameSetInfo 
VVVDR1 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vvvVarFrameSetInfo 
VVVDR2 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vvvVarFrameSetInfo 
VVVv20100531 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kschiSqPht 
vvvVarFrameSetInfo 
VVVv20110718 
Goodness of fit of Strateva function to photometric data in Ks band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksClass 
svNgc253Source 
SVNGC253v20100429 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
svOrionSource 
SVORIONv20100429 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
ultravistaSource, ultravistaSourceRemeasurement 
ULTRAVISTAv20100429 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vhsSource 
VHSDR2 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vhsSource 
VHSDR3 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class;em.IR.K 
ksClass 
vhsSource 
VHSv20120926 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vhsSource 
VHSv20130417 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vhsSource 
VHSv20140409 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class;em.IR.K 
ksClass 
vhsSource 
VHSv20150108 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class;em.IR.K 
ksClass 
vhsSource, vhsSourceRemeasurement 
VHSDR1 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
videoSource 
VIDEODR2 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
videoSource 
VIDEODR3 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
videoSource 
VIDEODR4 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class;em.IR.K 
ksClass 
videoSource 
VIDEOv20111208 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
videoSource, videoSourceRemeasurement 
VIDEOv20100513 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vikingSource 
VIKINGDR2 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vikingSource 
VIKINGDR3 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vikingSource 
VIKINGDR4 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class;em.IR.K 
ksClass 
vikingSource 
VIKINGv20111019 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vikingSource 
VIKINGv20130417 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vikingSource 
VIKINGv20140402 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vikingSource 
VIKINGv20150421 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class;em.IR.K 
ksClass 
vikingSource, vikingSourceRemeasurement 
VIKINGv20110714 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vmcSource 
VMCDR2 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vmcSource 
VMCDR3 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class;em.IR.K 
ksClass 
vmcSource 
VMCv20110909 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vmcSource 
VMCv20120126 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vmcSource 
VMCv20121128 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vmcSource 
VMCv20130304 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vmcSource 
VMCv20130805 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vmcSource 
VMCv20140428 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class;em.IR.K 
ksClass 
vmcSource 
VMCv20140903 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class;em.IR.K 
ksClass 
vmcSource 
VMCv20150309 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class;em.IR.K 
ksClass 
vmcSource, vmcSourceRemeasurement 
VMCv20110816 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vmcSource, vmcSynopticSource 
VMCDR1 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vvvSource 
VVVDR2 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vvvSource 
VVVv20110718 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vvvSource, vvvSourceRemeasurement 
VVVv20100531 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClass 
vvvSource, vvvSynopticSource 
VVVDR1 
discrete image classification flag in Ks 
smallint 
2 

9999 
src.class 
ksClassStat 
svNgc253Source 
SVNGC253v20100429 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
svOrionSource 
SVORIONv20100429 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
ultravistaSource 
ULTRAVISTAv20100429 
SExtractor classification statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
ultravistaSourceRemeasurement 
ULTRAVISTAv20100429 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vhsSource 
VHSDR2 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vhsSource 
VHSDR3 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat;em.IR.K 
ksClassStat 
vhsSource 
VHSv20120926 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vhsSource 
VHSv20130417 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vhsSource 
VHSv20140409 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat;em.IR.K 
ksClassStat 
vhsSource 
VHSv20150108 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat;em.IR.K 
ksClassStat 
vhsSource, vhsSourceRemeasurement 
VHSDR1 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
videoSource 
VIDEODR2 
SExtractor classification statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
videoSource 
VIDEODR3 
SExtractor classification statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
videoSource 
VIDEODR4 
SExtractor classification statistic in Ks 
real 
4 

0.9999995e9 
stat;em.IR.K 
ksClassStat 
videoSource 
VIDEOv20100513 
SExtractor classification statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
videoSource 
VIDEOv20111208 
SExtractor classification statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
videoSourceRemeasurement 
VIDEOv20100513 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vikingSource 
VIKINGDR2 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vikingSource 
VIKINGDR3 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vikingSource 
VIKINGDR4 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat;em.IR.K 
ksClassStat 
vikingSource 
VIKINGv20111019 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vikingSource 
VIKINGv20130417 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vikingSource 
VIKINGv20140402 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vikingSource 
VIKINGv20150421 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat;em.IR.K 
ksClassStat 
vikingSource, vikingSourceRemeasurement 
VIKINGv20110714 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vmcSource 
VMCDR2 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vmcSource 
VMCDR3 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat;em.IR.K 
ksClassStat 
vmcSource 
VMCv20110909 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vmcSource 
VMCv20120126 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vmcSource 
VMCv20121128 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vmcSource 
VMCv20130304 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vmcSource 
VMCv20130805 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vmcSource 
VMCv20140428 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat;em.IR.K 
ksClassStat 
vmcSource 
VMCv20140903 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat;em.IR.K 
ksClassStat 
vmcSource 
VMCv20150309 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat;em.IR.K 
ksClassStat 
vmcSource, vmcSourceRemeasurement 
VMCv20110816 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vmcSource, vmcSynopticSource 
VMCDR1 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vvvSource 
VVVDR1 
SExtractor classification statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vvvSource 
VVVDR2 
SExtractor classification statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vvvSource 
VVVv20100531 
SExtractor classification statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vvvSource 
VVVv20110718 
SExtractor classification statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vvvSourceRemeasurement 
VVVv20100531 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vvvSourceRemeasurement 
VVVv20110718 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vvvSynopticSource 
VVVDR1 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
ksClassStat 
vvvSynopticSource 
VVVDR2 
N(0,1) stellarnessofprofile statistic in Ks 
real 
4 

0.9999995e9 
stat 
kscStratAst 
videoVarFrameSetInfo 
VIDEODR2 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
videoVarFrameSetInfo 
VIDEODR3 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
videoVarFrameSetInfo 
VIDEODR4 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
videoVarFrameSetInfo 
VIDEOv20100513 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
videoVarFrameSetInfo 
VIDEOv20111208 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vikingVarFrameSetInfo 
VIKINGDR2 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vikingVarFrameSetInfo 
VIKINGv20110714 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vikingVarFrameSetInfo 
VIKINGv20111019 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vmcVarFrameSetInfo 
VMCDR1 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vmcVarFrameSetInfo 
VMCDR2 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vmcVarFrameSetInfo 
VMCDR3 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vmcVarFrameSetInfo 
VMCv20110816 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vmcVarFrameSetInfo 
VMCv20110909 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vmcVarFrameSetInfo 
VMCv20120126 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vmcVarFrameSetInfo 
VMCv20121128 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vmcVarFrameSetInfo 
VMCv20130304 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vmcVarFrameSetInfo 
VMCv20130805 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vmcVarFrameSetInfo 
VMCv20140428 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vmcVarFrameSetInfo 
VMCv20140903 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vmcVarFrameSetInfo 
VMCv20150309 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vvvVarFrameSetInfo 
VVVDR1 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vvvVarFrameSetInfo 
VVVDR2 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vvvVarFrameSetInfo 
VVVv20100531 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratAst 
vvvVarFrameSetInfo 
VVVv20110718 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
kscStratPht 
videoVarFrameSetInfo 
VIDEODR2 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
videoVarFrameSetInfo 
VIDEODR3 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
videoVarFrameSetInfo 
VIDEODR4 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
videoVarFrameSetInfo 
VIDEOv20100513 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
videoVarFrameSetInfo 
VIDEOv20111208 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vikingVarFrameSetInfo 
VIKINGDR2 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vikingVarFrameSetInfo 
VIKINGv20110714 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vikingVarFrameSetInfo 
VIKINGv20111019 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vmcVarFrameSetInfo 
VMCDR1 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vmcVarFrameSetInfo 
VMCDR2 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vmcVarFrameSetInfo 
VMCDR3 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vmcVarFrameSetInfo 
VMCv20110816 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vmcVarFrameSetInfo 
VMCv20110909 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vmcVarFrameSetInfo 
VMCv20120126 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vmcVarFrameSetInfo 
VMCv20121128 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vmcVarFrameSetInfo 
VMCv20130304 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vmcVarFrameSetInfo 
VMCv20130805 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vmcVarFrameSetInfo 
VMCv20140428 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vmcVarFrameSetInfo 
VMCv20140903 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vmcVarFrameSetInfo 
VMCv20150309 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.K 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vvvVarFrameSetInfo 
VVVDR1 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vvvVarFrameSetInfo 
VVVDR2 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vvvVarFrameSetInfo 
VVVv20100531 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
kscStratPht 
vvvVarFrameSetInfo 
VVVv20110718 
Strateva parameter, c, in fit to photometric rms vs magnitude in Ks band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ksDeblend 
ultravistaSource, ultravistaSourceRemeasurement 
ULTRAVISTAv20100429 
placeholder flag indicating parent/child relation in Ks 
int 
4 

99999999 
meta.code 
ksDeblend 
vhsSourceRemeasurement 
VHSDR1 
placeholder flag indicating parent/child relation in Ks 
int 
4 

99999999 
meta.code 
ksDeblend 
videoSource, videoSourceRemeasurement 
VIDEOv20100513 
placeholder flag indicating parent/child relation in Ks 
int 
4 

99999999 
meta.code 
ksDeblend 
vikingSourceRemeasurement 
VIKINGv20110714 
placeholder flag indicating parent/child relation in Ks 
int 
4 

99999999 
meta.code 
ksDeblend 
vikingSourceRemeasurement 
VIKINGv20111019 
placeholder flag indicating parent/child relation in Ks 
int 
4 

99999999 
meta.code 
ksDeblend 
vmcSourceRemeasurement 
VMCv20110816 
placeholder flag indicating parent/child relation in Ks 
int 
4 

99999999 
meta.code 
ksDeblend 
vmcSourceRemeasurement 
VMCv20110909 
placeholder flag indicating parent/child relation in Ks 
int 
4 

99999999 
meta.code 
ksDeblend 
vvvSource 
VVVv20110718 
placeholder flag indicating parent/child relation in Ks 
int 
4 

99999999 
meta.code 
ksDeblend 
vvvSource, vvvSourceRemeasurement 
VVVv20100531 
placeholder flag indicating parent/child relation in Ks 
int 
4 

99999999 
meta.code 
ksEll 
svNgc253Source 
SVNGC253v20100429 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
svOrionSource 
SVORIONv20100429 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
ultravistaSource, ultravistaSourceRemeasurement 
ULTRAVISTAv20100429 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vhsSource 
VHSDR2 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vhsSource 
VHSDR3 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.K 
ksEll 
vhsSource 
VHSv20120926 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vhsSource 
VHSv20130417 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vhsSource 
VHSv20140409 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.K 
ksEll 
vhsSource 
VHSv20150108 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.K 
ksEll 
vhsSource, vhsSourceRemeasurement 
VHSDR1 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
videoSource 
VIDEODR2 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
videoSource 
VIDEODR3 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
videoSource 
VIDEODR4 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.K 
ksEll 
videoSource 
VIDEOv20111208 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
videoSource, videoSourceRemeasurement 
VIDEOv20100513 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vikingSource 
VIKINGDR2 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vikingSource 
VIKINGDR3 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vikingSource 
VIKINGDR4 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.K 
ksEll 
vikingSource 
VIKINGv20111019 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vikingSource 
VIKINGv20130417 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vikingSource 
VIKINGv20140402 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vikingSource 
VIKINGv20150421 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.K 
ksEll 
vikingSource, vikingSourceRemeasurement 
VIKINGv20110714 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vmcSource 
VMCDR2 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vmcSource 
VMCDR3 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.K 
ksEll 
vmcSource 
VMCv20110909 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vmcSource 
VMCv20120126 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vmcSource 
VMCv20121128 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vmcSource 
VMCv20130304 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vmcSource 
VMCv20130805 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vmcSource 
VMCv20140428 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.K 
ksEll 
vmcSource 
VMCv20140903 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.K 
ksEll 
vmcSource 
VMCv20150309 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.K 
ksEll 
vmcSource, vmcSourceRemeasurement 
VMCv20110816 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vmcSource, vmcSynopticSource 
VMCDR1 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vvvSource 
VVVDR2 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vvvSource 
VVVv20110718 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vvvSource, vvvSourceRemeasurement 
VVVv20100531 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
ksEll 
vvvSource, vvvSynopticSource 
VVVDR1 
1b/a, where a/b=semimajor/minor axes in Ks 
real 
4 

0.9999995e9 
src.ellipticity 
kseNum 
svNgc253MergeLog 
SVNGC253v20100429 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
svOrionMergeLog 
SVORIONv20100429 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
ultravistaMergeLog 
ULTRAVISTAv20100429 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vhsMergeLog 
VHSDR1 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vhsMergeLog 
VHSDR2 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vhsMergeLog 
VHSDR3 
the extension number of this Ks frame 
tinyint 
1 


meta.number;em.IR.K 
kseNum 
vhsMergeLog 
VHSv20120926 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vhsMergeLog 
VHSv20130417 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vhsMergeLog 
VHSv20140409 
the extension number of this Ks frame 
tinyint 
1 


meta.number;em.IR.K 
kseNum 
vhsMergeLog 
VHSv20150108 
the extension number of this Ks frame 
tinyint 
1 


meta.number;em.IR.K 
kseNum 
videoMergeLog 
VIDEODR2 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
videoMergeLog 
VIDEODR3 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
videoMergeLog 
VIDEODR4 
the extension number of this Ks frame 
tinyint 
1 


meta.number;em.IR.K 
kseNum 
videoMergeLog 
VIDEOv20100513 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
videoMergeLog 
VIDEOv20111208 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vikingMergeLog 
VIKINGDR2 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vikingMergeLog 
VIKINGDR3 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vikingMergeLog 
VIKINGDR4 
the extension number of this Ks frame 
tinyint 
1 


meta.number;em.IR.K 
kseNum 
vikingMergeLog 
VIKINGv20110714 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vikingMergeLog 
VIKINGv20111019 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vikingMergeLog 
VIKINGv20130417 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vikingMergeLog 
VIKINGv20140402 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vikingMergeLog 
VIKINGv20150421 
the extension number of this Ks frame 
tinyint 
1 


meta.number;em.IR.K 
kseNum 
vmcMergeLog 
VMCDR2 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vmcMergeLog 
VMCDR3 
the extension number of this Ks frame 
tinyint 
1 


meta.number;em.IR.K 
kseNum 
vmcMergeLog 
VMCv20110816 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vmcMergeLog 
VMCv20110909 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vmcMergeLog 
VMCv20120126 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vmcMergeLog 
VMCv20121128 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vmcMergeLog 
VMCv20130304 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vmcMergeLog 
VMCv20130805 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vmcMergeLog 
VMCv20140428 
the extension number of this Ks frame 
tinyint 
1 


meta.number;em.IR.K 
kseNum 
vmcMergeLog 
VMCv20140903 
the extension number of this Ks frame 
tinyint 
1 


meta.number;em.IR.K 
kseNum 
vmcMergeLog 
VMCv20150309 
the extension number of this Ks frame 
tinyint 
1 


meta.number;em.IR.K 
kseNum 
vmcMergeLog, vmcSynopticMergeLog 
VMCDR1 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vvvMergeLog 
VVVDR2 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vvvMergeLog 
VVVv20100531 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vvvMergeLog 
VVVv20110718 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
kseNum 
vvvMergeLog, vvvSynopticMergeLog 
VVVDR1 
the extension number of this Ks frame 
tinyint 
1 


meta.number 
ksErrBits 
svNgc253Source 
SVNGC253v20100429 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
svOrionSource 
SVORIONv20100429 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
ultravistaSource 
ULTRAVISTAv20100429 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
This uses the FLAGS attribute in SE. The individual bit flags that this can be decomposed into are as follows: Bit Flag  Meaning   1  The object has neighbours, bright enough and close enough to significantly bias the MAG_AUTO photometry or bad pixels (more than 10% of photometry affected).   2  The object was originally blended with another   4  At least one pixel is saturated (or very close to)   8  The object is truncated (too close to an image boundary)   16  Object's aperture data are incomplete or corrupted   32  Object's isophotal data are imcomplete or corrupted. This is an old flag inherited from SE v1.0, and is kept for compatability reasons. It doesn't have any consequence for the extracted parameters.   64  Memory overflow occurred during deblending   128  Memory overflow occurred during extraction  

ksErrBits 
ultravistaSourceRemeasurement 
ULTRAVISTAv20100429 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
ksErrBits 
vhsSource 
VHSDR1 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vhsSource 
VHSDR2 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vhsSource 
VHSDR3 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code;em.IR.K 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vhsSource 
VHSv20120926 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vhsSource 
VHSv20130417 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vhsSource 
VHSv20140409 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code;em.IR.K 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vhsSource 
VHSv20150108 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code;em.IR.K 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vhsSourceRemeasurement 
VHSDR1 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
ksErrBits 
videoSource 
VIDEODR2 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
This uses the FLAGS attribute in SE. The individual bit flags that this can be decomposed into are as follows: Bit Flag  Meaning   1  The object has neighbours, bright enough and close enough to significantly bias the MAG_AUTO photometry or bad pixels (more than 10% of photometry affected).   2  The object was originally blended with another   4  At least one pixel is saturated (or very close to)   8  The object is truncated (too close to an image boundary)   16  Object's aperture data are incomplete or corrupted   32  Object's isophotal data are imcomplete or corrupted. This is an old flag inherited from SE v1.0, and is kept for compatability reasons. It doesn't have any consequence for the extracted parameters.   64  Memory overflow occurred during deblending   128  Memory overflow occurred during extraction  

ksErrBits 
videoSource 
VIDEODR3 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
This uses the FLAGS attribute in SE. The individual bit flags that this can be decomposed into are as follows: Bit Flag  Meaning   1  The object has neighbours, bright enough and close enough to significantly bias the MAG_AUTO photometry or bad pixels (more than 10% of photometry affected).   2  The object was originally blended with another   4  At least one pixel is saturated (or very close to)   8  The object is truncated (too close to an image boundary)   16  Object's aperture data are incomplete or corrupted   32  Object's isophotal data are imcomplete or corrupted. This is an old flag inherited from SE v1.0, and is kept for compatability reasons. It doesn't have any consequence for the extracted parameters.   64  Memory overflow occurred during deblending   128  Memory overflow occurred during extraction  

ksErrBits 
videoSource 
VIDEODR4 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code;em.IR.K 
This uses the FLAGS attribute in SE. The individual bit flags that this can be decomposed into are as follows: Bit Flag  Meaning   1  The object has neighbours, bright enough and close enough to significantly bias the MAG_AUTO photometry or bad pixels (more than 10% of photometry affected).   2  The object was originally blended with another   4  At least one pixel is saturated (or very close to)   8  The object is truncated (too close to an image boundary)   16  Object's aperture data are incomplete or corrupted   32  Object's isophotal data are imcomplete or corrupted. This is an old flag inherited from SE v1.0, and is kept for compatability reasons. It doesn't have any consequence for the extracted parameters.   64  Memory overflow occurred during deblending   128  Memory overflow occurred during extraction  

ksErrBits 
videoSource 
VIDEOv20100513 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
This uses the FLAGS attribute in SE. The individual bit flags that this can be decomposed into are as follows: Bit Flag  Meaning   1  The object has neighbours, bright enough and close enough to significantly bias the MAG_AUTO photometry or bad pixels (more than 10% of photometry affected).   2  The object was originally blended with another   4  At least one pixel is saturated (or very close to)   8  The object is truncated (too close to an image boundary)   16  Object's aperture data are incomplete or corrupted   32  Object's isophotal data are imcomplete or corrupted. This is an old flag inherited from SE v1.0, and is kept for compatability reasons. It doesn't have any consequence for the extracted parameters.   64  Memory overflow occurred during deblending   128  Memory overflow occurred during extraction  

ksErrBits 
videoSource 
VIDEOv20111208 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
This uses the FLAGS attribute in SE. The individual bit flags that this can be decomposed into are as follows: Bit Flag  Meaning   1  The object has neighbours, bright enough and close enough to significantly bias the MAG_AUTO photometry or bad pixels (more than 10% of photometry affected).   2  The object was originally blended with another   4  At least one pixel is saturated (or very close to)   8  The object is truncated (too close to an image boundary)   16  Object's aperture data are incomplete or corrupted   32  Object's isophotal data are imcomplete or corrupted. This is an old flag inherited from SE v1.0, and is kept for compatability reasons. It doesn't have any consequence for the extracted parameters.   64  Memory overflow occurred during deblending   128  Memory overflow occurred during extraction  

ksErrBits 
videoSourceRemeasurement 
VIDEOv20100513 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
ksErrBits 
vikingSource 
VIKINGDR2 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vikingSource 
VIKINGDR3 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vikingSource 
VIKINGDR4 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code;em.IR.K 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vikingSource 
VIKINGv20110714 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vikingSource 
VIKINGv20111019 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vikingSource 
VIKINGv20130417 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vikingSource 
VIKINGv20140402 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vikingSource 
VIKINGv20150421 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code;em.IR.K 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vikingSourceRemeasurement 
VIKINGv20110714 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
ksErrBits 
vikingSourceRemeasurement 
VIKINGv20111019 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
ksErrBits 
vmcSource 
VMCDR2 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vmcSource 
VMCDR3 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code;em.IR.K 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vmcSource 
VMCv20110816 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vmcSource 
VMCv20110909 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vmcSource 
VMCv20120126 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vmcSource 
VMCv20121128 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vmcSource 
VMCv20130304 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vmcSource 
VMCv20130805 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vmcSource 
VMCv20140428 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code;em.IR.K 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vmcSource 
VMCv20140903 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code;em.IR.K 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vmcSource 
VMCv20150309 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code;em.IR.K 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vmcSource, vmcSynopticSource 
VMCDR1 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vmcSourceRemeasurement 
VMCv20110816 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
ksErrBits 
vmcSourceRemeasurement 
VMCv20110909 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
ksErrBits 
vvvSource 
VVVDR2 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vvvSource 
VVVv20100531 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vvvSource 
VVVv20110718 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vvvSource, vvvSynopticSource 
VVVDR1 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
ksErrBits 
vvvSourceRemeasurement 
VVVv20100531 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
ksErrBits 
vvvSourceRemeasurement 
VVVv20110718 
processing warning/error bitwise flags in Ks 
int 
4 

99999999 
meta.code 
ksEta 
svNgc253Source 
SVNGC253v20100429 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
svOrionSource 
SVORIONv20100429 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
ultravistaSource 
ULTRAVISTAv20100429 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vhsSource 
VHSDR1 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vhsSource 
VHSDR2 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vhsSource 
VHSDR3 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.K 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vhsSource 
VHSv20120926 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vhsSource 
VHSv20130417 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vhsSource 
VHSv20140409 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.K 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vhsSource 
VHSv20150108 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.K 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
videoSource 
VIDEODR2 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
videoSource 
VIDEODR3 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
videoSource 
VIDEODR4 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.K 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
videoSource 
VIDEOv20100513 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
videoSource 
VIDEOv20111208 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vikingSource 
VIKINGDR2 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vikingSource 
VIKINGDR3 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vikingSource 
VIKINGDR4 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.K 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vikingSource 
VIKINGv20110714 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vikingSource 
VIKINGv20111019 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vikingSource 
VIKINGv20130417 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vikingSource 
VIKINGv20140402 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vikingSource 
VIKINGv20150421 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.K 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vmcSource 
VMCDR2 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vmcSource 
VMCDR3 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.K 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vmcSource 
VMCv20110816 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vmcSource 
VMCv20110909 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vmcSource 
VMCv20120126 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vmcSource 
VMCv20121128 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vmcSource 
VMCv20130304 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vmcSource 
VMCv20130805 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vmcSource 
VMCv20140428 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.K 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vmcSource 
VMCv20140903 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.K 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vmcSource 
VMCv20150309 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.K 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vmcSource, vmcSynopticSource 
VMCDR1 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vvvSource 
VVVDR2 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vvvSource 
VVVv20100531 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vvvSource 
VVVv20110718 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksEta 
vvvSource, vvvSynopticSource 
VVVDR1 
Offset of Ks detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
ksexpML 
videoVarFrameSetInfo 
VIDEODR2 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 

ksexpML 
videoVarFrameSetInfo 
VIDEODR3 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 
phot.mag;stat.max;em.IR.NIR 
ksexpML 
videoVarFrameSetInfo 
VIDEODR4 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max 
ksexpML 
videoVarFrameSetInfo 
VIDEOv20100513 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 

ksexpML 
videoVarFrameSetInfo 
VIDEOv20111208 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 

ksexpML 
vikingVarFrameSetInfo 
VIKINGDR2 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 

ksexpML 
vikingVarFrameSetInfo 
VIKINGv20110714 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 

ksexpML 
vikingVarFrameSetInfo 
VIKINGv20111019 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 

ksexpML 
vmcVarFrameSetInfo 
VMCDR1 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 

ksexpML 
vmcVarFrameSetInfo 
VMCDR2 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max;em.IR.NIR 
ksexpML 
vmcVarFrameSetInfo 
VMCDR3 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max 
ksexpML 
vmcVarFrameSetInfo 
VMCv20110816 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 

ksexpML 
vmcVarFrameSetInfo 
VMCv20110909 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 

ksexpML 
vmcVarFrameSetInfo 
VMCv20120126 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 

ksexpML 
vmcVarFrameSetInfo 
VMCv20121128 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.max;em.IR.NIR 
ksexpML 
vmcVarFrameSetInfo 
VMCv20130304 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.max;em.IR.NIR 
ksexpML 
vmcVarFrameSetInfo 
VMCv20130805 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max;em.IR.NIR 
ksexpML 
vmcVarFrameSetInfo 
VMCv20140428 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max 
ksexpML 
vmcVarFrameSetInfo 
VMCv20140903 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max 
ksexpML 
vmcVarFrameSetInfo 
VMCv20150309 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max 
ksexpML 
vvvVarFrameSetInfo 
VVVDR1 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.max;em.IR.NIR 
ksexpML 
vvvVarFrameSetInfo 
VVVDR2 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max;em.IR.NIR 
ksexpML 
vvvVarFrameSetInfo 
VVVv20100531 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 

ksexpML 
vvvVarFrameSetInfo 
VVVv20110718 
Expected magnitude limit of frameSet in this in Ks band. 
real 
4 

0.9999995e9 

ksExpRms 
videoVariability 
VIDEODR2 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
videoVariability 
VIDEODR3 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
videoVariability 
VIDEODR4 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
videoVariability 
VIDEOv20100513 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
videoVariability 
VIDEOv20111208 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vikingVariability 
VIKINGDR2 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vikingVariability 
VIKINGv20110714 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vikingVariability 
VIKINGv20111019 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vmcVariability 
VMCDR1 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vmcVariability 
VMCDR2 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vmcVariability 
VMCDR3 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vmcVariability 
VMCv20110816 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vmcVariability 
VMCv20110909 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vmcVariability 
VMCv20120126 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vmcVariability 
VMCv20121128 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vmcVariability 
VMCv20130304 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vmcVariability 
VMCv20130805 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vmcVariability 
VMCv20140428 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vmcVariability 
VMCv20140903 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vmcVariability 
VMCv20150309 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vvvVariability 
VVVDR1 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vvvVariability 
VVVDR2 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vvvVariability 
VVVv20100531 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksExpRms 
vvvVariability 
VVVv20110718 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Ks band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksGausig 
svNgc253Source 
SVNGC253v20100429 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
svOrionSource 
SVORIONv20100429 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
ultravistaSource, ultravistaSourceRemeasurement 
ULTRAVISTAv20100429 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vhsSource 
VHSDR2 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vhsSource 
VHSDR3 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.K 
ksGausig 
vhsSource 
VHSv20120926 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vhsSource 
VHSv20130417 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vhsSource 
VHSv20140409 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.K 
ksGausig 
vhsSource 
VHSv20150108 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.K 
ksGausig 
vhsSource, vhsSourceRemeasurement 
VHSDR1 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
videoSource 
VIDEODR2 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
videoSource 
VIDEODR3 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
videoSource 
VIDEODR4 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.K 
ksGausig 
videoSource 
VIDEOv20111208 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
videoSource, videoSourceRemeasurement 
VIDEOv20100513 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vikingSource 
VIKINGDR2 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vikingSource 
VIKINGDR3 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vikingSource 
VIKINGDR4 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.K 
ksGausig 
vikingSource 
VIKINGv20111019 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vikingSource 
VIKINGv20130417 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vikingSource 
VIKINGv20140402 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vikingSource 
VIKINGv20150421 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.K 
ksGausig 
vikingSource, vikingSourceRemeasurement 
VIKINGv20110714 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vmcSource 
VMCDR2 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vmcSource 
VMCDR3 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.K 
ksGausig 
vmcSource 
VMCv20110909 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vmcSource 
VMCv20120126 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vmcSource 
VMCv20121128 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vmcSource 
VMCv20130304 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vmcSource 
VMCv20130805 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vmcSource 
VMCv20140428 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.K 
ksGausig 
vmcSource 
VMCv20140903 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.K 
ksGausig 
vmcSource 
VMCv20150309 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.K 
ksGausig 
vmcSource, vmcSourceRemeasurement 
VMCv20110816 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vmcSource, vmcSynopticSource 
VMCDR1 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vvvSource 
VVVDR2 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vvvSource 
VVVv20110718 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vvvSource, vvvSourceRemeasurement 
VVVv20100531 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksGausig 
vvvSource, vvvSynopticSource 
VVVDR1 
RMS of axes of ellipse fit in Ks 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
ksHalfRad 
videoSource 
VIDEODR4 
SExtractor halflight radius in Ks band 
real 
4 
pixels 
0.9999995e9 
phys.angSize;em.IR.K 
ksHlCorSMjRadAs 
svNgc253Source 
SVNGC253v20100429 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
ksHlCorSMjRadAs 
ultravistaSource 
ULTRAVISTAv20100429 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
ksHlCorSMjRadAs 
vhsSource 
VHSDR1 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
ksHlCorSMjRadAs 
vhsSource 
VHSDR2 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
ksHlCorSMjRadAs 
vhsSource 
VHSDR3 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.K 
ksHlCorSMjRadAs 
vhsSource 
VHSv20120926 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize 
ksHlCorSMjRadAs 
vhsSource 
VHSv20130417 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize 
ksHlCorSMjRadAs 
vhsSource 
VHSv20140409 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.K 
ksHlCorSMjRadAs 
vhsSource 
VHSv20150108 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.K 
ksHlCorSMjRadAs 
videoSource 
VIDEODR2 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
ksHlCorSMjRadAs 
videoSource 
VIDEODR3 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize 
ksHlCorSMjRadAs 
videoSource 
VIDEODR4 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.K 
ksHlCorSMjRadAs 
videoSource 
VIDEOv20100513 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
ksHlCorSMjRadAs 
videoSource 
VIDEOv20111208 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
ksHlCorSMjRadAs 
vikingSource 
VIKINGDR2 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
ksHlCorSMjRadAs 
vikingSource 
VIKINGDR3 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize 
ksHlCorSMjRadAs 
vikingSource 
VIKINGDR4 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.K 
ksHlCorSMjRadAs 
vikingSource 
VIKINGv20110714 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
ksHlCorSMjRadAs 
vikingSource 
VIKINGv20111019 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
ksHlCorSMjRadAs 
vikingSource 
VIKINGv20130417 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize 
ksHlCorSMjRadAs 
vikingSource 
VIKINGv20140402 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize 
ksHlCorSMjRadAs 
vikingSource 
VIKINGv20150421 
Seeing corrected halflight, semimajor axis in Ks band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.K 
ksIntRms 
videoVariability 
VIDEODR2 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
videoVariability 
VIDEODR3 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
videoVariability 
VIDEODR4 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
videoVariability 
VIDEOv20100513 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
videoVariability 
VIDEOv20111208 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vikingVariability 
VIKINGDR2 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vikingVariability 
VIKINGv20110714 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vikingVariability 
VIKINGv20111019 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vmcVariability 
VMCDR1 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vmcVariability 
VMCDR2 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vmcVariability 
VMCDR3 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vmcVariability 
VMCv20110816 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vmcVariability 
VMCv20110909 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vmcVariability 
VMCv20120126 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vmcVariability 
VMCv20121128 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vmcVariability 
VMCv20130304 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vmcVariability 
VMCv20130805 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vmcVariability 
VMCv20140428 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vmcVariability 
VMCv20140903 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vmcVariability 
VMCv20150309 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vvvVariability 
VVVDR1 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vvvVariability 
VVVDR2 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vvvVariability 
VVVv20100531 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksIntRms 
vvvVariability 
VVVv20110718 
Intrinsic rms in Ksband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksisDefAst 
videoVarFrameSetInfo 
VIDEODR2 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 

ksisDefAst 
videoVarFrameSetInfo 
VIDEODR3 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefAst 
videoVarFrameSetInfo 
VIDEODR4 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.K 
ksisDefAst 
videoVarFrameSetInfo 
VIDEOv20111208 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 

ksisDefAst 
vikingVarFrameSetInfo 
VIKINGDR2 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 

ksisDefAst 
vikingVarFrameSetInfo 
VIKINGv20111019 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 

ksisDefAst 
vmcVarFrameSetInfo 
VMCDR1 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 

ksisDefAst 
vmcVarFrameSetInfo 
VMCDR2 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefAst 
vmcVarFrameSetInfo 
VMCDR3 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.K 
ksisDefAst 
vmcVarFrameSetInfo 
VMCv20110816 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 

ksisDefAst 
vmcVarFrameSetInfo 
VMCv20110909 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 

ksisDefAst 
vmcVarFrameSetInfo 
VMCv20120126 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 

ksisDefAst 
vmcVarFrameSetInfo 
VMCv20121128 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefAst 
vmcVarFrameSetInfo 
VMCv20130304 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefAst 
vmcVarFrameSetInfo 
VMCv20130805 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefAst 
vmcVarFrameSetInfo 
VMCv20140428 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.K 
ksisDefAst 
vmcVarFrameSetInfo 
VMCv20140903 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.K 
ksisDefAst 
vmcVarFrameSetInfo 
VMCv20150309 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.K 
ksisDefAst 
vvvVarFrameSetInfo 
VVVDR1 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefAst 
vvvVarFrameSetInfo 
VVVDR2 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefAst 
vvvVarFrameSetInfo 
VVVv20110718 
Use a default model for the astrometric noise in Ks band. 
tinyint 
1 

0 

ksisDefPht 
videoVarFrameSetInfo 
VIDEODR2 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 

ksisDefPht 
videoVarFrameSetInfo 
VIDEODR3 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefPht 
videoVarFrameSetInfo 
VIDEODR4 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.K 
ksisDefPht 
videoVarFrameSetInfo 
VIDEOv20111208 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 

ksisDefPht 
vikingVarFrameSetInfo 
VIKINGDR2 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 

ksisDefPht 
vikingVarFrameSetInfo 
VIKINGv20111019 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 

ksisDefPht 
vmcVarFrameSetInfo 
VMCDR1 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 

ksisDefPht 
vmcVarFrameSetInfo 
VMCDR2 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefPht 
vmcVarFrameSetInfo 
VMCDR3 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.K 
ksisDefPht 
vmcVarFrameSetInfo 
VMCv20110816 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 

ksisDefPht 
vmcVarFrameSetInfo 
VMCv20110909 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 

ksisDefPht 
vmcVarFrameSetInfo 
VMCv20120126 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 

ksisDefPht 
vmcVarFrameSetInfo 
VMCv20121128 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefPht 
vmcVarFrameSetInfo 
VMCv20130304 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefPht 
vmcVarFrameSetInfo 
VMCv20130805 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefPht 
vmcVarFrameSetInfo 
VMCv20140428 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.K 
ksisDefPht 
vmcVarFrameSetInfo 
VMCv20140903 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.K 
ksisDefPht 
vmcVarFrameSetInfo 
VMCv20150309 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.K 
ksisDefPht 
vvvVarFrameSetInfo 
VVVDR1 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefPht 
vvvVarFrameSetInfo 
VVVDR2 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
ksisDefPht 
vvvVarFrameSetInfo 
VVVv20110718 
Use a default model for the photometric noise in Ks band. 
tinyint 
1 

0 

ksKronMag 
videoSource 
VIDEODR4 
Extended source Ks mag (Kron  SExtractor MAG_AUTO) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K 
ksKronMagErr 
videoSource 
VIDEODR4 
Extended source Ks mag error (Kron  SExtractor MAG_AUTO) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
ksMag 
ultravistaSourceRemeasurement 
ULTRAVISTAv20100429 
Ks mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksMag 
vhsSourceRemeasurement 
VHSDR1 
Ks mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksMag 
videoSourceRemeasurement 
VIDEOv20100513 
Ks mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksMag 
vikingSourceRemeasurement 
VIKINGv20110714 
Ks mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksMag 
vikingSourceRemeasurement 
VIKINGv20111019 
Ks mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksMag 
vmcSourceRemeasurement 
VMCv20110816 
Ks mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksMag 
vmcSourceRemeasurement 
VMCv20110909 
Ks mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksMag 
vvvSourceRemeasurement 
VVVv20100531 
Ks mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksMag 
vvvSourceRemeasurement 
VVVv20110718 
Ks mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
ksMagErr 
ultravistaSourceRemeasurement 
ULTRAVISTAv20100429 
Error in Ks mag 
real 
4 
mag 
0.9999995e9 
stat.error 
ksMagErr 
vhsSourceRemeasurement 
VHSDR1 
Error in Ks mag 
real 
4 
mag 
0.9999995e9 
stat.error 
ksMagErr 
videoSourceRemeasurement 
VIDEOv20100513 
Error in Ks mag 
real 
4 
mag 
0.9999995e9 
stat.error 
ksMagErr 
vikingSourceRemeasurement 
VIKINGv20110714 
Error in Ks mag 
real 
4 
mag 
0.9999995e9 
stat.error 
ksMagErr 
vikingSourceRemeasurement 
VIKINGv20111019 
Error in Ks mag 
real 
4 
mag 
0.9999995e9 
stat.error 
ksMagErr 
vmcCepheidVariables 
VMCDR3 
Error in mean Ks band magnitude {catalogue TType keyword: err_Ks} 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.K 
ksMagErr 
vmcCepheidVariables 
VMCv20121128 
Error in mean Ks band magnitude {catalogue TType keyword: err_Ks} 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
ksMagErr 
vmcCepheidVariables 
VMCv20140428 
Error in mean Ks band magnitude {catalogue TType keyword: err_Ks} 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
ksMagErr 
vmcCepheidVariables 
VMCv20140903 
Error in mean Ks band magnitude {catalogue TType keyword: err_Ks} 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.K 
ksMagErr 
vmcCepheidVariables 
VMCv20150309 
Error in mean Ks band magnitude {catalogue TType keyword: err_Ks} 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.K 
ksMagErr 
vmcSourceRemeasurement 
VMCv20110816 
Error in Ks mag 
real 
4 
mag 
0.9999995e9 
stat.error 
ksMagErr 
vmcSourceRemeasurement 
VMCv20110909 
Error in Ks mag 
real 
4 
mag 
0.9999995e9 
stat.error 
ksMagErr 
vvvSourceRemeasurement 
VVVv20100531 
Error in Ks mag 
real 
4 
mag 
0.9999995e9 
stat.error 
ksMagErr 
vvvSourceRemeasurement 
VVVv20110718 
Error in Ks mag 
real 
4 
mag 
0.9999995e9 
stat.error 
ksMagMAD 
videoVariability 
VIDEODR2 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
videoVariability 
VIDEODR3 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
videoVariability 
VIDEODR4 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.err;em.IR.K;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
videoVariability 
VIDEOv20100513 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
videoVariability 
VIDEOv20111208 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vikingVariability 
VIKINGDR2 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vikingVariability 
VIKINGv20110714 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vikingVariability 
VIKINGv20111019 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vmcVariability 
VMCDR1 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vmcVariability 
VMCDR2 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vmcVariability 
VMCDR3 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.err;em.IR.K;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vmcVariability 
VMCv20110816 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vmcVariability 
VMCv20110909 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vmcVariability 
VMCv20120126 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vmcVariability 
VMCv20121128 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vmcVariability 
VMCv20130304 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vmcVariability 
VMCv20130805 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vmcVariability 
VMCv20140428 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.err;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vmcVariability 
VMCv20140903 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.err;em.IR.K;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vmcVariability 
VMCv20150309 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.err;em.IR.K;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vvvVariability 
VVVDR1 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vvvVariability 
VVVDR2 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vvvVariability 
VVVv20100531 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagMAD 
vvvVariability 
VVVv20110718 
Median Absolute Deviation of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
videoVariability 
VIDEODR2 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
videoVariability 
VIDEODR3 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
videoVariability 
VIDEODR4 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
videoVariability 
VIDEOv20100513 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
videoVariability 
VIDEOv20111208 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vikingVariability 
VIKINGDR2 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vikingVariability 
VIKINGv20110714 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vikingVariability 
VIKINGv20111019 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vmcVariability 
VMCDR1 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vmcVariability 
VMCDR2 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vmcVariability 
VMCDR3 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vmcVariability 
VMCv20110816 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vmcVariability 
VMCv20110909 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vmcVariability 
VMCv20120126 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vmcVariability 
VMCv20121128 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vmcVariability 
VMCv20130304 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vmcVariability 
VMCv20130805 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vmcVariability 
VMCv20140428 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vmcVariability 
VMCv20140903 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vmcVariability 
VMCv20150309 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.K;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vvvVariability 
VVVDR1 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vvvVariability 
VVVDR2 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vvvVariability 
VVVv20100531 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMagRms 
vvvVariability 
VVVv20110718 
rms of Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMax 
vmcEclipsingBinaryVariables 
VMCv20140903 
Ks magnitude at maximum light, determined by fitting with GRATIS {catalogue TType keyword: KS_MAX} 
real 
4 
mag 

phot.mag;stat.max;em.IR.K 
ksMax 
vmcEclipsingBinaryVariables 
VMCv20150309 
Ks magnitude at maximum light, determined by fitting with GRATIS {catalogue TType keyword: KS_MAX} 
real 
4 
mag 

phot.mag;stat.max;em.IR.K 
ksmaxCadence 
videoVariability 
VIDEODR2 
maximum gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
videoVariability 
VIDEODR3 
maximum gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.max 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
videoVariability 
VIDEODR4 
maximum gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.max 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
videoVariability 
VIDEOv20100513 
maximum gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
videoVariability 
VIDEOv20111208 
maximum gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vikingVariability 
VIKINGDR2 
maximum gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vikingVariability 
VIKINGv20110714 
maximum gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vikingVariability 
VIKINGv20111019 
maximum gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vmcVariability 
VMCDR1 
maximum gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vmcVariability 
VMCDR2 
maximum gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.max 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vmcVariability 
VMCDR3 
maximum gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.max 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vmcVariability 
VMCv20110816 
maximum gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vmcVariability 
VMCv20110909 
maximum gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vmcVariability 
VMCv20120126 
maximum gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vmcVariability 
VMCv20121128 
maximum gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.max 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vmcVariability 
VMCv20130304 
maximum gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.max 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vmcVariability 
VMCv20130805 
maximum gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.max 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vmcVariability 
VMCv20140428 
maximum gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.max;em.IR.K 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vmcVariability 
VMCv20140903 
maximum gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.max 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vmcVariability 
VMCv20150309 
maximum gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.max 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vvvVariability 
VVVDR1 
maximum gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.max 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vvvVariability 
VVVDR2 
maximum gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.max 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vvvVariability 
VVVv20100531 
maximum gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmaxCadence 
vvvVariability 
VVVv20110718 
maximum gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksMaxErr 
vmcEclipsingBinaryVariables 
VMCv20140903 
Error on Ks magnitude at maximum light {catalogue TType keyword: ERROR} 
real 
4 
mag 

stat.error;phot.mag;em.IR.K 
ksMaxErr 
vmcEclipsingBinaryVariables 
VMCv20150309 
Error on Ks magnitude at maximum light {catalogue TType keyword: ERROR} 
real 
4 
mag 

stat.error;phot.mag;em.IR.K 
ksMaxMag 
videoVariability 
VIDEODR2 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
videoVariability 
VIDEODR3 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 
phot.mag;stat.max;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
videoVariability 
VIDEODR4 
Maximum magnitude in Ks band, of good detections 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
videoVariability 
VIDEOv20100513 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
videoVariability 
VIDEOv20111208 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vikingVariability 
VIKINGDR2 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vikingVariability 
VIKINGv20110714 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vikingVariability 
VIKINGv20111019 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vmcVariability 
VMCDR1 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vmcVariability 
VMCDR2 
Maximum magnitude in Ks band, of good detections 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vmcVariability 
VMCDR3 
Maximum magnitude in Ks band, of good detections 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vmcVariability 
VMCv20110816 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vmcVariability 
VMCv20110909 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vmcVariability 
VMCv20120126 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vmcVariability 
VMCv20121128 
Maximum magnitude in Ks band, of good detections 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.max;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vmcVariability 
VMCv20130304 
Maximum magnitude in Ks band, of good detections 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.max;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vmcVariability 
VMCv20130805 
Maximum magnitude in Ks band, of good detections 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vmcVariability 
VMCv20140428 
Maximum magnitude in Ks band, of good detections 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vmcVariability 
VMCv20140903 
Maximum magnitude in Ks band, of good detections 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vmcVariability 
VMCv20150309 
Maximum magnitude in Ks band, of good detections 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vvvVariability 
VVVDR1 
Maximum magnitude in Ks band, of good detections 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.max;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vvvVariability 
VVVDR2 
Maximum magnitude in Ks band, of good detections 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.max;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vvvVariability 
VVVv20100531 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMaxMag 
vvvVariability 
VVVv20110718 
Maximum magnitude in Ks band, of good detections 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksMeanMag 
vmcCepheidVariables 
VMCDR3 
Mean Ks band magnitude {catalogue TType keyword: Ks} 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.mean;em.IR.K 
ksMeanMag 
vmcCepheidVariables 
VMCv20121128 
Mean Ks band magnitude {catalogue TType keyword: Ks} 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.mean;em.IR.NIR 
ksMeanMag 
vmcCepheidVariables 
VMCv20140428 
Mean Ks band magnitude {catalogue TType keyword: Ks} 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.mean;em.IR.K 
ksMeanMag 
vmcCepheidVariables 
VMCv20140903 
Mean Ks band magnitude {catalogue TType keyword: Ks} 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.mean;em.IR.K 
ksMeanMag 
vmcCepheidVariables 
VMCv20150309 
Mean Ks band magnitude {catalogue TType keyword: Ks} 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.mean;em.IR.K 
ksmeanMag 
videoVariability 
VIDEODR2 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
videoVariability 
VIDEODR3 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.mean;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
videoVariability 
VIDEODR4 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.mean;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
videoVariability 
VIDEOv20100513 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
videoVariability 
VIDEOv20111208 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vikingVariability 
VIKINGDR2 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vikingVariability 
VIKINGv20110714 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vikingVariability 
VIKINGv20111019 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vmcVariability 
VMCDR1 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vmcVariability 
VMCDR2 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.mean;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vmcVariability 
VMCDR3 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.mean;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vmcVariability 
VMCv20110816 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vmcVariability 
VMCv20110909 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vmcVariability 
VMCv20120126 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vmcVariability 
VMCv20121128 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.mean;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vmcVariability 
VMCv20130304 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.mean;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vmcVariability 
VMCv20130805 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.mean;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vmcVariability 
VMCv20140428 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.mean;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vmcVariability 
VMCv20140903 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.mean;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vmcVariability 
VMCv20150309 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.mean;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vvvVariability 
VVVDR1 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.mean;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vvvVariability 
VVVDR2 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.mean;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vvvVariability 
VVVv20100531 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmeanMag 
vvvVariability 
VVVv20110718 
Mean Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedCadence 
videoVariability 
VIDEODR2 
median gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
videoVariability 
VIDEODR3 
median gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.median 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
videoVariability 
VIDEODR4 
median gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.median 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
videoVariability 
VIDEOv20100513 
median gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
videoVariability 
VIDEOv20111208 
median gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vikingVariability 
VIKINGDR2 
median gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vikingVariability 
VIKINGv20110714 
median gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vikingVariability 
VIKINGv20111019 
median gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vmcVariability 
VMCDR1 
median gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vmcVariability 
VMCDR2 
median gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.median 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vmcVariability 
VMCDR3 
median gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.median 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vmcVariability 
VMCv20110816 
median gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vmcVariability 
VMCv20110909 
median gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vmcVariability 
VMCv20120126 
median gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vmcVariability 
VMCv20121128 
median gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.median 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vmcVariability 
VMCv20130304 
median gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.median 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vmcVariability 
VMCv20130805 
median gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.median 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vmcVariability 
VMCv20140428 
median gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.median;em.IR.K 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vmcVariability 
VMCv20140903 
median gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.median 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vmcVariability 
VMCv20150309 
median gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.median 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vvvVariability 
VVVDR1 
median gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.median 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vvvVariability 
VVVDR2 
median gap between observations 
real 
4 
days 
0.9999995e9 
time.interval;obs;stat.median 
The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vvvVariability 
VVVv20100531 
median gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedCadence 
vvvVariability 
VVVv20110718 
median gap between observations 
real 
4 
days 
0.9999995e9 

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable. 
ksmedianMag 
videoVariability 
VIDEODR2 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
videoVariability 
VIDEODR3 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.median;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
videoVariability 
VIDEODR4 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.median;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
videoVariability 
VIDEOv20100513 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
videoVariability 
VIDEOv20111208 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vikingVariability 
VIKINGDR2 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vikingVariability 
VIKINGv20110714 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vikingVariability 
VIKINGv20111019 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vmcVariability 
VMCDR1 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vmcVariability 
VMCDR2 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.median;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vmcVariability 
VMCDR3 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.median;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vmcVariability 
VMCv20110816 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vmcVariability 
VMCv20110909 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vmcVariability 
VMCv20120126 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vmcVariability 
VMCv20121128 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.median;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vmcVariability 
VMCv20130304 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.median;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vmcVariability 
VMCv20130805 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.median;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vmcVariability 
VMCv20140428 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.median;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vmcVariability 
VMCv20140903 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.median;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vmcVariability 
VMCv20150309 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.median;em.IR.K 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vvvVariability 
VVVDR1 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.median;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vvvVariability 
VVVDR2 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.K;stat.median;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vvvVariability 
VVVv20100531 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmedianMag 
vvvVariability 
VVVv20110718 
Median Ks magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ksmfID 
svNgc253MergeLog 
SVNGC253v20100429 
the UID of the relevant Ks multiframe 
bigint 
8 


obs.field 
ksmfID 
svOrionMergeLog 
SVORIONv20100429 
the UID of the relevant Ks multiframe 
bigint 
8 


obs.field 
ksmfID 
ultravistaMergeLog 
ULTRAVISTAv20100429 
the UID of the relevant Ks multiframe 
bigint 
8 


obs.field 
ksmfID 
vhsMergeLog 
VHSDR1 
the UID of the relevant Ks multiframe 
bigint 