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### Glossary of WSA attributes

##### This Glossary alphabetically lists all attributes used in the UKIDSSDR11 database(s) held in the WSA. If you would like to have more information about the schema tables please use the UKIDSSDR11Schema Browser (other Browser versions).
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### N

NameSchema TableDatabaseDescriptionTypeLengthUnitDefault ValueUnified Content Descriptor
N1 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Possible number of detections for band 1 int 4   -9
N2 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Possible number of detections for band 2 int 4   -9
N3 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Possible number of detections for band 3 int 4   -9
N3_6 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Number of possible detections for 3.6um IRAC (Band 1) int 4   -9
N4 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Possible number of detections for band 4 int 4   -9
N4_5 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Number of possible detections for 4.5um IRAC (Band 2) int 4   -9
N5_8 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Number of possible detections for 5.8um IRAC (Band 3) int 4   -9
N8_0 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Number of possible detections for 8.0um IRAC (Band 4) int 4   -9
n_2mass allwise_sc2 WISE The number of 2MASS PSC entries found within a 3" radius of the WISE source position. If more than one 2MASS PSC falls within 3" of the WISE position, the closest 2MASS PSC entry is listed. This column is zero if there is no associated 2MASS PSC source. int 4
n_blank twomass_xsc 2MASS number of blanked source records. smallint 2     NUMBER
N_DETECTIONS twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM The number of detections of the unique source SRCID used to derive the averaged values. int 4
N_DETECTIONS xmm3dr4 XMM The number of detections of the unique source SRCID used to derive the averaged values. smallint 2
n_ext twomass_scn 2MASS Number of regular extended sources detected in scan. int 4     NUMBER
n_ext twomass_sixx2_scn 2MASS number of regular extended sources detected in scan int 4
N_SPEC mgcBrightSpec MGC Total number of spectra for this object smallint 2
n_sub twomass_xsc 2MASS number of subtracted source records. smallint 2     NUMBER
na allwise_sc2 WISE Active deblending flag. Indicates if a single detection was split into multiple sources in the process of profile-fitting: 0 - the source is not actively deblended; 1 - the source is actively deblended. int 4
name Filter WSA The name of the filter, eg. "MKO J", "WFCAM Y" etc. varchar 16     meta.note
name Filter WSACalib The name of the filter, eg. "MKO J", "WFCAM Y" etc. varchar 16     meta.note
name Filter WSATransit The name of the filter, eg. "MKO J", "WFCAM Y" etc. varchar 16     meta.note
name Filter WSAUHS The name of the filter, eg. "MKO J", "WFCAM Y" etc. varchar 16     meta.note
name RequiredMergeLogMultiEpoch WSAUHS Name of the stacked product varchar 64     ??
name RequiredMergeLogMultiEpoch, RequiredStack WSA Name of the stacked product varchar 64     ??
name RequiredMosaic WSA Name of the mosaiced product varchar 64     ??
name RequiredMosaic WSACalib Name of the mosaiced product varchar 64     ??
name RequiredMosaic WSATransit Name of the mosaiced product varchar 64     ??
name RequiredMosaic WSAUHS Name of the mosaiced product varchar 64     ??
name Survey WSA The short name for the survey varchar 128     ??
name Survey WSACalib The short name for the survey varchar 128     ??
name Survey WSATransit The short name for the survey varchar 128     ??
name Survey WSAUHS The short name for the survey varchar 128     ??
name iras_asc, iras_psc IRAS Source Name varchar 11     ID_MAIN
name ukirtFSstars WSA reference name of field varchar 16   NONE ????
name ukirtFSstars WSACalib reference name of field varchar 16   NONE ????
name ukirtFSstars WSAUHS reference name of field varchar 16   NONE ????
nb allwise_sc2 WISE Number of PSF components used simultaneously in the profile-fitting for this source. This number includes the source itself, so the minimum value of nb is "1". Nb is greater than "1" when the source is fit concurrently with other nearby detections (passive deblending), or when a single source is split into two components during the fitting process (active deblending). int 4
nbjAperMag1 calSynopticSource WSACalib Extended source Nbj aperture corrected mag (1.0 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG
nbjAperMag1Err calSynopticSource WSACalib Error in extended source Nbj mag (1.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR
nbjAperMag2 calSynopticSource WSACalib Extended source Nbj aperture corrected mag (1.4 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG
nbjAperMag2Err calSynopticSource WSACalib Error in extended source Nbj mag (1.4 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR
nbjAperMag3 calSource WSACalib Default point/extended source Nbj aperture corrected mag (2.0 arcsec aperture diameter)
If in doubt use this flux estimator
real 4 mag -0.9999995e9 PHOT_MAG
nbjAperMag3 calSynopticSource WSACalib Default point/extended source Nbj aperture corrected mag (2.0 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG
nbjAperMag3Err calSource, calSynopticSource WSACalib Error in default point/extended source Nbj mag (2.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR
nbjAperMag4 calSource, calSynopticSource WSACalib Extended source Nbj aperture corrected mag (2.8 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG
nbjAperMag4Err calSource, calSynopticSource WSACalib Error in extended source Nbj mag (2.8 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR
nbjAperMag5 calSynopticSource WSACalib Extended source Nbj aperture corrected mag (4.0 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG
nbjAperMag5Err calSynopticSource WSACalib Error in extended source Nbj mag (4.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR
nbjAperMag6 calSource WSACalib Extended source Nbj aperture corrected mag (5.7 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG
nbjAperMag6Err calSource WSACalib Error in extended source Nbj mag (5.7 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR
nbjaStratAst calVarFrameSetInfo WSACalib Strateva parameter, a, in fit to astrometric rms vs magnitude in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.
nbjaStratPht calVarFrameSetInfo WSACalib Strateva parameter, a, in fit to photometric rms vs magnitude in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.
nbjbestAper calVariability WSACalib Best aperture (1-6) for photometric statistics in the Nbj band int 4   -9999
Aperture magnitude (1-6) 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)
nbjbStratAst calVarFrameSetInfo WSACalib Strateva parameter, b, in fit to astrometric rms vs magnitude in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.
nbjbStratPht calVarFrameSetInfo WSACalib Strateva parameter, b, in fit to photometric rms vs magnitude in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.
nbjchiSqAst calVarFrameSetInfo WSACalib Goodness of fit of Strateva function to astrometric data in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.
nbjchiSqpd calVariability WSACalib 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjchiSqPht calVarFrameSetInfo WSACalib Goodness of fit of Strateva function to photometric data in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.
nbjClass calSource, calSynopticSource WSACalib discrete image classification flag in Nbj smallint 2   -9999 CLASS_MISC
nbjClassStat calSource, calSynopticSource WSACalib N(0,1) stellarness-of-profile statistic in Nbj real 4   -0.9999995e9 STAT_PROP
nbjcStratAst calVarFrameSetInfo WSACalib Strateva parameter, c, in fit to astrometric rms vs magnitude in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.
nbjcStratPht calVarFrameSetInfo WSACalib Strateva parameter, c, in fit to photometric rms vs magnitude in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.
nbjDeblend calSource WSACalib placeholder flag indicating parent/child relation in Nbj int 4   -99999999 CODE_MISC
This CASU pipeline processing source extraction flag is a placeholder only, and is always set to zero in all passbands in the merged source lists. If you need to know when a particular image detection is a component of a deblend or not, test bit 4 of attribute ppErrBits (see corresponding glossary entry) which is set by WFAU's post-processing software based on testing the areal profiles aprof2-8 (these are set by CASU to -1 for deblended components, or positive values for non-deblended detections). We encode this in an information bit of ppErrBits for convenience when querying the merged source tables.
nbjDeblend calSynopticSource WSACalib placeholder flag indicating parent/child relation in Nbj int 4   -99999999 CODE_MISC
nbjEll calSource, calSynopticSource WSACalib 1-b/a, where a/b=semi-major/minor axes in Nbj real 4   -0.9999995e9 PHYS_ELLIPTICITY
nbjeNum calMergeLog, calSynopticMergeLog WSACalib the extension number of this Nbj frame tinyint 1     NUMBER
nbjErrBits calSource, calSynopticSource WSACalib processing warning/error bitwise flags in Nbj int 4   -99999999 CODE_MISC
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture.
nbjEta calSource, calSynopticSource WSACalib Offset of Nbj detection from master position (+north/-south) real 4 arcsec -0.9999995e9 POS_EQ_DEC_OFF
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 2.0 (UKIDSS LAS and GPS; UHS; also non-survey programmes) or 1.0 (UKIDSS GPS, DXS and UDS) arcseconds is used, the higher value enabling pairing of moving sources when epoch separations may be several years. 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 LAS, you might wish to insist that the offsets in the selected sample are all below 1 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.
nbjexpML calVarFrameSetInfo WSACalib Expected magnitude limit of frameSet in this in Nbj band. real 4   -0.9999995e9
The expected magnitude limit of an intermediate stack, based on the total exposure time. expML=Filter.oneSecML+1.25*log10(totalExpTime). Since different intermediate stacks can have different exposure times, the totalExpTime is the minimum, as long as the number of stacks with this minimum make up 10% of the total. This is a more conservative treatment than just taking the mean or median total exposure time.
nbjExpRms calVariability WSACalib Rms calculated from polynomial fit to modal RMS as a function of magnitude in Nbj 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjGausig calSource, calSynopticSource WSACalib RMS of axes of ellipse fit in Nbj real 4 pixels -0.9999995e9 MORPH_PARAM
nbjHallMag calSource WSACalib Total point source Nbj mag real 4 mag -0.9999995e9 PHOT_MAG
nbjHallMagErr calSource WSACalib Error in total point source Nbj mag real 4 mag -0.9999995e9 ERROR
nbjIntRms calVariability WSACalib Intrinsic rms in Nbj-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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjisDefAst calVarFrameSetInfo WSACalib Use a default model for the astrometric noise in Nbj band. tinyint 1   0
nbjisDefPht calVarFrameSetInfo WSACalib Use a default model for the photometric noise in Nbj band. tinyint 1   0
nbjMagMAD calVariability WSACalib Median Absolute Deviation of Nbj 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjMagRms calVariability WSACalib rms of Nbj 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjmaxCadence calVariability WSACalib 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.
nbjMaxMag calVariability WSACalib Maximum magnitude in Nbj 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjmeanMag calVariability WSACalib Mean Nbj 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjmedCadence calVariability WSACalib 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.
nbjmedianMag calVariability WSACalib Median Nbj 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjmfID calMergeLog, calSynopticMergeLog WSACalib the UID of the relevant Nbj multiframe bigint 8     ID_FRAME
nbjminCadence calVariability WSACalib minimum 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.
nbjMinMag calVariability WSACalib Minimum magnitude in Nbj 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjmjExt calSource WSACalib Extended source colour Nbj-J (using aperMag3) real 4 mag -0.9999995e9 PHOT_COLOR
Default colours from pairs of adjacent passbands within a given set (e.g. Y-J, J-H and H-K for YJHK) are recorded in the merged source table for ease of querying and speedy querying via indexing of these attributes. Presently, the point-source colours and extended source colours are computed from the aperture corrected AperMag3 fixed 2 arcsec aperture diameter measures (for consistent measurement across all passbands) and generally good signal-to-noise. At some point in the future, this may be changed such that point-source colours will be computed from the PSF-fitted measures and extended source colours computed from the 2-d Sersic model profile fits.
nbjmjExtErr calSource WSACalib Error on extended source colour Nbj-J real 4 mag -0.9999995e9 ERROR
Default colours from pairs of adjacent passbands within a given set (e.g. Y-J, J-H and H-K for YJHK) are recorded in the merged source table for ease of querying and speedy querying via indexing of these attributes. Presently, the point-source colours and extended source colours are computed from the aperture corrected AperMag3 fixed 2 arcsec aperture diameter measures (for consistent measurement across all passbands) and generally good signal-to-noise. At some point in the future, this may be changed such that point-source colours will be computed from the PSF-fitted measures and extended source colours computed from the 2-d Sersic model profile fits.
nbjmjPnt calSource, calSynopticSource WSACalib Point source colour Nbj-J (using aperMag3) real 4 mag -0.9999995e9 PHOT_COLOR
Default colours from pairs of adjacent passbands within a given set (e.g. Y-J, J-H and H-K for YJHK) are recorded in the merged source table for ease of querying and speedy querying via indexing of these attributes. Presently, the point-source colours and extended source colours are computed from the aperture corrected AperMag3 fixed 2 arcsec aperture diameter measures (for consistent measurement across all passbands) and generally good signal-to-noise. At some point in the future, this may be changed such that point-source colours will be computed from the PSF-fitted measures and extended source colours computed from the 2-d Sersic model profile fits.
nbjmjPntErr calSource, calSynopticSource WSACalib Error on point source colour Nbj-J real 4 mag -0.9999995e9 ERROR
Default colours from pairs of adjacent passbands within a given set (e.g. Y-J, J-H and H-K for YJHK) are recorded in the merged source table for ease of querying and speedy querying via indexing of these attributes. Presently, the point-source colours and extended source colours are computed from the aperture corrected AperMag3 fixed 2 arcsec aperture diameter measures (for consistent measurement across all passbands) and generally good signal-to-noise. At some point in the future, this may be changed such that point-source colours will be computed from the PSF-fitted measures and extended source colours computed from the 2-d Sersic model profile fits.
nbjndof calVariability WSACalib Number of degrees of freedom for chisquare smallint 2   -9999
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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjnDofAst calVarFrameSetInfo WSACalib Number of degrees of freedom of astrometric fit in Nbj band. smallint 2   -9999
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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.
nbjnDofPht calVarFrameSetInfo WSACalib Number of degrees of freedom of photometric fit in Nbj band. smallint 2   -9999
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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.
nbjnFlaggedObs calVariability WSACalib Number of detections in Nbj band flagged as potentially spurious by calDetection.ppErrBits int 4   0
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.
nbjnGoodObs calVariability WSACalib Number of good detections in Nbj band int 4   0
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.
nbjNgt3sig calVariability WSACalib Number of good detections in Nbj-band that are more than 3 sigma deviations smallint 2   -9999
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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjnMissingObs calVariability WSACalib Number of Nbj band frames that this object should have been detected on and was not int 4   0
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.
nbjPA calSource, calSynopticSource WSACalib ellipse fit celestial orientation in Nbj real 4 Degrees -0.9999995e9 POS_POS-ANG
nbjPetroMag calSource WSACalib Extended source Nbj mag (Petrosian) real 4 mag -0.9999995e9 PHOT_MAG
nbjPetroMagErr calSource WSACalib Error in extended source Nbj mag (Petrosian) real 4 mag -0.9999995e9 ERROR
nbjppErrBits calSource, calSynopticSource WSACalib additional WFAU post-processing error bits in Nbj int 4   0 CODE_MISC
Post-processing error quality bit flags assigned (NB: from UKIDSS DR2 release onwards) in the WSA curation procedure for survey data. From least to most significant byte in the 4-byte integer attribute byte 0 (bits 0 to 7) corresponds to information on generally innocuous conditions that are nonetheless potentially significant as regards the integrity of that detection; byte 1 (bits 8 to 15) corresponds to warnings; byte 2 (bits 16 to 23) corresponds to important warnings; and finally byte 3 (bits 24 to 31) corresponds to severe warnings:
 Byte Bit Detection quality issue Threshold or bit mask Applies to Decimal Hexadecimal 0 4 Deblended 16 0x00000010 All VDFS catalogues 0 6 Bad pixel(s) in default aperture 64 0x00000040 All VDFS catalogues 1 15 Source in poor flat field region 32768 0x00008000 All but mosaics 2 16 Close to saturated 65536 0x00010000 All VDFS catalogues (though deeps excluded prior to DR8) 2 17 Photometric calibration probably subject to systematic error 131072 0x00020000 GPS only 2 19 Possible crosstalk artefact/contamination 524288 0x00080000 All but GPS 2 22 Lies within a dither offset of the stacked frame boundary 4194304 0x00400000 All but mosaics

In this way, the higher the error quality bit flag value, the more likely it is that the detection is spurious. The decimal threshold (column 4) gives the minimum value of the quality flag for a detection having the given condition (since other bits in the flag may be set also; the corresponding hexadecimal value, where each digit corresponds to 4 bits in the flag, can be easier to compute when writing SQL queries to test for a given condition). For example, to exclude all K band sources in the LAS having any error quality condition other than informational ones, include a predicate ... AND kppErrBits ≤ 255. See the SQL Cookbook and other online pages for further information.
nbjprobVar calVariability WSACalib Probability of variable from chi-square (and other data) 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjPsfMag calSource WSACalib Point source profile-fitted Nbj mag real 4 mag -0.9999995e9 PHOT_MAG
nbjPsfMagErr calSource WSACalib Error in point source profile-fitted Nbj mag real 4 mag -0.9999995e9 ERROR
nbjSeqNum calSource, calSynopticSource WSACalib the running number of the Nbj detection int 4   -99999999 ID_NUMBER
nbjSerMag2D calSource WSACalib Extended source Nbj mag (profile-fitted) real 4 mag -0.9999995e9 PHOT_MAG
nbjSerMag2DErr calSource WSACalib Error in extended source Nbj mag (profile-fitted) real 4 mag -0.9999995e9 ERROR
nbjskewness calVariability WSACalib Skewness in Nbj band (see Sesar et al. 2007) 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjtotalPeriod calVariability WSACalib total period of observations (last obs-first obs) 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.
nbjVarClass calVariability WSACalib Classification of variability in this band smallint 2   -9999
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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.
nbjXi calSource, calSynopticSource WSACalib Offset of Nbj detection from master position (+east/-west) real 4 arcsec -0.9999995e9 POS_EQ_RA_OFF
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 2.0 (UKIDSS LAS and GPS; UHS; also non-survey programmes) or 1.0 (UKIDSS GPS, DXS and UDS) arcseconds is used, the higher value enabling pairing of moving sources when epoch separations may be several years. 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 LAS, you might wish to insist that the offsets in the selected sample are all below 1 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.
nc hipparcos_new_reduction GAIADR1 Number of components int 4     meta.number
ndet twomass_psc 2MASS Frame detection statistics. varchar 6     NUMBER
ndet twomass_sixx2_psc 2MASS number of >3-sig. ap. mag measurements, # possible (jjhhkk) varchar 6
NED_CLASS mgcBrightSpec MGC MGC translation of NED_IDENT smallint 2
NED_DEC mgcBrightSpec MGC NED object declination in deg (J2000) float 8
NED_IDENT mgcBrightSpec MGC NED identification varchar 4
NED_N mgcBrightSpec MGC Number of NED objects matched to this MGC object smallint 2
NED_NAME mgcBrightSpec MGC NED object name varchar 32
NED_RA mgcBrightSpec MGC NED object right ascension in deg (J2000) float 8
NED_ZHELIO mgcBrightSpec MGC NED heliocentric redshift real 4
NED_ZQUAL mgcBrightSpec MGC NED redshift quality tinyint 1
neighboursSchema Programme WSA Script file that describes the neighbour tables schema for this programme varchar 64     ??
neighboursSchema Programme WSACalib Script file that describes the neighbour tables schema for this programme varchar 64     ??
neighboursSchema Programme WSATransit Script file that describes the neighbour tables schema for this programme varchar 64     ??
neighboursSchema Programme WSAUHS Script file that describes the neighbour tables schema for this programme varchar 64     ??
neighbourTable RequiredNeighbours WSA the name of the neighbour join table varchar 256     meta.id;meta.dataset
neighbourTable RequiredNeighbours WSACalib the name of the neighbour join table varchar 256     meta.id;meta.dataset
neighbourTable RequiredNeighbours WSATransit the name of the neighbour join table varchar 256     meta.id;meta.dataset
neighbourTable RequiredNeighbours WSAUHS the name of the neighbour join table varchar 256     meta.id;meta.dataset
newBrframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newFrameSet calMergeLog, calSynopticMergeLog WSACalib Flag used internally by curation applications tinyint 1     CODE_MISC
newFrameSet dxsJKmergeLog, dxsMergeLog, gcsMergeLog, gcsZYJHKmergeLog, gpsJHKmergeLog, gpsMergeLog, lasMergeLog, lasYJHKmergeLog, udsMergeLog WSA Flag used internally by curation applications tinyint 1     CODE_MISC
newFrameSet uhsMergeLog WSAUHS Flag used internally by curation applications tinyint 1     CODE_MISC
newH2frame calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newH2frame gpsJHKmergeLog, gpsMergeLog WSA new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newHframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newHframe dxsJKmergeLog, dxsMergeLog, gcsMergeLog, gcsZYJHKmergeLog, gpsJHKmergeLog, gpsMergeLog, lasMergeLog, lasYJHKmergeLog, udsMergeLog WSA new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newJ_1frame lasMergeLog, lasYJHKmergeLog WSA new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newJ_2frame lasMergeLog, lasYJHKmergeLog WSA new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newJframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newJframe dxsJKmergeLog, dxsMergeLog, gcsMergeLog, gcsZYJHKmergeLog, gpsJHKmergeLog, gpsMergeLog, lasMergeLog, lasYJHKmergeLog, udsMergeLog WSA new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newJframe uhsMergeLog WSAUHS new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newK_1frame gcsMergeLog, gcsZYJHKmergeLog, gpsJHKmergeLog, gpsMergeLog WSA new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newK_2frame gcsMergeLog, gcsZYJHKmergeLog, gpsJHKmergeLog, gpsMergeLog WSA new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newKframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newKframe dxsJKmergeLog, dxsMergeLog, gcsMergeLog, gcsZYJHKmergeLog, gpsJHKmergeLog, gpsMergeLog, lasMergeLog, lasYJHKmergeLog, udsMergeLog WSA new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newlyIngested Multiframe WSA Curation flag for internal use only (0=no, 1=yes) tinyint 1   1 ??
newlyIngested Multiframe WSACalib Curation flag for internal use only (0=no, 1=yes) tinyint 1   1 ??
newlyIngested Multiframe WSATransit Curation flag for internal use only (0=no, 1=yes) tinyint 1   1 ??
newlyIngested Multiframe WSAUHS Curation flag for internal use only (0=no, 1=yes) tinyint 1   1 ??
newNbjframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newYframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newYframe gcsMergeLog, gcsZYJHKmergeLog, lasMergeLog, lasYJHKmergeLog WSA new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newZframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
newZframe gcsMergeLog, gcsZYJHKmergeLog WSA new/old flag (1/0) of this detector image tinyint 1     CODE_MISC
nFlag rosat_bsc, rosat_fsc ROSAT nearby sources affecting SASS flux determination varchar 1     CODE_MISC
nFoc Multiframe WSA Number of positions in focus scan {image primary HDU keyword: NFOC} smallint 2   -9999 meta.number
nFoc Multiframe WSACalib Number of positions in focus scan {image primary HDU keyword: NFOC} smallint 2   -9999 meta.number
nFoc Multiframe WSATransit Number of positions in focus scan {image primary HDU keyword: NFOC} smallint 2   -9999 meta.number
nFoc Multiframe WSAUHS Number of positions in focus scan {image primary HDU keyword: NFOC} smallint 2   -9999 meta.number
nFocScan Multiframe WSA Number of focus scans in focus test {image primary HDU keyword: NFOCSCAN} smallint 2   -9999 meta.number
nFocScan Multiframe WSACalib Number of focus scans in focus test {image primary HDU keyword: NFOCSCAN} smallint 2   -9999 meta.number
nFocScan Multiframe WSATransit Number of focus scans in focus test {image primary HDU keyword: NFOCSCAN} smallint 2   -9999 meta.number
nFocScan Multiframe WSAUHS Number of focus scans in focus test {image primary HDU keyword: NFOCSCAN} smallint 2   -9999 meta.number
nFrames calVariability WSACalib Number of frames with good detections used to calculate astrometric fits int 4   0 NUMBER
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
nFrames dxsVariability, gcsVariability, gpsVariability, lasVariability, udsVariability WSA Number of frames with good detections used to calculate astrometric fits int 4   0 NUMBER
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
nFrames gcsPointSource, gcsSource, gcsZYJHKsource, gpsJHKsource, gpsPointSource, gpsSource, lasExtendedSource, lasPointSource, lasSource, lasYJHKsource, reliableGcsPointSource, reliableGpsPointSource, reliableLasPointSource WSA No. of frames used for this proper motion measurement tinyint 1   0 NUMBER
ngrp allwise_sc2 WISE Excess number of positionally associated duplicate resolution groups in which this extractions was included. Values of ngrp>0 indicate that the source was associated with more than one possible group. CAUTION: In the All-Sky Release Catalog and 3-Band Cryo Source Working Database, this column indicated the total number of groups with which a source was associated. In the AllWISE Catalog and Reject Table, ngrp is the total number of groups minus one. smallint 2
nhcon iras_psc IRAS Number of times observed (<25) tinyint 1     NUMBER
nId iras_psc IRAS Number of positional associations (<25). tinyint 1     NUMBER
night_key twomass_xsc 2MASS key to night data record in "scan DB". smallint 2     ID_NUMBER
nightZPCat MultiframeDetector WSA Average photometric zero point for night {catalogue extension keyword:  NIGHTZPT} real 4 mags -0.9999995e9 ??
nightZPCat MultiframeDetector WSACalib Average photometric zero point for night {catalogue extension keyword:  NIGHTZPT} real 4 mags -0.9999995e9 ??
nightZPCat MultiframeDetector WSATransit Average photometric zero point for night {catalogue extension keyword:  NIGHTZPT} real 4 mags -0.9999995e9 ??
nightZPCat MultiframeDetector WSAUHS Average photometric zero point for night {catalogue extension keyword:  NIGHTZPT} real 4 mags -0.9999995e9 ??
nightZPCat PreviousMFDZP WSA Average photometric zero point for night real 4 mags -0.9999995e9 ??
nightZPCat PreviousMFDZP WSACalib Average photometric zero point for night real 4 mags -0.9999995e9 ??
nightZPCat PreviousMFDZP WSAUHS Average photometric zero point for night real 4 mags -0.9999995e9 ??
nightZPErrCat MultiframeDetector WSA Photometric zero point sigma for night {catalogue extension keyword:  NIGHTZRR}
<0.05 mags for a good night
real 4 mags -0.9999995e9 ??
nightZPErrCat MultiframeDetector WSACalib Photometric zero point sigma for night {catalogue extension keyword:  NIGHTZRR}
<0.05 mags for a good night
real 4 mags -0.9999995e9 ??
nightZPErrCat MultiframeDetector WSATransit Photometric zero point sigma for night {catalogue extension keyword:  NIGHTZRR}
<0.05 mags for a good night
real 4 mags -0.9999995e9 ??
nightZPErrCat MultiframeDetector WSAUHS Photometric zero point sigma for night {catalogue extension keyword:  NIGHTZRR}
<0.05 mags for a good night
real 4 mags -0.9999995e9 ??
nightZPErrCat PreviousMFDZP WSA Photometric zero point sigma for night
<0.05 mags for a good night
real 4 mags -0.9999995e9 ??
nightZPErrCat PreviousMFDZP WSACalib Photometric zero point sigma for night
<0.05 mags for a good night
real 4 mags -0.9999995e9 ??
nightZPErrCat PreviousMFDZP WSAUHS Photometric zero point sigma for night
<0.05 mags for a good night
real 4 mags -0.9999995e9 ??
nightZPNum MultiframeDetector WSA Number of ZP in band used to calculate nightZPCat {catalogue extension keyword:  NIGHTNUM} int 4 mags -99999999 ??
nightZPNum MultiframeDetector WSACalib Number of ZP in band used to calculate nightZPCat {catalogue extension keyword:  NIGHTNUM} int 4 mags -99999999 ??
nightZPNum MultiframeDetector WSATransit Number of ZP in band used to calculate nightZPCat {catalogue extension keyword:  NIGHTNUM} int 4 mags -99999999 ??
nightZPNum MultiframeDetector WSAUHS Number of ZP in band used to calculate nightZPCat {catalogue extension keyword:  NIGHTNUM} int 4 mags -99999999 ??
nightZPNum PreviousMFDZP WSA Number of ZP in band used to calculate nightZPCat int 4 mags -99999999 ??
nightZPNum PreviousMFDZP WSACalib Number of ZP in band used to calculate nightZPCat int 4 mags -99999999 ??
nightZPNum PreviousMFDZP WSAUHS Number of ZP in band used to calculate nightZPCat int 4 mags -99999999 ??
njitter Multiframe WSA Number of positions in telescope pattern {image primary HDU keyword: NJITTER} smallint 2   -9999 meta.number
njitter Multiframe WSACalib Number of positions in telescope pattern {image primary HDU keyword: NJITTER} smallint 2   -9999 meta.number
njitter Multiframe WSATransit Number of positions in telescope pattern {image primary HDU keyword: NJITTER} smallint 2   -9999 meta.number
njitter Multiframe WSAUHS Number of positions in telescope pattern {image primary HDU keyword: NJITTER} smallint 2   -9999 meta.number
nLrs iras_psc IRAS Number of significant LRS spectra tinyint 1     NUMBER
nonperp dxsAstrometricInfo, gcsAstrometricInfo, gpsAstrometricInfo, lasAstrometricInfo, udsAstrometricInfo WSA Non-perpendicularity of axes float 8 radians -0.9999995e9 ??
nonperp uhsAstrometricInfo WSAUHS Non-perpendicularity of axes float 8 radians -0.9999995e9 ??
nopt_mchs twomass_psc 2MASS The number of USNO-A2.0 or Tycho 2 optical sources found within a 5" radius of the TWOMASS position. smallint 2     NUMBER
nPass RequiredFilters WSA the number of passes that will be made smallint 2     meta.number
nPass RequiredFilters WSACalib the number of passes that will be made smallint 2     meta.number
nPass RequiredFilters WSATransit the number of passes that will be made smallint 2     meta.number
nPass RequiredFilters WSAUHS the number of passes that will be made smallint 2     meta.number
ntr hipparcos_new_reduction GAIADR1 Number of field transits used int 4     meta.id;obs.field
num tycho2 GAIADR1 NUmber of positions used smallint 2     meta.number
num_harmonics_for_p1 cepheid, rrlyrae GAIADR1 Number of harmonics used to model P1 of the light curve int 4     meta.number
num_observations_processed phot_variable_time_series_g_fov_statistical_parameters GAIADR1 Number of processed G-band observations for variability analysis int 4     meta.number
numAxes MultiframeDetector WSA Number of data axes; eg. 2 tinyint 1     meta.number
numAxes MultiframeDetector WSACalib Number of data axes; eg. 2 tinyint 1     meta.number
numAxes MultiframeDetector WSATransit Number of data axes; eg. 2 tinyint 1     meta.number
numAxes MultiframeDetector WSAUHS Number of data axes; eg. 2 tinyint 1     meta.number
numberStk RequiredStack WSA Number of intermediate stacks. If default, stack all good quality stacks int 4   -99999999
numberStk RequiredStack WSACalib Number of intermediate stacks. If default, stack all good quality stacks int 4   -99999999
numberStk RequiredStack WSATransit Number of intermediate stacks. If default, stack all good quality stacks int 4   -99999999
numberStk RequiredStack WSAUHS Number of intermediate stacks. If default, stack all good quality stacks int 4   -99999999
numDetectors Multiframe WSA The number of "detectors" (=image extensions in FITS file) tinyint 1     ??
numDetectors Multiframe WSACalib The number of "detectors" (=image extensions in FITS file) tinyint 1     ??
numDetectors Multiframe WSATransit The number of "detectors" (=image extensions in FITS file) tinyint 1     ??
numDetectors Multiframe WSAUHS The number of "detectors" (=image extensions in FITS file) tinyint 1     ??
numExp Multiframe WSA Number of exposures in integration {image primary HDU keyword: NEXP} smallint 2   -9999 meta.number
numExp Multiframe WSACalib Number of exposures in integration {image primary HDU keyword: NEXP} smallint 2   -9999 meta.number
numExp Multiframe WSATransit Number of exposures in integration {image primary HDU keyword: NEXP} smallint 2   -9999 meta.number
numExp Multiframe WSAUHS Number of exposures in integration {image primary HDU keyword: NEXP} smallint 2   -9999 meta.number
numInts Multiframe WSA Number of integrations in observation {image primary HDU keyword: NINT} smallint 2     meta.number
numInts Multiframe WSACalib Number of integrations in observation {image primary HDU keyword: NINT} smallint 2     meta.number
numInts Multiframe WSATransit Number of integrations in observation {image primary HDU keyword: NINT} smallint 2     meta.number
numInts Multiframe WSAUHS Number of integrations in observation {image primary HDU keyword: NINT} smallint 2     meta.number
numReads Multiframe WSA Number of reads per exposure {image primary HDU keyword: NREADS} smallint 2   -9999 meta.number
numReads Multiframe WSACalib Number of reads per exposure {image primary HDU keyword: NREADS} smallint 2   -9999 meta.number
numReads Multiframe WSATransit Number of reads per exposure {image primary HDU keyword: NREADS} smallint 2   -9999 meta.number
numReads Multiframe WSAUHS Number of reads per exposure {image primary HDU keyword: NREADS} smallint 2   -9999 meta.number
numRms CurrentAstrometry WSACalib No. of astrometric standards used in fit {image extension keyword: NUMBRMS} int 4   -99999999 stat.fit.param
numRms CurrentAstrometry WSATransit No. of astrometric standards used in fit {image extension keyword: NUMBRMS} int 4   -99999999 stat.fit.param
numRms CurrentAstrometry WSAUHS No. of astrometric standards used in fit {image extension keyword: NUMBRMS} int 4   -99999999 stat.fit.param
numRms CurrentAstrometry, PreviousAstrometry WSA No. of astrometric standards used in fit {image extension keyword: NUMBRMS} int 4   -99999999 stat.fit.param
numZPCat MultiframeDetector WSA Number of standards used in determining photZPCat and photZPCatErr {catalogue extension keyword:  NUMZPT} int 4   -99999999
numZPCat MultiframeDetector WSACalib Number of standards used in determining photZPCat and photZPCatErr {catalogue extension keyword:  NUMZPT} int 4   -99999999
numZPCat MultiframeDetector WSATransit Number of standards used in determining photZPCat and photZPCatErr {catalogue extension keyword:  NUMZPT} int 4   -99999999
numZPCat MultiframeDetector WSAUHS Number of standards used in determining photZPCat and photZPCatErr {catalogue extension keyword:  NUMZPT} int 4   -99999999
numZPCat PreviousMFDZP WSA Number of standards used in determining photZP and photZPErr int 4   -99999999
numZPCat PreviousMFDZP WSACalib Number of standards used in determining photZP and photZPErr int 4   -99999999
numZPCat PreviousMFDZP WSAUHS Number of standards used in determining photZP and photZPErr int 4   -99999999
nuStep Multiframe WSA Number of positions in microstep pattern {image primary HDU keyword: NUSTEP} smallint 2   -9999 meta.number
nuStep Multiframe WSACalib Number of positions in microstep pattern {image primary HDU keyword: NUSTEP} smallint 2   -9999 meta.number
nuStep Multiframe WSATransit Number of positions in microstep pattern {image primary HDU keyword: NUSTEP} smallint 2   -9999 meta.number
nuStep Multiframe WSAUHS Number of positions in microstep pattern {image primary HDU keyword: NUSTEP} smallint 2   -9999 meta.number
nustep RequiredMosaic WSACalib Amount of microstepping tinyint 1     ??
nustep RequiredMosaic WSATransit Amount of microstepping tinyint 1     ??
nustep RequiredMosaic WSAUHS Amount of microstepping tinyint 1     ??
nustep RequiredMosaic, RequiredStack WSA Amount of microstepping tinyint 1     ??
NVSS nvssSource NVSS Source name varchar 14     ID_MAIN

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