Z |
Name | Schema Table | Database | Description | Type | Length | Unit | Default Value | Unified Content Descriptor |
z11 |
Multiframe |
WSA |
Spherical: Z11 {image primary HDU keyword: Z11} |
real |
4 |
|
-0.9999995e9 |
|
z11 |
Multiframe |
WSACalib |
Spherical: Z11 {image primary HDU keyword: Z11} |
real |
4 |
|
-0.9999995e9 |
|
z11 |
Multiframe |
WSATransit |
Spherical: Z11 {image primary HDU keyword: Z11} |
real |
4 |
|
-0.9999995e9 |
|
z7 |
Multiframe |
WSA |
Coma: Z7 {image primary HDU keyword: Z7} |
real |
4 |
|
-0.9999995e9 |
|
z7 |
Multiframe |
WSACalib |
Coma: Z7 {image primary HDU keyword: Z7} |
real |
4 |
|
-0.9999995e9 |
|
z7 |
Multiframe |
WSATransit |
Coma: Z7 {image primary HDU keyword: Z7} |
real |
4 |
|
-0.9999995e9 |
|
z8 |
Multiframe |
WSA |
Coma: Z8 {image primary HDU keyword: Z8} |
real |
4 |
|
-0.9999995e9 |
|
z8 |
Multiframe |
WSACalib |
Coma: Z8 {image primary HDU keyword: Z8} |
real |
4 |
|
-0.9999995e9 |
|
z8 |
Multiframe |
WSATransit |
Coma: Z8 {image primary HDU keyword: Z8} |
real |
4 |
|
-0.9999995e9 |
|
zAperMag1 |
calSynopticSource |
WSACalib |
Extended source Z aperture corrected mag (1.0 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zAperMag1Err |
calSynopticSource |
WSACalib |
Error in extended source Z mag (1.0 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zAperMag2 |
calSynopticSource |
WSACalib |
Extended source Z aperture corrected mag (1.4 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zAperMag2Err |
calSynopticSource |
WSACalib |
Error in extended source Z mag (1.4 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zAperMag3 |
calSource |
WSACalib |
Default point/extended source Z aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zAperMag3 |
calSynopticSource |
WSACalib |
Default point/extended source Z aperture corrected mag (2.0 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zAperMag3 |
gcsPointSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Default point/extended source Z aperture corrected mag (2.0 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zAperMag3 |
gcsSource |
WSA |
Default point/extended source Z aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zAperMag3Err |
calSource, calSynopticSource |
WSACalib |
Error in default point/extended source Z mag (2.0 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zAperMag3Err |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Error in default point/extended source Z mag (2.0 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zAperMag4 |
calSource, calSynopticSource |
WSACalib |
Extended source Z aperture corrected mag (2.8 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zAperMag4 |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Extended source Z aperture corrected mag (2.8 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zAperMag4Err |
calSource, calSynopticSource |
WSACalib |
Error in extended source Z mag (2.8 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zAperMag4Err |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Error in extended source Z mag (2.8 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zAperMag5 |
calSynopticSource |
WSACalib |
Extended source Z aperture corrected mag (4.0 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zAperMag5Err |
calSynopticSource |
WSACalib |
Error in extended source Z mag (4.0 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zAperMag6 |
calSource |
WSACalib |
Extended source Z aperture corrected mag (5.7 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zAperMag6 |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Extended source Z aperture corrected mag (5.7 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zAperMag6Err |
calSource |
WSACalib |
Error in extended source Z mag (5.7 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zAperMag6Err |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Error in extended source Z mag (5.7 arcsec aperture diameter) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zaStratAst |
calVarFrameSetInfo |
WSACalib |
Strateva parameter, a, in fit to astrometric rms vs magnitude in Z 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. |
zaStratPht |
calVarFrameSetInfo |
WSACalib |
Strateva parameter, a, in fit to photmetric rms vs magnitude in Z 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. |
zbestAper |
calVariability |
WSACalib |
Best aperture (1-6) for photometric statistics in the Z 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) |
zbStratAst |
calVarFrameSetInfo |
WSACalib |
Strateva parameter, b, in fit to astrometric rms vs magnitude in Z 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. |
zbStratPht |
calVarFrameSetInfo |
WSACalib |
Strateva parameter, b, in fit to photometric rms vs magnitude in Z 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. |
zchiSqAst |
calVarFrameSetInfo |
WSACalib |
Goodness of fit of Strateva function to astrometric data in Z 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. |
zchiSqpd |
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. |
zchiSqPht |
calVarFrameSetInfo |
WSACalib |
Goodness of fit of Strateva function to photometric data in Z 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. |
zClass |
calSource, calSourceRemeasurement, calSynopticSource |
WSACalib |
discrete image classification flag in Z |
smallint |
2 |
|
-9999 |
CLASS_MISC |
zClass |
gcsPointSource, gcsSource, gcsSourceRemeasurement, gcsZYJHKsource, reliableGcsPointSource |
WSA |
discrete image classification flag in Z |
smallint |
2 |
|
-9999 |
CLASS_MISC |
zClassStat |
calSource, calSourceRemeasurement, calSynopticSource |
WSACalib |
N(0,1) stellarness-of-profile statistic in Z |
real |
4 |
|
-0.9999995e9 |
STAT_PROP |
zClassStat |
gcsPointSource, gcsSource, gcsSourceRemeasurement, gcsZYJHKsource, reliableGcsPointSource |
WSA |
N(0,1) stellarness-of-profile statistic in Z |
real |
4 |
|
-0.9999995e9 |
STAT_PROP |
zcStratAst |
calVarFrameSetInfo |
WSACalib |
Strateva parameter, c, in fit to astrometric rms vs magnitude in Z 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. |
zcStratPht |
calVarFrameSetInfo |
WSACalib |
Strateva parameter, c, in fit to photometric rms vs magnitude in Z 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. |
zd |
twomass_scn |
2MASS |
Scan's distance from the zenith at beginning of scan. |
real |
4 |
degrees |
|
POS_ZD_RES |
zDeblend |
calSource |
WSACalib |
placeholder flag indicating parent/child relation in Z |
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. |
zDeblend |
calSourceRemeasurement, calSynopticSource |
WSACalib |
placeholder flag indicating parent/child relation in Z |
int |
4 |
|
-99999999 |
CODE_MISC |
zDeblend |
gcsPointSource, gcsSourceRemeasurement, gcsZYJHKsource, reliableGcsPointSource |
WSA |
placeholder flag indicating parent/child relation in Z |
int |
4 |
|
-99999999 |
CODE_MISC |
zDeblend |
gcsSource |
WSA |
placeholder flag indicating parent/child relation in Z |
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. |
zEll |
calSource, calSourceRemeasurement, calSynopticSource |
WSACalib |
1-b/a, where a/b=semi-major/minor axes in Z |
real |
4 |
|
-0.9999995e9 |
PHYS_ELLIPTICITY |
zEll |
gcsPointSource, gcsSource, gcsSourceRemeasurement, gcsZYJHKsource, reliableGcsPointSource |
WSA |
1-b/a, where a/b=semi-major/minor axes in Z |
real |
4 |
|
-0.9999995e9 |
PHYS_ELLIPTICITY |
zeNum |
calMergeLog, calSynopticMergeLog |
WSACalib |
the extension number of this Z frame |
tinyint |
1 |
|
|
NUMBER |
zeNum |
gcsMergeLog |
WSA |
the extension number of this Z frame |
tinyint |
1 |
|
|
NUMBER |
zeNum |
gcsZYJHKmergeLog |
WSA |
the extension number of this frame |
tinyint |
1 |
|
|
NUMBER |
zErrBits |
calSource, calSynopticSource |
WSACalib |
processing warning/error bitwise flags in Z |
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. |
zErrBits |
calSourceRemeasurement |
WSACalib |
processing warning/error bitwise flags in Z |
int |
4 |
|
-99999999 |
CODE_MISC |
zErrBits |
gcsPointSource, gcsSourceRemeasurement, gcsZYJHKsource, reliableGcsPointSource |
WSA |
processing warning/error bitwise flags in Z |
int |
4 |
|
-99999999 |
CODE_MISC |
zErrBits |
gcsSource |
WSA |
processing warning/error bitwise flags in Z |
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. |
zEta |
calSource, calSynopticSource |
WSACalib |
Offset of Z 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; 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. |
zEta |
gcsPointSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Offset of Z detection from master position (+north/-south) |
real |
4 |
arcsec |
-0.9999995e9 |
POS_EQ_DEC_OFF |
zEta |
gcsSource |
WSA |
Offset of Z 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; 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. |
zexpML |
calVarFrameSetInfo |
WSACalib |
Expected magnitude limit of frameSet in this in Z 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. |
zExpRms |
calVariability |
WSACalib |
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Z 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. |
zGausig |
calSource, calSourceRemeasurement, calSynopticSource |
WSACalib |
RMS of axes of ellipse fit in Z |
real |
4 |
pixels |
-0.9999995e9 |
MORPH_PARAM |
zGausig |
gcsPointSource, gcsSource, gcsSourceRemeasurement, gcsZYJHKsource, reliableGcsPointSource |
WSA |
RMS of axes of ellipse fit in Z |
real |
4 |
pixels |
-0.9999995e9 |
MORPH_PARAM |
zHallMag |
calSource |
WSACalib |
Total point source Z mag |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zHallMag |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Total point source Z mag |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zHallMagErr |
calSource |
WSACalib |
Error in total point source Z mag |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zHallMagErr |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Error in total point source Z mag |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zIntRms |
calVariability |
WSACalib |
Intrinsic rms in Z-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. |
zMag |
calSourceRemeasurement |
WSACalib |
Z mag (as appropriate for this merged source) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zMag |
gcsSourceRemeasurement |
WSA |
Z mag (as appropriate for this merged source) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zMagErr |
calSourceRemeasurement |
WSACalib |
Error in Z mag |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zMagErr |
gcsSourceRemeasurement |
WSA |
Error in Z mag |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zMagMAD |
calVariability |
WSACalib |
Median Absolute Deviation of Z 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. |
zMagRms |
calVariability |
WSACalib |
rms of Z 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. |
zmaxCadence |
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. |
zMaxMag |
calVariability |
WSACalib |
Maximum magnitude in Z 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. |
zmeanMag |
calVariability |
WSACalib |
Mean Z 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. |
zmedCadence |
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. |
zmedianMag |
calVariability |
WSACalib |
Median Z 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. |
zmfID |
calMergeLog, calSynopticMergeLog |
WSACalib |
the UID of the relevant Z multiframe |
bigint |
8 |
|
|
ID_FRAME |
zmfID |
gcsMergeLog |
WSA |
the UID of the relevant Z multiframe |
bigint |
8 |
|
|
ID_FRAME |
zmfID |
gcsZYJHKmergeLog |
WSA |
the UID of the relevant multiframe |
bigint |
8 |
|
|
ID_FRAME |
zminCadence |
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. |
zMinMag |
calVariability |
WSACalib |
|
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. |
zmy |
calSourceRemeasurement |
WSACalib |
Default colour Z-Y (using appropriate mags) |
real |
4 |
mag |
|
PHOT_COLOR |
zmy |
gcsSourceRemeasurement |
WSA |
Default colour Z-Y (using appropriate mags) |
real |
4 |
mag |
|
PHOT_COLOR |
zmyErr |
calSourceRemeasurement |
WSACalib |
Error on colour Z-Y |
real |
4 |
mag |
|
ERROR |
zmyErr |
gcsSourceRemeasurement |
WSA |
Error on colour Z-Y |
real |
4 |
mag |
|
ERROR |
zmyExt |
calSource |
WSACalib |
Extended source colour Z-Y (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. |
zmyExt |
gcsPointSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Extended source colour Z-Y (using aperMag3) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_COLOR |
zmyExt |
gcsSource |
WSA |
Extended source colour Z-Y (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. |
zmyExtErr |
calSource |
WSACalib |
Error on extended source colour Z-Y |
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. |
zmyExtErr |
gcsPointSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Error on extended source colour Z-Y |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zmyExtErr |
gcsSource |
WSA |
Error on extended source colour Z-Y |
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. |
zmyPnt |
calSource, calSynopticSource |
WSACalib |
Point source colour Z-Y (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. |
zmyPnt |
gcsPointSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Point source colour Z-Y (using aperMag3) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_COLOR |
zmyPnt |
gcsSource |
WSA |
Point source colour Z-Y (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. |
zmyPntErr |
calSource, calSynopticSource |
WSACalib |
Error on point source colour Z-Y |
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. |
zmyPntErr |
gcsPointSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Error on point source colour Z-Y |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zmyPntErr |
gcsSource |
WSA |
Error on point source colour Z-Y |
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. |
zndof |
calVariability |
WSACalib |
Number of degrees of freedom for chisquare |
int |
4 |
|
-99999999 |
|
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. |
znDofAst |
calVarFrameSetInfo |
WSACalib |
Number of degrees of freedom of astrometric fit in Z 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. |
znDofPht |
calVarFrameSetInfo |
WSACalib |
Number of degrees of freedom of photometric fit in Z 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. |
znFlaggedObs |
calVariability |
WSACalib |
Number of detections in Z 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. |
znGoodObs |
calVariability |
WSACalib |
Number of good detections in Z 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. |
zNgt3sig |
calVariability |
WSACalib |
Number of good detections in Z-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. |
znMissingObs |
calVariability |
WSACalib |
Number of Z 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. |
zObjID |
calSource, calSourceRemeasurement, calSynopticSource |
WSACalib |
DEPRECATED (do not use) |
bigint |
8 |
|
-99999999 |
ID_NUMBER |
This attribute is included in source tables for historical reasons, but it's use is not recommended unless you really know what you are doing. In general, if you need to look up detection table attributes for a source in a given passband that are not in the source table, you should make an SQL join between source, mergelog and detection using the primary key attribute frameSetID and combination multiframeID, extNum, seqNum to associate related rows between the three tables. See the Q&A example SQL for more information. |
zObjID |
gcsPointSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
DEPRECATED (do not use) |
bigint |
8 |
|
-99999999 |
ID_NUMBER |
zObjID |
gcsSource, gcsSourceRemeasurement |
WSA |
DEPRECATED (do not use) |
bigint |
8 |
|
-99999999 |
ID_NUMBER |
This attribute is included in source tables for historical reasons, but it's use is not recommended unless you really know what you are doing. In general, if you need to look up detection table attributes for a source in a given passband that are not in the source table, you should make an SQL join between source, mergelog and detection using the primary key attribute frameSetID and combination multiframeID, extNum, seqNum to associate related rows between the three tables. See the Q&A example SQL for more information. |
zone |
ExternalSurveyTable |
WSA |
default (0) or special (n) zone |
smallint |
2 |
|
|
ID_REGION |
zone |
ExternalSurveyTable |
WSACalib |
default (0) or special (n) zone |
smallint |
2 |
|
|
ID_REGION |
zone |
ExternalSurveyTable |
WSATransit |
default (0) or special (n) zone |
smallint |
2 |
|
|
ID_REGION |
zPA |
calSource, calSourceRemeasurement, calSynopticSource |
WSACalib |
ellipse fit celestial orientation in Z |
real |
4 |
Degrees |
-0.9999995e9 |
POS_POS-ANG |
zPA |
gcsPointSource, gcsSource, gcsSourceRemeasurement, gcsZYJHKsource, reliableGcsPointSource |
WSA |
ellipse fit celestial orientation in Z |
real |
4 |
Degrees |
-0.9999995e9 |
POS_POS-ANG |
zPetroMag |
calSource |
WSACalib |
Extended source Z mag (Petrosian) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zPetroMag |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Extended source Z mag (Petrosian) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zPetroMagErr |
calSource |
WSACalib |
Error in extended source Z mag (Petrosian) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zPetroMagErr |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Error in extended source Z mag (Petrosian) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zppErrBits |
calSource, calSynopticSource |
WSACalib |
additional WFAU post-processing error bits in Z |
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 | LAS, GCS, GPS, DXS | 0 | 6 | Bad pixel(s) in default aperture | 64 | 0x00000040 | LAS, GCS, GPS, DXS | 2 | 16 | Close to saturated | 65536 | 0x00010000 | LAS, GCS, GPS | 2 | 19 | Possible crosstalk artefact/contamination | 524288 | 0x00080000 | LAS, GCS, DXS | 2 | 22 | Lies within a dither offset of the stacked frame boundary | 4194304 | 0x00400000 | LAS, GCS, GPS, DXS | 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. |
zppErrBits |
calSourceRemeasurement |
WSACalib |
additional WFAU post-processing error bits in Z |
int |
4 |
|
0 |
CODE_MISC |
zppErrBits |
gcsPointSource, gcsSourceRemeasurement, gcsZYJHKsource, reliableGcsPointSource |
WSA |
additional WFAU post-processing error bits in Z |
int |
4 |
|
0 |
CODE_MISC |
zppErrBits |
gcsSource |
WSA |
additional WFAU post-processing error bits in Z |
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 | LAS, GCS, GPS, DXS | 0 | 6 | Bad pixel(s) in default aperture | 64 | 0x00000040 | LAS, GCS, GPS, DXS | 2 | 16 | Close to saturated | 65536 | 0x00010000 | LAS, GCS, GPS | 2 | 19 | Possible crosstalk artefact/contamination | 524288 | 0x00080000 | LAS, GCS, DXS | 2 | 22 | Lies within a dither offset of the stacked frame boundary | 4194304 | 0x00400000 | LAS, GCS, GPS, DXS | 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. |
zprobVar |
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. |
zPsfMag |
calSource |
WSACalib |
Point source profile-fitted Z mag |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zPsfMag |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Point source profile-fitted Z mag |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zPsfMagErr |
calSource |
WSACalib |
Error in point source profile-fitted Z mag |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zPsfMagErr |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Error in point source profile-fitted Z mag |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zSeqNum |
calSource, calSynopticSource |
WSACalib |
the running number of the Z detection |
int |
4 |
|
-99999999 |
ID_NUMBER |
zSeqNum |
calSourceRemeasurement |
WSACalib |
the running number of the Z remeasurement |
int |
4 |
|
-99999999 |
ID_NUMBER |
zSeqNum |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
the running number of the Z detection |
int |
4 |
|
-99999999 |
ID_NUMBER |
zSeqNum |
gcsSourceRemeasurement |
WSA |
the running number of the Z remeasurement |
int |
4 |
|
-99999999 |
ID_NUMBER |
zSerMag2D |
calSource |
WSACalib |
Extended source Z mag (profile-fitted) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zSerMag2D |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Extended source Z mag (profile-fitted) |
real |
4 |
mag |
-0.9999995e9 |
PHOT_MAG |
zSerMag2DErr |
calSource |
WSACalib |
Error in extended source Z mag (profile-fitted) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zSerMag2DErr |
gcsPointSource, gcsSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Error in extended source Z mag (profile-fitted) |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
zskewness |
calVariability |
WSACalib |
Skewness in Z 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. |
ZSOURCE |
mgcBrightSpec |
MGC |
Identifier for best redshift and quality |
varchar |
10 |
|
|
|
ztotalPeriod |
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. |
zVarClass |
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. |
zXi |
calSource, calSynopticSource |
WSACalib |
Offset of Z 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; 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. |
zXi |
gcsPointSource, gcsZYJHKsource, reliableGcsPointSource |
WSA |
Offset of Z detection from master position (+east/-west) |
real |
4 |
arcsec |
-0.9999995e9 |
POS_EQ_RA_OFF |
zXi |
gcsSource |
WSA |
Offset of Z 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; 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. |
zyiWS |
calVariability |
WSACalib |
Welch-Stetson statistic between Z and Y. This assumes colour does not vary much and helps remove variation due to a few poor detections |
real |
4 |
|
-0.9999995e9 |
|
The Welch-Stetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. |