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Glossary of WSA NonSurvey attributes (UKIDSSDR5)
This Glossary alphabetically lists all attributes used in the WSA NonSurvey database(s) held in the WSA. If you would like to have more information about the schema tables please use the Schema Browser (other Browser versions).

A

B

C

D

E

F

G

H

I

J

K

L

M

N

O

P

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P
Name	Schema Table	Database	Description	Type	Length	Unit	Default Value	Unified Content Descriptor
pa	[nspid]Detection	WSA NonSurvey	ellipse fit orientation to x axis {catalogue TType keyword: Position_angle} Angle of ellipse major axis wrt x axis.	real	4	degrees		POS_POS-ANG
pairingCriterion	[nspid]Programme	WSA NonSurvey	The pairing criterion for associating detections into merged sources	real	4	Degrees		??
parallax	[nspid]Variability	WSA NonSurvey	Parallax of star	real	4	mas	-0.9999995e9
			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.
pcSysID	[nspid]MultiframeDetector	WSA NonSurvey	PC system identifier {image extension keyword: PCSYSID}	varchar	32		NONE	??
petroFlux	[nspid]Detection	WSA NonSurvey	flux within circular aperture to k × r_p ; k = 2 {catalogue TType keyword: Petr_flux}	real	4	ADU		PHOT_INTENSITY_ADU
petroFluxErr	[nspid]Detection	WSA NonSurvey	error on Petrosian flux {catalogue TType keyword: Petr_flux_err}	real	4	ADU		ERROR
petroMag	[nspid]Detection	WSA NonSurvey	Calibrated Petrosian magnitude within circular aperture r_p	real	4	mag		PHOT_INT-MAG
petroMagErr	[nspid]Detection	WSA NonSurvey	error on calibrated Petrosian magnitude	real	4	mag		ERROR
petroRad	[nspid]Detection	WSA NonSurvey	r_p as defined in Yasuda et al. 2001 AJ 112 1104 {catalogue TType keyword: Petr_radius}	real	4	pixels		EXTENSION_RAD
pGalaxy	[nspid]Source	WSA NonSurvey	Probability that the source is a galaxy	real	4			STAT_PROP
			Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code: Flag Meaning Probability (%) Star Galaxy Noise Saturated -9 Saturated 0.0 0.0 5.0 95.0 -3 Probable galaxy 25.0 70.0 5.0 0.0 -2 Probable star 70.0 25.0 5.0 0.0 -1 Star 90.0 5.0 5.0 0.0 0 Noise 5.0 5.0 90.0 0.0 +1 Galaxy 5.0 90.0 5.0 0.0 Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent: P(classk)=ΠiP(classk)i / ΣkΠiP(classk)i where classk is one of star|galaxy|noise|saturated, and i denotes the ith single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.
pHeight	[nspid]Detection	WSA NonSurvey	Highest pixel value above sky {catalogue TType keyword: Peak_height} In counts relative to local value of sky - also zeroth order aperture flux.	real	4	ADU		PHOT_COUNTS_MISC
pHeightErr	[nspid]Detection	WSA NonSurvey	Error in peak height {catalogue TType keyword: Peak_height_err}	real	4	ADU		ERROR
photZPCat	[nspid]MultiframeDetector	WSA NonSurvey	Photometric zero point for default extinction for the catalogue data {catalogue extension keyword:  MAGZPT}	real	4	mags	-0.9999995e9	??
			Derived detector zero-point in the sense of what magnitude object gives a total (corrected) flux of 1 count/s. These ZPs are appropriate for generating magnitudes in the natural detector+filter system based on Vega, see CASU reports for more details on colour equations etc. The ZPs have been derived from a robust average of all photometric standards observed on any particular set of frames, corrected for airmass but assuming the default extinction values listed later. For other airmass or other values of the extinction use ZP → ZP - [sec(z)-1]×extinct + extinct default - extinct You can then make use of any of the assorted flux estimators to produce magnitudes via Mag = ZP - 2.5*log10(flux/exptime) - aperCor - skyCorr Note that for the so-called total and isophotal flux options it is not possible to have a single-valued aperture correction.
photZPCat	[nspid]PreviousMFDZP	WSA NonSurvey	Photometric zeropoint for default extinction in catalogue header	real	4	mag	-0.9999995e9
photZPErrCat	[nspid]MultiframeDetector	WSA NonSurvey	Photometric zero point error for the catalogue data {catalogue extension keyword:  MAGZRR} [Currently set to -1 for WFCAM data.]	real	4	mags	-0.9999995e9	??
			Error in the zero point. If good photometric night this error will be at the level of a few percent. Values of 0.05 and above indicate correspondingly non-photometric night and worse.
photZPErrCat	[nspid]PreviousMFDZP	WSA NonSurvey	Photometric zeropoint error in catalogue header	real	4	mag	-0.9999995e9
pixelScale	[nspid]MultiframeDetector	WSA NonSurvey	Warning - Original detector pixel size, the actual angular pixel size is written to xPixSize and yPixSize in the CurrentAstrometry table {image extension keyword: PIXLSIZE}	real	4	arcsec per pixel	-0.9999995e9	INST_PIXSIZE
pmDec	[nspid]FSstars	WSA NonSurvey	Proper motion in Dec	real	4	arcsec per year	0.0
pmRA	[nspid]FSstars	WSA NonSurvey	Proper motion in RA	real	4	arcsec per year	0.0
pNoise	[nspid]Source	WSA NonSurvey	Probability that the source is noise	real	4			STAT_PROP
			Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code: Flag Meaning Probability (%) Star Galaxy Noise Saturated -9 Saturated 0.0 0.0 5.0 95.0 -3 Probable galaxy 25.0 70.0 5.0 0.0 -2 Probable star 70.0 25.0 5.0 0.0 -1 Star 90.0 5.0 5.0 0.0 0 Noise 5.0 5.0 90.0 0.0 +1 Galaxy 5.0 90.0 5.0 0.0 Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent: P(classk)=ΠiP(classk)i / ΣkΠiP(classk)i where classk is one of star|galaxy|noise|saturated, and i denotes the ith single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.
pointingID	[nspid]Multiframe	WSA NonSurvey	Pointing ID within survey {image primary HDU keyword: SURVEY_I}	varchar	64		NONE	??
posAngle	[nspid]CurrentAstrometry, [nspid]PreviousAstrometry	WSA NonSurvey	orientation of image x-axis to N-S	float	8	Degrees	-0.9999995e9	POS_POS-ANG
ppErrBits	[nspid]Detection	WSA NonSurvey	additional WFAU post-processing error bits (place holder for now)	int	4		0	CODE_MISC
ppErrBitsStatus	[nspid]ProgrammeFrame	WSA NonSurvey	Bit flag to denote whether detection quality flagging has been done on this multiframe for this programme.	int	4		0
priOrSec	[nspid]Source	WSA NonSurvey	Seam code for a unique (=0) or duplicated (!=0) source (eg. flags overlap duplicates).	bigint	8		-99999999	CODE_MISC
			Because of the spacing of the detectors in WFCAM, and the restrictions on guide star brightness, there will always be overlap regions between adjacent frame sets. Source merging is done on a set-by-set basis; hence after source merging there are usually a small number of duplicate sources in the table. A process known as seaming takes place after source merging is complete, whereby duplicates are identified and flagged. The flagging attribute is priOrSec, and the meaning of the flag is quite simple: if a source is not found to be duplicated in overlap regions, then priOrSec=0; if a source is duplicated, then priOrSec will be set to the frameSetID of the source that should be considered the best one to use out of the set of duplicates. Presently, the choice of which is best is made on the basis of proximity to the optical axis of the camera, the assumption being that this will give the best quality image in general. So, if a particular source has a non-zero priOrSec that is set to it's own value of frameSetID, then this indicates that there is a duplicate elsewhere in the table, but this is the one that should be selected as the best (i.e. this is the primary source). On the other hand, if a source has a non-zero value of priOrSec that is set a different frameSetID than that of the source in question, then this indicates that this source should be considered as a secondary duplicate of a source who's primary is actually to be found in the frame set pointed to by that value of frameSetID. Hence, the WHERE clause for selecting out a seamless, best catalogue is of the form WHERE ... AND (priOrSec=0 OR priOrSec=frameSetID).
productID	[nspid]RequiredDiffImage	WSA NonSurvey	A unique identifier assigned to each required difference image product entry	int	4			??
productID	[nspid]RequiredMosaic	WSA NonSurvey	A unique identifier assigned to each required mosaic product entry	int	4			??
productID	[nspid]RequiredStack	WSA NonSurvey	A unique identifier assigned to each required stack product entry	int	4			??
programmeID	[nspid]Programme	WSA NonSurvey	UID of the archived programme coded as above	int	4			ID_SURVEY
programmeID	[nspid]ProgrammeCurationHistory, [nspid]ProgrammeTable, [nspid]RequiredDiffImage, [nspid]RequiredFilters, [nspid]RequiredListDrivenProduct, [nspid]RequiredMosaic, [nspid]RequiredNeighbours, [nspid]RequiredStack, [nspid]RequiredSynoptic	WSA NonSurvey	the unique programme ID	int	4			ID_SURVEY
programmeID	[nspid]ProgrammeFrame, [nspid]SurveyProgrammes	WSA NonSurvey	WSA assigned programme UID {image primary HDU keyword: PROJECT}	int	4		-99999999	ID_SURVEY
project	[nspid]Multiframe	WSA NonSurvey	Time-allocation code {image primary HDU keyword: PROJECT}	varchar	64		NONE	REFER_CODE
projection	[nspid]RequiredMosaic	WSA NonSurvey	CASU mosaic tool option to specify output WCS projection type (TAN for gnomonic, ZPN for zenithal polynomial)	varchar	3			??
propPeriod	[nspid]Programme	WSA NonSurvey	the proprietory period for any data taken for this programme in months, e.g. 12 for open time.	int	4	months		TIME_PERIOD
proprietary	[nspid]Survey	WSA NonSurvey	Logical flag indicating whether a survey is proprietary or not (1=yes; 0=no)	tinyint	1			??
pSaturated	[nspid]Source	WSA NonSurvey	Probability that the source is saturated	real	4			STAT_PROP
			Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code: Flag Meaning Probability (%) Star Galaxy Noise Saturated -9 Saturated 0.0 0.0 5.0 95.0 -3 Probable galaxy 25.0 70.0 5.0 0.0 -2 Probable star 70.0 25.0 5.0 0.0 -1 Star 90.0 5.0 5.0 0.0 0 Noise 5.0 5.0 90.0 0.0 +1 Galaxy 5.0 90.0 5.0 0.0 Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent: P(classk)=ΠiP(classk)i / ΣkΠiP(classk)i where classk is one of star|galaxy|noise|saturated, and i denotes the ith single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.
psfFitChi2	[nspid]Detection	WSA NonSurvey	standard normalised variance of PSF fit {catalogue TType keyword: PSF_fit_chi2}	real	4		-0.9999995e9	FIT_STDEV
psfFitDof	[nspid]Detection	WSA NonSurvey	no. of degrees of freedom of PSF fit {catalogue TType keyword: PSF_fit_dof}	smallint	2		-9999	STAT_N-DOF
psfFitX	[nspid]Detection	WSA NonSurvey	PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X}	real	4	pixels	-0.9999995e9	POS_PLATE_X
psfFitXerr	[nspid]Detection	WSA NonSurvey	Error on PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X_err}	real	4	pixels	-0.9999995e9	ERROR
psfFitY	[nspid]Detection	WSA NonSurvey	PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_Y}	real	4	pixels	-0.9999995e9	POS_PLATE_Y
psfFitYerr	[nspid]Detection	WSA NonSurvey	Error on PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_y_err}	real	4	pixels	-0.9999995e9	ERROR
psfFlux	[nspid]Detection	WSA NonSurvey	PSF-fitted flux {catalogue TType keyword: PSF_flux}	real	4	ADU	-0.9999995e9	PHOT_INTENSITY_ADU
psfFluxErr	[nspid]Detection	WSA NonSurvey	Error on PSF-fitted flux {catalogue TType keyword: PSF_flux_err}	real	4	ADU	-0.9999995e9	ERROR
psfMag	[nspid]Detection	WSA NonSurvey	PSF-fitted calibrated magnitude	real	4	mag	-0.9999995e9	PHOT_PROFILE
psfMagErr	[nspid]Detection	WSA NonSurvey	Error on PSF-fitted calibrated magnitude	real	4	mag	-0.9999995e9	ERROR
pStar	[nspid]Source	WSA NonSurvey	Probability that the source is a star	real	4			STAT_PROP
			Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code: Flag Meaning Probability (%) Star Galaxy Noise Saturated -9 Saturated 0.0 0.0 5.0 95.0 -3 Probable galaxy 25.0 70.0 5.0 0.0 -2 Probable star 70.0 25.0 5.0 0.0 -1 Star 90.0 5.0 5.0 0.0 0 Noise 5.0 5.0 90.0 0.0 +1 Galaxy 5.0 90.0 5.0 0.0 Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent: P(classk)=ΠiP(classk)i / ΣkΠiP(classk)i where classk is one of star|galaxy|noise|saturated, and i denotes the ith single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.
pv21	[nspid]CurrentAstrometry, [nspid]PreviousAstrometry	WSA NonSurvey	Coefficient for r term (use only with ZPN projection) {image extension keyword: PV2_1} transformation from pixel to celestial co-ordinates	float	8		-0.9999995e9	POS_TRANSF_PARAM
pv22	[nspid]CurrentAstrometry, [nspid]PreviousAstrometry	WSA NonSurvey	Coefficient for r**2 term (use only with ZPN projection) {image extension keyword: PV2_2} transformation from pixel to celestial co-ordinates	float	8		-0.9999995e9	POS_TRANSF_PARAM
pv23	[nspid]CurrentAstrometry, [nspid]PreviousAstrometry	WSA NonSurvey	Coefficient for r**3 term (use only with ZPN projection) {image extension keyword: PV2_3} transformation from pixel to celestial co-ordinates	float	8		-0.9999995e9	POS_TRANSF_PARAM