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PSF photometry is one of the major ways to measure the flux of sources (detections) in PanSTARRS1 data. It is based on fitting a predefined analytical shape to the counts reported for each detection, and then applying a zero point conversion to the total object count rate thus obtained.
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The starting point for the PS1 data archive is at PanSTARRS1 data archive home page.
PSF Photometry
Obtained from fitting a predefined PSF form to all detections. The quality of the fit can help determine whether a source is indeed a point source, it is extended, or it is spurious. PSF photometry is performed on warps by a module called PSFPHOT and on stacks by PSPHOTSTACK. The result of the fit is reported in the Detection table (or StackDetection table for stacks). Values reported include flux, uncertainty, position, elliptical size, and quality parameters.
The PSF Model
The PSF model takes the form of an analytical function plus residuals. The fitted parameters and residuals vary with position, but are actually determined at 9 positions (in a regular 3x3 grid pattern) per skycell then interpolated to other positions.
Analytical functions tested include:
 GAUSS : exp (z)
 PGAUSS : (1 + z + z^{2}/2 + z^{3}/6)^{1}
 QGAUSS : (1 + kz + z^{2.25})^{1}
 RGAUSS : (1 + z + z^{k})^{1}
 PS1_V1 : (1 + kz + z^{1.67})^{1}
where z is the elliptical contour (akin to a radius squared):
 z = x^{2}/(2σ^{2}_{xx}) + y^{2}/(2σ^{2}_{yy}) + σ_{xy}XY
The PS1_V1 model is the current default value for PS1 analysis.
Variability over the image is formally represented as:
 PSF = F[dx,dy;ai(x,y)] + R0[dx,dy] + x Rx[dx,dy] + y Ry[dx,dy]
Existing documentation states that a global linear fit is performed in which the fluxes of all objects is fitted for simultaneously with the following considerations:
 Simultaneous fit of fluxes for all objects in the image
 Chisquare fit:
 χ^{2} = Σ(f_{i}  Σ (A_{j} F_{j)})^{2} W_{i} (i : pixels; j : objects)
 W_{i} – weighting function
 now constant (from mid2012), was inv variance
 using a constant weight removes a photometric bias found for faint sources
 minimization of A_{j} requires inversion of large square matrix
 N (number of objects) may be up to 100k
 but, highly diagonal, so inversion is actually fast
 ~ 1 second for 100k objects (unless they grow too large)
Photometric and astrometric parameters from PSF fitting
The PS1 Detection table fields table contains the following parameters related to PSF photometry:
xPos  raw pixels  REAL  4  999  PSF x center location. 
yPos  raw pixels  REAL  4  999  PSF y center location. 
xPosErr  raw pixels  REAL  4  999  Error in PSF x center location. 
yPosErr  raw pixels  REAL  4  999  Error in PSF y center location. 
psfFlux  Janskys  REAL  4  999  Flux from PSF fit. 
psfFluxErr  Janskys  REAL  4  999  Error on flux from PSF fit. 
psfMajorFWHM  arcsec  REAL  4  999  PSF major axis FWHM. 
psfMinorFWHM  arcsec  REAL  4  999  PSF minor axis FWHM. 
psfTheta  degrees  REAL  4  999  PSF major axis orientation. 
psfCore  dimensionless  REAL  4  999  PSF core parameter k, where F = F0 / (1 + k r^2 + r^3.33). 
psfQf  dimensionless  REAL  4  999  PSF coverage factor. 
psfQfPerfect  dimensionless  REAL  4  999  PSF weighted fraction of pixels totally unmasked. 
psfChiSq  dimensionless  REAL  4  999  Reduced chi squared value of the PSF model fit. 
psfLikelihood  dimensionless  REAL  4  999  Likelihood that this detection is best fit by a PSF. 
The equivalent stack measurements are to be found in PS1 StackObjectAttributes table fields.
Note that psphot actually returns PSF_MAJOR and PSF_MINOR, whose relation to FWHM depends on the value of k (reported as psfCore) for the PS1_V1 profile. For k=0, FWHM=PSF_MAJOR*2*sqrt(2)*pixel_size.