Stellar Photometry and Astrometry with Discrete Point Spread Functions

Abstract

The key features of the MATPHOT algorithm for precise and accurate stellar photometry and astrometry using discrete Point Spread Functions are described. A discrete Point Spread Function (PSF) is a sampled version of a continuous PSF which describes the two-dimensional probability distribution of photons from a point source (star) just above the detector. The shape information about the photon scattering pattern of a discrete PSF is typically encoded using a numerical table (matrix) or a FITS image file. Discrete PSFs are shifted within an observational model using a 21-pixel-wide damped sinc function and position partial derivatives are computed using a five-point numerical differentiation formula. Precise and accurate stellar photometry and astrometry is achieved with undersampled CCD observations by using supersampled discrete PSFs that are sampled 2, 3, or more times more finely than the observational data. The precision and accuracy of the MATPHOT algorithm is demonstrated by using the C-language MPD code to analyze simulated CCD stellar observations; measured performance is compared with a theoretical performance model. Detailed analysis of simulated Next Generation Space Telescope observations demonstrate that millipixel relative astrometry and millimag photometric precision is achievable with complicated space-based discrete PSFs. For further information about MATPHOT and MPD, including source code and documentation, see http://www.noao.edu/staff/mighell/matphot