Principal Component Analysis of the Time- and Position-Dependent Point Spread Function of the Advanced Camera for Surveys
M.J. Jee, J.P. Blakeslee, M. Sirianni, A.R. Martel, R.L. White, and, H.C. Ford

TL;DR
This paper develops a principal component analysis-based model of the ACS/WFC point spread function's variation over time and position, enabling improved precision in weak-lensing and other astronomical analyses.
Contribution
It introduces a PCA-based PSF library derived from over 400 archival images, capturing time and position-dependent PSF variations for the ACS/WFC.
Findings
Interpolation of ~20 principal components accurately reproduces PSF variations.
The PSF model is applicable to any WFC image rectified with Lanczos3 kernel.
The model is publicly available for broad astronomical applications.
Abstract
We describe the time- and position-dependent point spread function (PSF) variation of the Wide Field Channel (WFC) of the Advanced Camera for Surveys (ACS) with the principal component analysis (PCA) technique. The time-dependent change is caused by the temporal variation of the focus whereas the position-dependent PSF variation in ACS/WFC at a given focus is mainly the result of changes in aberrations and charge diffusion across the detector, which appear as position-dependent changes in elongation of the astigmatic core and blurring of the PSF, respectively. Using >400 archival images of star cluster fields, we construct a ACS PSF library covering diverse environments of the observations (e.g., focus values). We find that interpolation of a small number () of principal components or ``eigen-PSFs'' per exposure can robustly reproduce the observed variation of the…
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