AIROPA IV: Validating Point Spread Function Reconstruction on Various Science Cases

TL;DR

This study evaluates the effectiveness of AIROPA's PSF reconstruction on six on-sky datasets from Keck-II/NIRC2, finding limited improvements in astrometry and photometry when using a spatially variable PSF model versus a static one, due to unaccounted instrumental aberrations.

Contribution

The paper provides a comprehensive on-sky validation of AIROPA's PSF reconstruction, highlighting its limited impact under certain conditions and identifying key factors affecting performance.

Findings

Limited improvement in astrometric residuals with variable PSF

Photometric accuracy improved by 10x in one dataset

Spatially variable PSF shows comparable performance to static PSF

Abstract

We present an analysis of six independent on-sky datasets taken with the Keck-II/NIRC2 instrument. Using the off-axis point spread function (PSF) reconstruction software AIROPA, we extract stellar astrometry, photometry, and other fitting metrics in order to characterize the performance of this package. We test the effectiveness of AIROPA to reconstruct the PSF across the field of view in varying atmospheric conditions, number and location of PSF reference stars, stellar crowding and telescope position angle (PA). We compare the astrometric precision and fitting residuals between a static PSF model and a spatially varying PSF model that incorporates instrumental aberrations and atmospheric turbulence during exposures. Most of the fitting residuals we measure show little to no improvement in the variable-PSF mode over the single-PSF mode. For one of the data sets, we find photometric performance is significantly improved (by ${\sim}10\times$) by measuring the trend seen in photometry as a function of off-axis location. For nearly all other metrics we find comparable astrometric and photometric precision across both PSF modes, with a ${\sim}13$% smaller astrometric uncertainty in variable-PSF mode in the best case. We largely confirm that the spatially variable PSF does not significantly improve the astrometric and other PSF fitting residuals over the static PSF for on-sky observations. We attribute this to unaccounted instrumental aberrations that are not characterized through afternoon adaptive optics (AO) bench calibrations.