Accurate uncertainty estimation in crowded fields: adaptive optics and speckle data

TL;DR

This paper introduces a resampling method to improve the accuracy of uncertainty estimates in high-resolution stellar photometry and astrometry, addressing the underestimation issue of traditional PSF fitting routines.

Contribution

A novel resampling approach that provides more reliable uncertainty estimates in crowded field high-angular-resolution imaging.

Findings

Resampling yields more accurate uncertainty estimates.

Improved photometry and astrometry in crowded fields.

Addresses underestimation of uncertainties by existing software.

Abstract

Optimal error estimation is key to achieve accurate photometry and astrometry. Stellar fluxes and positions in high angular resolution images are typically measured with PSF fitting routines, such as StarFinder. However, the formal uncertainties computed by these software packages tend to seriously underestimate the relevant uncertainties. We present a new approach to deal with this problem using a resampling method to obtain robust and reliable uncertainties without loss of sensitivity.