Testing Accuracy and Precision of Existing Photometry Algorithms on Moving Targets

TL;DR

This study evaluates various photometry algorithms on moving targets, finding that tphot most accurately reproduces the true light curve of a faint solar system object, especially in centroiding and contaminant exclusion.

Contribution

It introduces a comprehensive comparison of photometry algorithms on moving targets, highlighting tphot's superior accuracy and precision in this context.

Findings

Tphot outperforms other algorithms in accuracy and precision.

Tphot excels in centroiding and contaminant exclusion.

Photometry of moving targets presents unique challenges addressed by specific algorithms.

Abstract

Previous studies determining which astronomical photometry software is best suited for a particular dataset are usually focused on speed, source classification, and/or meeting a sensitivity requirement. For faint objects in particular, the priority is given to maximizing signal-to-noise. Photometry of moving targets offers additional challenges (i) to aperture photometry because background object contamination varies from image to image, and (ii) to routines that build a PSF model from point sources in the image because trailed field stars do not perfectly represent the PSF of the untrailed target. Here, we present the results of testing several photometry algorithms (tphot, DAOPHOT, DoPHOT, APT, and multiple techniques within Source Extractor and IRAF's PHOT) on data for a faint, slow-moving solar system object with a known light curve. We find that the newly-developed tphot software most accurately and precisely reproduces the object's true light curve, with particular advantages in centroiding, exclusion of contaminants from the target's flux, and fitting flux in the wings of the point-spread function.