TRIPPy: Trailed Image Photometry in Python

TL;DR

TRIPPy is a Python software package that improves photometry of moving sources by introducing pill-shaped apertures and a new method for modeling trailed PSFs, enabling accurate flux measurements with high SNR.

Contribution

The paper presents TRIPPy, a novel Python package that introduces pill-shaped apertures and a technique for modeling trailed PSFs for improved photometry of moving sources.

Findings

Accurate pill aperture corrections with 10 millimags precision.

Enhanced flux measurement accuracy for highly trailed sources.

Preservation of SNR using small pill apertures with proper correction.

Abstract

Photometry of moving sources typically suffers from reduced signal-to-noise (SNR) or flux measurements biased to incorrect low values through the use of circular apertures. To address this issue we present the software package, TRIPPy: TRailed Image Photometry in Python. TRIPPy introduces the pill aperture, which is the natural extension of the circular aperture appropriate for linearly trailed sources. The pill shape is a rectangle with two semicircular end-caps, and is described by three parameters, the trail length and angle, and the radius. The TRIPPy software package also includes a new technique to generate accurate model point-spread functions (PSF) and trailed point-spread functions (TSF) from stationary background sources in sidereally tracked images. The TSF is merely the convolution of the model PSF, which consists of a moffat profile, and super sampled lookup table. From the TSF, accurate pill aperture corrections can be estimated as a function of pill radius with a accuracy of 10 millimags for highly trailed sources. Analogous to the use of small circular apertures and associated aperture corrections, small radius pill apertures can be used to preserve signal-to-noise of low flux sources, with appropriate aperture correction applied to provide an accurate, unbiased flux measurement at all SNR.