Linearized Field Deblending: PSF Photometry for Impatient Astronomers
Christina Hedges, Rodrigo Luger, Jorge Martinez Palomera, Jessie, Dotson, Geert Barentsen

TL;DR
This paper introduces Linearized Field Deblending (LFD), a fast and effective PSF fitting method that improves photometry accuracy in crowded stellar fields for space missions like Kepler and TESS.
Contribution
The paper presents a simplified, linear PSF fitting approach that reduces computational costs while accurately deblending crowded stellar sources in space-based photometry data.
Findings
Successfully separates blended sources in Kepler data
Accurately identifies the nature of a contaminating transiting signal
Demonstrates applicability to TESS data
Abstract
NASA's Kepler, K2 and TESS missions employ Simple Aperture Photometry (SAP) to derive time-series photometry, where an aperture is estimated for each star, and pixels containing each star are summed to create a single light curve. This method is simple, but in crowded fields the derived time-series can be highly contaminated. The alternate method of fitting a Point Spread Function (PSF) to the data is able to account for crowding, but is computationally expensive. In this paper, we present a new approach to extracting photometry from these time-series missions, which fits the PSF directly, but makes simplifying assumptions in order to greatly reduce the computation expense. Our method fixes the scene of the field in each image, estimates the PSF shape of the instrument with a linear model, and allows only source flux and position to vary. We demonstrate that our method is able to…
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