Spitzer IRAC Photometry for Time Series in Crowded Fields

TL;DR

This paper introduces a new photometry algorithm optimized for crowded and faint targets in Spitzer time series, demonstrating its effectiveness on microlensing data and discussing its potential applicability to Kepler and WFIRST missions.

Contribution

A novel photometry algorithm tailored for crowded fields and faint targets in Spitzer data, with applications to microlensing campaigns and potential use in other space telescopes.

Findings

Successfully applied to 170 targets from the 2015 Spitzer microlensing campaign.

Presented three variants of the algorithm in an online catalog.

Detailed case studies on faint and crowded targets.

Abstract

We develop a new photometry algorithm that is optimized for $Spitzer$ time series in crowded fields and that is particularly adapted to faint and/or heavily blended targets. We apply this to the 170 targets from the 2015 $Spitzer$ microlensing campaign and present the results of three variants of this algorithm in an online catalog. We present detailed accounts of the application of this algorithm to two difficult cases, one very faint and the other very crowded. Several of $Spitzer$'s instrumental characteristics that drive the specific features of this algorithm are shared by $Kepler$ and $WFIRST$, implying that these features may prove to be a useful starting point for algorithms designed for microlensing campaigns by these other missions.