QLP Data Release Notes 004: TESS-Gaia Light Curve Photometry Implementation

TL;DR

This paper introduces an improved photometry method for the TESS-QPL pipeline, adopting TESS-Gaia Light Curve techniques to enhance noise performance and enable detection of fainter signals in star light curves.

Contribution

It implements TESS-Gaia Light Curve photometry within QLP, improving noise characteristics and detection capabilities for fainter stars in TESS data.

Findings

Higher precision light curves for stars with T magnitude 10.5-13.5.

Enhanced detection of faint signals in TESS data.

Seamless integration with existing QLP pipeline.

Abstract

The Quick-Look Pipeline (QLP; Huang et al. 2020, Kunimoto et al. 2021 and references therein) generates light curves for up to 2 million stars every 27.4 days observed by TESS as part of its planet search. As machine learning methods enable deeper searches and scientific priorities shift toward fainter stars, there is a motivation for QLP to perform better at fainter magnitudes. We have adopted the photometry methods employed by the TESS-Gaia Light Curve package (Han & Brandt 2023), which has been shown to have better noise characteristics than the original QLP photometry from 10.5 $<$ $T$ $<$ 13.5. We still perform aperture photometry and deliver 3 apertures, and 3 levels of detrending for all stars brighter than $T$ = 13.5, so the changes should be seamless for external users. This method is implemented as of Sector 94 in QLP light curves and is providing users with higher precision light curves and allows detection of fainter signals in our planet searches.