The SARS algorithm: detrending CoRoT light curves with Sysrem using simultaneous external parameters

TL;DR

This paper introduces the SARS algorithm, an extension of Sysrem that incorporates external parameters to better detrend CoRoT light curves, reducing red noise and improving exoplanet transit detection.

Contribution

The paper presents a generalized Sysrem algorithm that simultaneously models external parameters and systematic effects, enhancing transit detection in space-based survey data.

Findings

The SARS algorithm effectively reduces red noise in CoRoT data.

It enables detection of previously missed transit-like signals.

The method improves exoplanet transit identification accuracy.

Abstract

Surveys for exoplanetary transits are usually limited not by photon noise but rather by the amount of red noise in their data. In particular, although the CoRoT spacebased survey data are being carefully scrutinized, significant new sources of systematic noises are still being discovered. Recently, a magnitude-dependant systematic effect was discovered in the CoRoT data by Mazeh & Guterman et al. and a phenomenological correction was proposed. Here we tie the observed effect a particular type of effect, and in the process generalize the popular Sysrem algorithm to include external parameters in a simultaneous solution with the unknown effects. We show that a post-processing scheme based on this algorithm performs well and indeed allows for the detection of new transit-like signals that were not previously detected.