The democratic detrender: Ensemble-Based Removal of the Nuisance Signal in Stellar Time-Series Photometry

TL;DR

This paper introduces the democratic detrender, an ensemble-based, open-source tool that combines multiple detrending methods to improve the removal of systematic trends in stellar photometry, enhancing exoplanet transit analysis.

Contribution

It presents a modular ensemble approach for detrending stellar light curves, reducing model dependency and propagating uncertainty, which is a novel strategy in this context.

Findings

Reduces risk of poor detrending choices

Increases robustness of light curve analysis

Provides scalable, open-source implementation

Abstract

Accurate, precise, and computationally efficient removal of unwanted activity that exists as a combination of periodic, quasi-periodic, and non-periodic systematic trends in time-series photometric data is a critical step in exoplanet transit analysis. Throughout the years, many different modeling methods have been used for this process, often called "detrending." However, there is no community-wide consensus regarding the favored approach. In order to mitigate model dependency, we present an ensemble-based approach to detrending via community-of-models and the democratic detrender: a modular and scalable open-source coding package that implements ensemble detrending. The democratic detrender allows users to select from a number of packaged detrending methods (including cosine filtering, Gaussian processes, and polynomial fits) or provide their own set of detrended light curves via methods of their choosing. It then combines the individually detrended light curves into a single method marginalized light curve. Additionally, the democratic detrender inflates each data point's uncertainty based on the scatter between detrenders, thereby propagating model-selection uncertainty into the final light curve. This ensemble strategy does not guarantee improvement over the single best-performing detrending method, but it substantially reduces the risk of selecting a detrending solution that is poorly calibrated or overfit to noise.