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

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 $\texttt{democratic detrender}$: a modular and scalable open-source coding package that implements ensemble detrending. The $\texttt{democratic detrender}$ 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. The $\texttt{democratic detrender}$ then combines the resulting individually detrended light curves into a single method marginalized (via median selection) light curve. Additionally, the $\texttt{democratic detrender}$ inflates the uncertainties of each time-series data point using information from the median absolute deviation between the individually detrended light curve, propagating information into the final detrended light curve about the added uncertainty due to the correctness of the underlying models.