Reliable inference of exoplanet light curve parameters using deterministic and stochastic systematics models

Abstract

Time-series photometry and spectroscopy of transiting exoplanets allow us to study their atmospheres. Unfortunately, the required precision to extract atmospheric information surpasses the design specifications of most general purpose instrumenta-tion, resulting in instrumental systematics in the light curves that are typically larger than the target precision. Systematics must therefore be modelled, leaving the infer-ence of light curve parameters conditioned on the subjective choice of systematics models and model selection criteria. This paper aims to test the reliability of the most commonly used deterministic systematics models and model selection criteria. As we are primarily interested in recovering light curve parameters rather than the favoured systematics model, marginalisation over systematics models is introduced as a more robust alternative than simple model selection. This can incorporate uncertainties in the choice of systematics model into the error budget as well as the model parameters. Its use is demonstrated using a series of simulated transit light curves. Stochastic mod-els, specifically Gaussian processes, are also discussed in the context of marginalisatio