Atmospheric characterization of hot Jupiters using hierarchical models of Spitzer observations

The field of exoplanet atmospheric characterization is trending towards comparative studies involving many planetary systems, and using Bayesian hierarchical modelling is a natural next step. Here we demonstrate two use cases. We first use hierarchical modelling to quantify variability in repeated observations by reanalyzing a suite of ten Spitzer secondary eclipse observations of the hot Jupiter XO-3b. We compare three models: one where we fit ten separate eclipse depths, one where we use a single eclipse depth for all ten observations, and a hierarchical model. By comparing the Widely Applicable Information Criterion of each model, we show that the hierarchical model is preferred over the others. The hierarchical model yields less scatter across the suite of eclipse depths -- and higher precision on the individual eclipse depths -- than does fitting the observations separately. We find that the hierarchical eclipse depth uncertainty is larger than the uncertainties on the individual eclipse depths, which suggests either slight astrophysical variability or that single eclipse observations underestimate the true eclipse depth uncertainty. Finally, we fit a suite of published dayside brightness measurements for 37 planets using a hierarchical model of brightness temperature vs irradiation temperature. The hierarchical model gives tighter constraints on the individual brightness temperatures than the non-hierarchical model. Although we tested hierarchical modelling on Spitzer eclipse data of hot Jupiters, it is applicable to observations of smaller planets like hot neptunes and super earths, as well as for photometric and spectroscopic transit or phase curve observations.
Comment: 11 pages, 7 figures. Accepted for publication by MNRAS. Updated analysis to use the correctly calculated brightness temperature uncertainties from Baxter (2020). Conclusions in second half of paper changed slightly compared to previous version to reflect the new analysis