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The study of exoplanets (planets orbiting other stars) is revolutionizing theway we view our universe. High-precision photometric data provided by theKepler Space Telescope (Kepler) enables not only the detection of such planets,but also their characterization. This presents a unique opportunity to applyBayesian methods to better characterize the multitude of previously confirmedexoplanets. This paper focuses on applying the EXONEST algorithm tocharacterize the transiting short-period-hot-Jupiter, HAT-P-7b. EXONESTevaluates a suite of exoplanet photometric models by applying Bayesian ModelSelection, which is implemented with the MultiNest algorithm. These models takeinto account planetary effects, such as reflected light and thermal emissions,as well as the effect of the planetary motion on the host star, such as Dopplerbeaming, or boosting, of light from the reflex motion of the host star, andphotometric variations due to the planet-induced ellipsoidal shape of the hoststar. By calculating model evidences, one can determine which model bestdescribes the observed data, thus identifying which effects dominate theplanetary system. Presented are parameter estimates and model evidences forHAT-P-7b.

A Bayesian Analysis of HAT-P-7b Using the EXONEST Algorithm