  The study of exoplanets (planets orbiting other stars) is revolutionizing the
way we view our universe. High-precision photometric data provided by the
Kepler Space Telescope (Kepler) enables not only the detection of such planets,
but also their characterization. This presents a unique opportunity to apply
Bayesian methods to better characterize the multitude of previously confirmed
exoplanets. This paper focuses on applying the EXONEST algorithm to
characterize the transiting short-period-hot-Jupiter, HAT-P-7b. EXONEST
evaluates a suite of exoplanet photometric models by applying Bayesian Model
Selection, which is implemented with the MultiNest algorithm. These models take
into 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 Doppler
beaming, or boosting, of light from the reflex motion of the host star, and
photometric variations due to the planet-induced ellipsoidal shape of the host
star. By calculating model evidences, one can determine which model best
describes the observed data, thus identifying which effects dominate the
planetary system. Presented are parameter estimates and model evidences for
HAT-P-7b.
