Special Astrophysics Seminar

Detecting Extra-solar Planets with a Bayesian hybrid MCMC Kepler periodogram

Phil Gregory

Department of Physics & Astronomy
UBC

A Bayesian re-analysis of published radial velocity data sets is providing evidence for additional planetary candidates. The nonlinear model fitting is accomplished with a new hybrid Markov chain Monte Carlo (HMCMC) algorithm which incorporates parallel tempering, simulated annealing and the genetic algorithm. Each of these components facilitate the detection of a global minimum in χ². By combining all three, the HMCMC greatly increase the probability of realizing this goal in a blind search of the parameter space. When applied to the Kepler problem it acts as a powerful multi-planet Kepler periodogram for both parameter estimation and model selection. The HMCMC algorithm is very general and applicable to many other nonlinear model fitting problems.