A Bayesian Periodogram Finds Evidence for Three Planets in 47 Ursae Majoris
Philip C. Gregory, Debra A. Fischer

TL;DR
This paper introduces a Bayesian periodogram method using a hybrid MCMC algorithm to detect multiple planets in radial velocity data, successfully identifying three planets around 47 Ursae Majoris with refined orbital parameters.
Contribution
It presents a novel hybrid MCMC algorithm for multi-planet detection and applies it to 47 Ursae Majoris, confirming two known planets and discovering a third, with improved orbital parameter estimation.
Findings
Confirmed two known planets with refined periods and eccentricities.
Detected a third long-period planet with high confidence.
Developed a noise bias correction filter for eccentricity detection.
Abstract
A Bayesian analysis of 47 Ursae Majoris (47 UMa) radial velocity data confirms and refines the properties of two previously reported planets with periods of 1079 and 2325 days and finds evidence for an additional long period planet with a period of approximately 10000 days. The three planet model is found to be 10^5 times more probable than the next most probable model which is a two planet model. The nonlinear model fitting is accomplished with a new hybrid Markov chain Monte Carlo (HMCMC) algorithm which incorporates parallel tempering, simulated annealing and genetic crossover operations. Each of these features facilitate the detection of a global minimum in chi-squared. By combining all three, the HMCMC greatly increases the probability of realizing this goal. When applied to the Kepler problem it acts as a powerful multi-planet Kepler periodogram. The measured periods are 1078 \pm…
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