Astronomy and Astrophysics – Astrophysics
Scientific paper
2008-05-23
Astronomy and Astrophysics
Astrophysics
Accepted to MNRAS, 11 pages, 10 figures. Minor changes in Section 2, Appendix removed . ExoFit can be downloaded from http:/
Scientific paper
10.1111/j.1365-2966.2008.14385.x
Retrieval of orbital parameters of extrasolar planets poses considerable statistical challenges.Due to sparse sampling, measurement errors, parameters degeneracy and modelling limitations, there are no unique values of basic parameters, such as period and eccentricity. Here, we estimate the orbital parameters from radial velocity data in a Bayesian framework by utilizing Markov Chain Monte Carlo (MCMC) simulations with the Metropolis-Hastings algorithm. We follow a methodology recently proposed by Gregory and Ford. Our implementation of MCMC is based on the object-oriented approach outlined by Graves. We make our resulting code, ExoFit, publicly available with this paper. It can search for either one or two planets as illustrated on mock data. As an example we re-analysed the orbital solution of companions to HD 187085 and HD 159868 from the published radial velocity data. We confirm the degeneracy reported for orbital parameters of the companion to HD 187085, and show that a low-eccentricity orbit is more probable for this planet. For HD 159868, we obtained slightly different orbital solution and a relatively high 'noise' factor indicating the presence of an unaccounted signal in the radial velocity data. ExoFit is designed in such a way that it can be extended for a variety of probability models, including different Bayesian priors.
Balan Sreekumar T.
Lahav Ofer
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