Journal Article

A Bayesian algorithm for model selection applied to caustic-crossing binary-lens microlensing events

N. Kains, P. Browne, K. Horne, M. Hundertmark and A. Cassan

in Monthly Notices of the Royal Astronomical Society

Published on behalf of The Royal Astronomical Society

Volume 426, issue 3, pages 2228-2238
Published in print November 2012 | ISSN: 0035-8711
Published online November 2012 | e-ISSN: 1365-2966 | DOI: http://dx.doi.org/10.1111/j.1365-2966.2012.21813.x
A Bayesian algorithm for model selection applied to caustic-crossing binary-lens microlensing events

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We present a full Bayesian algorithm designed to perform automated searches of the parameter space of caustic-crossing binary-lens microlensing events. This builds on previous work implementing priors derived from Galactic models and geometrical considerations. The geometrical structure of the priors divides the parameter space into well-defined boxes that we explore with multiple Monte Carlo Markov Chains. We outline our Bayesian framework and test our automated search scheme using two data sets: a synthetic light curve, and the observations of OGLE-2007-BLG-472 that we analysed in previous work. For the synthetic data, we recover the input parameters. For OGLE-2007-BLG-472 we find that while χ2 is minimized for a planetary mass-ratio model with extremely long time-scale, the introduction of priors and minimization of the Bayesian information criterion, rather than χ2, favour a more plausible lens model, a binary star with components of 0.78 and 0.11 M at a distance of 6.3 kpc, compared to our previous result of 1.50 and 0.12 M at a distance of 1 kpc.

Keywords: methods: data analysis; methods: statistical; Galaxy: bulge

Journal Article.  6518 words.  Illustrated.

Subjects: Astronomy and Astrophysics

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