Poster abstract details

Bayesian inference with the MultiNest algorithm
Johannes Rothe, Chelsea Huang, Johnny Greco


The MultiNest algorithm (e.g. DOI 10.1111/j.1365-2966.2009.14548.x) is an efficient numerical tool for parameter fitting and model selection that significantly outperforms traditional Markov chain Monte Carlo methods in a wide range of astrophysical problems. It is built upon the nested sampling technique and optimized for performance in problems with multimodal posteriors and curving degeneracies. In the last years, MultiNest has found wide use in cosmology as well as exoplanet studies. We will present the methods underlying MultiNest's success, introduce an independent C/C++ implementation of the algorithm and describe applications of our code.