BAYES-X: A Bayesian inference tool for the analysis of X-ray observations of galaxy clusters

Abstract

We present the first public release of our Bayesian inference tool, BAYES-X, for the analysis of X-ray observations of galaxy clusters. We illustrate the use of BAYES-X by analysing a set of four simulated clusters at z = 0.2-0.9 as they would be observed by a Chandra-like X-ray observatory. In both the simulations and the analysis pipeline we assume that the dark matter density follows a spherically symmetric Navarro, Frenk and White (NFW) profile and that the gas pressure is described by a generalized NFW (GNFW) profile. We then perform four sets of analyses. These include prior-only analyses and analyses in which we adopt wide uniform prior probability distributions on fg(r200) and on the model parameters describing the shape and slopes of the GNFW pressure profile, namely (c500, a, b, c). By numerically exploring the joint probability distribution of the cluster parameters given simulated Chandra-like data, we show that themodel and analysis technique can robustly return the simulated cluster input quantities, constrain the cluster physical parameters and reveal the degeneracies among the model parameters and cluster physical parameters.We then use BAYES-X to analyse Chandra data on the nearby cluster, A262, and derive the cluster physical and thermodynamic profiles. The results are in good agreement with other results given in literature for the cluster. To illustrate the performance of the Bayesian model selection, we also carried out analyses assuming an Einasto profile for the matter density and calculated the Bayes factor. The results of the model selection analyses for the simulated data favour the NFW model as expected. However, we find that the Einasto profile is preferred in the analysis of A262. The BAYES-X software, which is implemented in Fortran 90, is available at http://www.mrao.cam.ac.uk/facilities/software/bayesx/.