Bayes-X: a Bayesian inference tool for the analysis of X-ray observations of galaxy clusters

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 generalised NFW (GNFW) profile. We then perform four sets of analyses. By numerically exploring the joint probability distribution of the cluster parameters given simulated Chandra-like data, we show that the model 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 analyse Chandra data on the nearby cluster, A262, and derive the cluster physical profiles. 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/.

Mass and pressure constraints on galaxy clusters from interferometric SZ observations

Following on our previous study of an analytic parametric model to describe the baryonic and dark matter distributions in clusters of galaxies with spherical symmetry, we perform an SZ analysis of a set of simulated clusters and present their mass and pressure profiles. The simulated clusters span a wide range in mass, 2.0 x 10^14 Msun < M200 < 1.0 x 10^15Msun, and observations with the Arcminute Microkelvin Imager (AMI) are simulated through their Sunyaev- Zeldovich (SZ) effect. We assume that the dark matter density follows a Navarro, Frenk and White (NFW) profile and that the gas pressure is described by a generalised NFW (GNFW) profile. By numerically exploring the probability distributions of the cluster parameters given simulated interferometric SZ data in the context of Bayesian methods, we investigate the capability of this model and analysis technique to return the simulated clusters input quantities. We show that considering the mass and redshift dependency of the cluster halo concentration parameter is crucial in obtaining an unbiased cluster mass estimate and hence deriving the radial profiles of the enclosed total mass and the gas pressure out to r200.

A simple parametric model for spherical galaxy clusters

We present an analytic parametric model to describe the baryonic and dark matter distributions in clusters of galaxies with spherical symmetry. It is assumed that the dark matter density follows a Navarro, Frenk and White (NFW) profile and that the gas pressure is described by a generalised NFW (GNFW) profile. By further demanding hydrostatic equilibrium and that the gas fraction is small throughout the cluster, one obtains unique functional forms, dependent on basic cluster parameters, for the radial profiles of all the properties of interest in the cluster. We show these profiles are consistent both with numerical simulations and multi-wavelength observations of clusters. We also use our model to analyse six simulated SZ clusters as well as A611 SZ data from the Arcminute Microkelvin Imager (AMI). In each case, we derive the radial profile of the enclosed total mass and the gas pressure and show that the results are in good agreement with our model prediction.