Open AccessBayesian joint analysis of cluster weak lensing and Sunyaev–Zel'dovich effect data
Author(s) -
Marshall P. J.,
Hobson M. P.,
Slosar A.
Publication year - 2003
Publication title -
monthly notices of the royal astronomical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.058
H-Index - 383
eISSN - 1365-2966
pISSN - 0035-8711
DOI - 10.1046/j.1365-2966.2003.07111.x
Subject(s) - physics , cosmic microwave background , galaxy cluster , weak gravitational lensing , cluster (spacecraft) , gravitational lens , markov chain monte carlo , sunyaev–zel'dovich effect , astrophysics , cosmic background radiation , statistical physics , bayesian probability , cosmic cancer database , galaxy , redshift , statistics , computer science , optics , programming language , mathematics , anisotropy
As the quality of the available galaxy cluster data improves, the models fitted to these data might be expected to become increasingly complex. Here we present the Bayesian approach to the problem of cluster data modelling: starting from simple, physically motivated parametrized functions to describe the cluster's gas density, gravitational potential and temperature, we explore the high‐dimensional parameter spaces with a Markov‐Chain Monte Carlo sampler, and compute the Bayesian evidence in order to make probabilistic statements about the models tested. In this way sufficiently good data will enable the models to be distinguished, enhancing our astrophysical understanding; in any case the models may be marginalized over in the correct way when estimating global, perhaps cosmological, parameters. In this work we apply this methodology to two sets of simulated interferometric Sunyaev–Zel'dovich effect and gravitational weak lensing data, corresponding to current and next‐generation telescopes. We calculate the expected precision on the measurement of the cluster gas fraction from such experiments, and investigate the effect of the primordial cosmic microwave background (CMB) fluctuations on their accuracy. We find that data from instruments such as the Arcminute Microkelvin Imager (AMI), when combined with wide‐field ground‐based weak lensing data, should allow both cluster model selection and estimation of gas fractions to a precision of better than 30 per cent for a given cluster.