A Bayesian approach to strong lensing modelling of galaxy clusters

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dc.creatorJullo, Eric
dc.creatorKneib, Jean-Paul
dc.creatorLimousin, Marceau
dc.creatorElíasdóttir, Árdis
dc.creatorMarshall, Phil
dc.creatorVerdugo, Tomas
dc.date2007-06-01
dc.date2007-12-26
dc.date.accessioned2026-07-07T11:16:30Z
dc.date.available2026-07-07T11:16:30Z
dc.descriptionIn this paper, we describe a procedure for modelling strong lensing galaxy clusters with parametric methods, and to rank models quantitatively using the Bayesian evidence. We use a publicly available Markov chain Monte-Carlo (MCMC) sampler ('Bayesys'), allowing us to avoid local minima in the likelihood functions. To illustrate the power of the MCMC technique, we simulate three clusters of galaxies, each composed of a cluster-scale halo and a set of perturbing galaxy-scale subhalos. We ray-trace three light beams through each model to produce a catalogue of multiple images, and then use the MCMC sampler to recover the model parameters in the three different lensing configurations. We find that, for typical Hubble Space Telescope (HST)-quality imaging data, the total mass in the Einstein radius is recovered with ~1-5% error according to the considered lensing configuration. However, we find that the mass of the galaxies is strongly degenerated with the cluster mass when no multiple images appear in the cluster centre. The mass of the galaxies is generally recovered with a 20% error, largely due to the poorly constrained cut-off radius. Finally, we describe how to rank models quantitatively using the Bayesian evidence. We confirm the ability of strong lensing to constrain the mass profile in the central region of galaxy clusters in this way. Ultimately, such a method applied to strong lensing clusters with a very large number of multiple images may provide unique geometrical constraints on cosmology. The implementation of the MCMC sampler used in this paper has been done within the framework of the Lenstool software package, which is publicly available.
dc.descriptionAccepted to "Gravitational Lensing" Focus Issue of the New Journal of Physics (invited), 35 pages, 11 figures at reduced resolution
dc.identifierhttps://arxiv.org/abs/0706.0048
dc.identifierhttp://arxiv.org/abs/0706.0048
dc.identifierNewJ.Phys.9:447,2007
dc.identifierdoi:10.1088/1367-2630/9/12/447
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/192693
dc.subjectAstrophysics
dc.titleA Bayesian approach to strong lensing modelling of galaxy clusters
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