Cosmological parameter determination in free-form strong gravitational lens modelling

We develop a novel statistical strong-lensing approach to probe the cosmological parameters by exploiting multiple redshift image systems behind galaxies or galaxy clusters. The method relies on free-form mass inversion of strong lenses and does not need any additional information other than gravitational lensing. Since in free-form lensing the solution space is a high-dimensional convex polytope, we consider Bayesian model comparison analysis to infer the cosmological parameters. The volume of the solution space is taken as a tracer of the probability of the underlying cosmological assumption. In contrast to parametric mass inversions, our method accounts for the mass-sheet degeneracy, which implies a degeneracy between the steepness of the profile and the cosmological parameters. Parametric models typically break this degeneracy, introducing hidden priors to the analysis that contaminate the inference of the parameters. We test our method with synthetic lenses, showing that it is able to infer the assumed cosmological parameters. Applied to the Cluster Lensing And Supernova survey with Hubble (CLASH) clusters, the method might be competitive with other probes. DOI: https://doi.org/10.1093/mnras/stt2057 Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-98139 Published Version Originally published at: Lubini, M; Sereno, M; Coles, J; Jetzer, P; Saha, P (2014). Cosmological parameter determination in free-form strong gravitational lens modelling. Monthly Notices of the Royal Astronomical Society, 437(3):2461-2470. DOI: https://doi.org/10.1093/mnras/stt2057 MNRAS 437, 2461–2470 (2014) doi:10.1093/mnras/stt2057 Advance Access publication 2013 November 30 Cosmological parameter determination in free-form strong gravitational lens modelling M. Lubini,1‹ M. Sereno,2,3 J. Coles,1 Ph. Jetzer1 and P. Saha1 1Institut für Theoretische Physik, Universität Zürich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland 2Dipartimento di Scienza Applicata e Tecnologia, Politecnico di Torino, Corso Duca degli Abruzzi 24, I-10129 Torino, Italia 3INFN, Sezione di Torino, Via Pietro Giuria 1, I-10125 Torino, Italia Accepted 2013 October 23. Received 2013 September 24; in original form 2013 April 26