Bayesian cluster finder: Clusters in the CFHTLS Archive Research Survey

Abstract

The detection of galaxy clusters in present and future surveys enables measuring mass-to-light ratios, clustering properties, galaxy cluster abundances and, therefore, constraining cosmological parameters. We present a new technique for detecting galaxy clusters, which is based on the matched filter algorithm from a Bayesian point of view. The method is able to determine the position, redshift and richness of the cluster through the maximization of a filter depending on galaxy luminosity, density and photometric redshift combined with a galaxy cluster prior that accounts for colour-magnitude relations and brightest cluster galaxy-redshift relation. We tested the algorithm through realistic mock galaxy catalogues, revealing that the detections are 100 per cent complete and 80 per cent pure for clusters up to z < 1.2 and richer than Λ CL > 20 (Abell richness ~0, M~ 4 × 10 14M ⊙). The completeness and purity remain approximately the same if we do not include the prior information, implying that this method is able to detect galaxy cluster with and without a well-defined red sequence. We applied the algorithm to the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) Archive Research Survey data, recovering similar detections as previously published using the same or deeper data plus additional clusters which appear to be real. © 2011 The Authors Monthly Notices of the Royal Astronomical Society © 2011 RAS.