Characterizing the optical properties of galaxy clusters with GMPhoRCC

We introduce the Gaussian Mixture full Photometric Red sequence Cluster Characteriser (GMPhoRCC), an algorithm for determining the redshift and richness of a galaxy cluster candidate. By using data from a multiband sky survey with photometric redshifts, a red sequence colour-magnitude relation (CMR) is isolated and modelled and used to characterize the optical properties of the candidate. GMPhoRCC provides significant advantages over existing methods, including treatment of multimodal distributions, variable width full CMR red sequence, richness extrapolation and quality control in order to algorithmically identify catastrophic failures. We present redshift comparisons for clusters from the GMBCG, NORAS, REFLEX and XMM Cluster Survey catalogues, where the GMPhoRCC estimates are in excellent agreement with spectra, showing accurate, unbiased results with low scatter (sigma(delta z/(1+z)) similar to 0.017). We conclude with the evaluation of GMPhoRCC performance using empirical Sloan Digital Sky Survey (SDSS) like mock galaxy clusters. GMPhoRCC is shown to produce highly pure characterizations with very low probabilities (<1 per cent) of spurious, clean characterizations. In addition, GMPhoRCC is shown to demonstrate high rates of completeness with respect to recovering redshift, richness and correctly identifying the brightest cluster galaxy (BCG).