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Paper: LRCF: Likelihood Ratio Cluster Finder
Volume: 176, Observational Cosmology: The Development of Galaxy Systems
Page: 97
Authors: Cocco, V.; Scaramella, R.
Abstract: We present a cluster-finding algorithm based on the ratio, {cal R}, of two likelihood functions. Within our approach, based on Poissonian statistics, it is possible to analytically derive the probability distribution functions of {cal R} when a cluster is present or absent in a given region of the sky. This allows a significant improvement in choosing the detection threshold(s), by exact computation of the probability of missing or misidentifying a cluster. The formalism can be applied assuming a variety of cluster models and prior information and, under simple hypotheses, it only requires a photometric catalog of objects and not one of galaxies. This allows to go deeper in the selection of candidate clusters, since typically the star-galaxy separation does not reach the limiting magnitude of the catalog of objects. We present the main formulae and some preliminary results from simulations and applications.
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