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We describe a new method (Poisson Probability Method, PPM) to search for highredshift galaxy clusters and groups by using photometric redshift informationand galaxy number counts. The method relies on Poisson statistics and isprimarily introduced to search for Mpc-scale environments around a specificbeacon. The PPM is tailored to both the properties of the FR I radio galaxiesin the Chiaberge et al. (2009) sample, that are selected within the COSMOSsurvey, and on the specific dataset used. We test the efficiency of our methodof searching for cluster candidates against simulations. Two differentapproaches are adopted. i) We use two z~1 X-ray detected cluster candidatesfound in the COSMOS survey and we shift them to higher redshift up to z=2. Wefind that the PPM detects the cluster candidates up to z=1.5, and it correctlyestimates both the redshift and size of the two clusters. ii) We simulatespherically symmetric clusters of different size and richness, and we locatethem at different redshifts (i.e. z = 1.0,1.5, and 2.0) in the COSMOS field. Wefind that the PPM detects the simulated clusters within the considered redshiftrange with a statistical 1-sigma redshift accuracy of ~0.05. The PPM is anefficient alternative method for high-redshift cluster searches that may alsobe applied to both present and future wide field surveys such as SDSS Stripe82, LSST, and Euclid. Accurate photometric redshifts and a survey depth similaror better than that of COSMOS (e.g. I<25) are required.

A new method to search for high redshift clusters using photometric redshifts