A new method to search for high redshift clusters using photometric
  redshifts
  We describe a new method (Poisson Probability Method, PPM) to search for high
redshift galaxy clusters and groups by using photometric redshift information
and galaxy number counts. The method relies on Poisson statistics and is
primarily introduced to search for Mpc-scale environments around a specific
beacon. The PPM is tailored to both the properties of the FR I radio galaxies
in the Chiaberge et al. (2009) sample, that are selected within the COSMOS
survey, and on the specific dataset used. We test the efficiency of our method
of searching for cluster candidates against simulations. Two different
approaches are adopted. i) We use two z~1 X-ray detected cluster candidates
found in the COSMOS survey and we shift them to higher redshift up to z=2. We
find that the PPM detects the cluster candidates up to z=1.5, and it correctly
estimates both the redshift and size of the two clusters. ii) We simulate
spherically symmetric clusters of different size and richness, and we locate
them at different redshifts (i.e. z = 1.0,1.5, and 2.0) in the COSMOS field. We
find that the PPM detects the simulated clusters within the considered redshift
range with a statistical 1-sigma redshift accuracy of ~0.05. The PPM is an
efficient alternative method for high-redshift cluster searches that may also
be applied to both present and future wide field surveys such as SDSS Stripe
82, LSST, and Euclid. Accurate photometric redshifts and a survey depth similar
or better than that of COSMOS (e.g. I<25) are required.
