Arc statistics with realistic cluster models
Massimo Meneghetti, Matthias Bartelmann, Lauro Moscardini, Elena Rasia, Giuseppe Tormen, Elena Torri
Abstract
Arc statistics is known to be a powerful cosmological tool. Numerical lensing simulations show that orders of magnitude differences in the number of giant arcs on the whole sky are expected in different cosmological models. In this paper, we discuss the analytic and numerical methods in arc statistics and show that analytic models fail to reproduce the efficiency for strong lensing of more realistic numerical cluster models. Then, we discuss two recent extensions of the lensing simulations, i.e. the effects of cD galaxies in the lensing clusters and the impact of cluster mergers on arc statistics. We show that cD galaxies can increase the lensing cross sections for long and thin arcs by perhaps up to 50%, while major mergers can change the cluster efficiency for producing such arcs by up to one order of magnitude.
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