SIMBAD references

We study the potential of weak-lensing surveys to detect clusters of galaxies, using a fast particle-mesh cosmological N-body simulation algorithm specifically tailored to investigate the statistics of these shear-selected clusters. In particular, we explore the degree to which the radial positions of galaxy clusters can be determined tomographically, by using photometric redshifts of background source galaxies. We quantify the errors in the tomographic redshifts, Δz≡z_tomography-z_real, and study their dependence on mass, redshift, detection significance, and filtering scheme. For clusters detected with signal-to-noise ratio S/N≳4.5, the fraction of clusters with tomographic redshift errors|Δz|≤0.2 is 45% and the rms deviation from the real redshifts is <(Δz)²>^1/2=0.41, with smaller errors for higher S/N. A tomographic matched filtering (TMF) scheme, which combines tomography and matched filtering, is introduced that optimally detects clusters of galaxies in weak-lensing surveys. The TMF exploits the extra information provided by photometric redshifts of background source galaxies, neglected in previous studies, to optimally weight the sources. The efficacy and reliability of the TMF are investigated using a large ensemble of mock observations from our simulations, and detailed comparisons are made to other filters. Using photometric redshift information with the TMF enhances the number of clusters detected with S/N≳4.5 by as much as 76%, and it increases the dynamic range of weak-lensing searches for clusters, detecting more high-redshift clusters and extending the mass sensitivity down to the scale of large groups. Furthermore, we find that coarse redshift binning of source galaxies with as few as three bins is sufficient to realize the gains of the TMF. Thus, the tomographic filtering techniques presented here can be applied to current ground-based weak-lensing data in as few as three bands, since two colors and magnitude prior are sufficient to bin source galaxies this coarsely. Cosmological applications of shear-selected cluster samples are also discussed.