Searching for massive clusters in weak lensing surveys
Abstract
We explore the ability of weak lensing surveys to locate massive clusters. We use both an analytic model of dark matter halos and mock weak lensing surveys generated from a large cosmological N-body simulation. The analytic model describes average properties of weak lensing halos and predicts the number counts of the halos, enabling us to compute an effective survey selection function. We test the model prediction for the weak lensing peak counts against the numerical simulations, and find that the noise due to intrinsic galaxy ellipticities causes a systematic effect which increases the peak number counts. We develop a correction scheme for the systematic effect in an empirical manner, and show that, after the correction, the model prediction agrees well with the mock data. Using the mock data, we also examine the completeness and efficiency of the weak lensing halo search with fully taking into account the noise and the so-called projection effect by large-scale structures. We show that the detection threshold of S/N=4-5 gives an optimal balance between efficiency and completeness. Our results suggest that, for a weak lensing survey with a galaxy number density of ng=30/arcmin^2 with a mean redshift z=1, the mean number of peaks is Npeak=65 per 10 square degrees for a detection threshold S/N=4. The contamination rate is 44%, and thus, on average, 36 out of 65 peaks (at least) are signals from real halos. Weak lensing surveys thus provide a reasonably efficient way to searching for massive clusters.Keywords
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