Abstract
This paper presents MoLUSC, a new method for generating mock galaxy catalogs from a large-scale (≈10003 Mpc3) dark matter simulation, which requires only modest CPU time and memory allocation. The method uses a small-scale (≈1503 Mpc3) dark matter simulation on which the GalICS semianalytic code has been run in order to define the transformation from dark matter density to galaxy density using a probabilistic treatment. MoLUSC is then applied to a large-scale dark matter simulation in order to produce a realistic distribution of galaxies and their associated spectra. This permits the fast generation of large-scale mock surveys using relatively low-resolution simulations. We describe various tests that have been conducted to validate the method and illustrate it by generating a mock Sloan Digital Sky Survey redshift survey.
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