Abstract
This paper presents MoLUSC, a new method for generating mock galaxy catalogs from a large scale ($\approx 1000^3$ Mpc$^3$) dark matter simulation, that requires only modest CPU time and memory allocation. The method uses a small-scale ($\approx 256^3$ Mpc$^3$) dark matter simulation on which the \galics semi-analytic code has been run in order to define the transformation from dark matter density to galaxy density transformation 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 which have been conducted to validate the method, and demonstrate a first application to generate a mock Sloan Digital Sky Survey redshift survey.
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