Approximate Methods for the Generation of Dark Matter Halo Catalogs in the Age of Precision Cosmology

Precision cosmology has recently triggered new attention on the topic of approximate methods for the clustering of matter on large scales, whose foundations date back to the period from late '60s to early '90s. Indeed, although the prospect of reaching sub-percent accuracy in the measurement of clustering poses a challenge even to full N-body simulations, an accurate estimation of the covariance matrix of clustering statistics, not to mention the sampling of parameter space, requires usage of a large number (hundreds in the most favourable cases) of simulated (mock) galaxy catalogs. Combination of few N-body simulations with a large number of realizations performed with approximate methods gives the most promising approach to solve these problems with a reasonable amount of resources. In this paper I review this topic, starting from the foundations of the methods, then going through the pioneering efforts of the '90s, and finally presenting the latest extensions and a few codes that are now being used in present-generation surveys and thoroughly tested to assess their performance in the context of future surveys.