PTHALOS: a fast method for generating mock galaxy distributions

摘要: Current models of galaxy formation applied to understanding the large-scale structure Universe have two parts. The first is an accurate solution equations motion for dark matter caused by gravitational clustering. second consists making physically reasonable approximations behaviour baryons inside haloes. uses large, computationally intensive, N-body simulations. We argue that because step is, at least present, uncertain, it possible obtain similar distributions without solving exactly. We describe algorithm several orders magnitude faster than simulations, but nevertheless, rather accurate. combines perturbation theory with virialized halo non-linear density and velocity fields. For two- three-point statistics resulting fields are exact on large scales, well into regime, particularly two-point in real redshift space. then show how one can use this generate mock from occupation numbers. As a application, we provides good description clustering galaxies PSCz survey. We also discuss applications estimation non-Gaussian contributions error bars covariance matrix power spectrum, space, matter. results latter agreement supporting our method constraining cosmological parameters forthcoming surveys.