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arXiv · astro-ph/0501029

Redshift-Space Distortions with the Halo Occupation Distribution I: Numerical Simulations

Abstract

We show how redshift-space distortions of the galaxy correlation function or power spectrum can constrain the matter density parameter Omega_m and the linear matter fluctuation amplitude sigma_8. We improve on previous treatments by adopting a fully non-linear description of galaxy clustering and bias, which allows us to break parameter degeneracies by combining large-scale and small- scale distortions. We consider different combinations of Omega_m and sigma_8 and find parameters of the galaxy halo occupation distribution (HOD) that yield nearly identical galaxy correlation functions in real space. We use these HOD parameters to populate the dark matter halos of large N-body simulations, from which we measure redshift-space distortions on small and large scales. We include a velocity bias parameter alpha_v that allows the velocity dispersions of satellite galaxies in halos to be systematically higher or lower than those of dark matter. Large-scale distortions are determined by the parameter combination beta = Omega_m^{0.6}/b_g, where b_g is the galaxy bias, in agreement with linear theory. However, linear theory does not accurately describe the distortions themselves on scales accessible to our simulations. We provide fitting formulas to estimate beta from the redshift-space correlation function or power spectrum, and we show that these formulas are significantly more accurate than those in the existing literature. On small scales, the ``finger-of-god'' distortions at projected separations ~0.1 Mpc/h depend on Omega_m*alpha_v^2 but are independent of sigma_8, while at intermediate separations they depend on sigma_8 as well. One can thus use redshift-space distortions over a wide range of scales to separately determine Omega_m, sigma_8, and alpha_v. (Abridged)

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BibTeXRIS

Jeremy L. Tinker, David H. Weinberg, Zheng Zheng. 2005-01-04. Redshift-Space Distortions with the Halo Occupation Distribution I: Numerical Simulations. https://doi.org/10.1111/j.1365-2966.2006.10114.x

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