Modelling non-linear redshift-space distortions in the galaxy clustering pattern: systematic errors on the growth rate parameter
Sylvain de la Torre, Luigi Guzzo

TL;DR
This study evaluates advanced models for redshift-space distortions in galaxy clustering to accurately estimate the growth rate of structure, highlighting the importance of bias and non-linear effects on different galaxy populations.
Contribution
It demonstrates that the Taruya et al. (2010) model provides unbiased growth rate estimates across various galaxy luminosities, improving upon standard models by accounting for non-linearities.
Findings
Taruya et al. (2010) model yields unbiased growth rate estimates within 4%.
Model performance varies with galaxy luminosity and bias scale-dependence.
Systematic errors increase for luminous galaxies due to bias effects.
Abstract
We investigate the ability of state-of-the-art redshift-space distortions models for the galaxy anisotropic two-point correlation function \xi(r_p, \pi), to recover precise and unbiased estimates of the linear growth rate of structure f, when applied to catalogues of galaxies characterised by a realistic bias relation. To this aim, we make use of a set of simulated catalogues at z = 0.1 and z = 1 with different luminosity thresholds, obtained by populating dark-matter haloes from a large N-body simulation using halo occupation prescriptions. We examine the most recent developments in redshift-space distortions modelling, which account for non-linearities on both small and intermediate scales produced respectively by randomised motions in virialised structures and non-linear coupling between the density and velocity fields. We consider the possibility of including the linear component of…
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