http://arxiv.org/abs/1909.08016

Redshift-space clustering distortions provide one of the most powerful probes to test the gravity theory on the largest cosmological scales. In this paper we perform a systematic validation study of the state-of-the-art statistical methods currently used to constrain the linear growth rate from redshift-space distortions in the galaxy two-point correlation function. The numerical pipelines are tested on mock halo catalogues extracted from large N-body simulations of the standard cosmological framework, in the redshift range $0.5\lesssim z\lesssim2$. We consider both the monopole and quadrupole multipole moments of the redshift-space two-point correlation function, as well as the radial and transverse clustering wedges, in the comoving scale range $10<r[$\Mpch$]<55$. Moreover, we investigate the impact of redshift measurement errors, up to $\delta z \sim 0.5\%$, which introduce spurious clustering anisotropies. We quantify the systematic uncertainties on the growth rate and linear bias measurements due to the assumptions in the redshift-space distortion model. Considering both the dispersion model and two widely-used models based on perturbation theory, that is the Scoccimarro model and the TNS model, we find that the linear growth rate is underestimated by about $5-10\%$ at $z<1$, while limiting the analysis at larger scales, $r>30$ \Mpch, the discrepancy is reduced below $5\%$. At higher redshifts, we find instead an overall good agreement between measurements and model predictions. The TNS model is the one which performs better, with growth rate uncertainties below about $3\%$. The effect of redshift errors is degenerate with the one of small-scale random motions, and can be marginalised over in the statistical analysis, not introducing any statistically significant bias in the linear growth constraints, especially at $z\geq1$.

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J. García-Farieta, F. Marulli, L. Moscardini, et. al.
Thu, 19 Sep 19
12/71

Comments: 17 pages, 14 figures, submitted to MNRAS