%0 Generic %1 garciafarieta2019validating %A García-Farieta, Jorge Enrique %A Marulli, Federico %A Moscardini, Lauro %A Veropalumbo, Alfonso %A Casas-Miranda, Rigoberto A. %D 2019 %K observations %T Validating the methodology for constraining the linear growth rate from clustering anisotropies %U http://arxiv.org/abs/1909.08016 %X 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 $0.5złesssim2$. 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 $z 0.5\%$, 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 $z\geq1$.

@misc{garciafarieta2019validating, abstract = {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 $z\geq1$.}, added-at = {2019-09-23T06:35:37.000+0200}, author = {García-Farieta, Jorge Enrique and Marulli, Federico and Moscardini, Lauro and Veropalumbo, Alfonso and Casas-Miranda, Rigoberto A.}, biburl = {https://www.bibsonomy.org/bibtex/2db6d46c07e8c0b61f765cc0527187db4/rana_7690}, description = {Validating the methodology for constraining the linear growth rate from clustering anisotropies}, interhash = {4859491d3ab1492f55942e91075ce860}, intrahash = {db6d46c07e8c0b61f765cc0527187db4}, keywords = {observations}, note = {cite arxiv:1909.08016Comment: 17 pages, 14 figures, submitted to MNRAS}, timestamp = {2019-09-25T22:58:39.000+0200}, title = {Validating the methodology for constraining the linear growth rate from clustering anisotropies}, url = {http://arxiv.org/abs/1909.08016}, year = 2019 }