Constraints on shear and rotation with massive galaxy clusters

TL;DR

This study uses massive galaxy cluster data to constrain deviations from sphericity due to shear and rotation within the extended spherical collapse model, refining cosmological parameters in a ΛCDM framework.

Contribution

It introduces a logarithmic functional form for the deviation parameter and provides new constraints on cosmological parameters using galaxy cluster data.

Findings

Constraints on Ω_m, h, and β within ΛCDM model

A 9% decrease in the predicted number of massive clusters

Upper limits on deviation parameters at higher confidence levels

Abstract

A precise determination of the mass function is an important tool to verify cosmological predictions of the $\Lambda$CDM model and to infer more precisely the better model describing the evolution of the Universe. Galaxy clusters have been currently used to infer cosmological parameters, in particular the matter density parameter $\Omega_{\rm m}$, the matter power spectrum normalization $\sigma_8$ and the equation of state parameter $w_{\rm de}$ of the dark energy fluid. In this work, using data on massive galaxy clusters ($M>8\times 10^{14}~h^{-1}~M_{\odot}$) in the redshift range $0.05\lesssim z\lesssim 0.83$ we put constraints on the parameter $\alpha$ introduced within the formalism of the extended spherical collapse model to quantify deviations from sphericity due to shear and rotation. Since at the moment there is no physical model describing its functional shape, we assume it to be a logarithmic function of the cluster mass. By holding $\sigma_8$ fixed and restricting our analysis to a $\Lambda$CDM model, we find, at $1-\sigma$ confidence level, $\Omega_{\rm m}=0.284\pm0.0064$, $h=0.678\pm0.017$ and $\beta=0.0019^{+0.0008}_{-0.0015}$, where $\beta$ represents the slope of the parameter $\alpha$. This results translates into a $9\%$ decrement of the number of massive clusters with respect to a standard $\Lambda$CDM mass function, but better data are required to better constrain this quantity, since at the $2-\sigma$ and $3-\sigma$ confidence level we are only able to infer upper limits.