Tidal virialization of dark matter haloes with clustering dark energy

TL;DR

This paper models the virialization process in dark matter haloes considering clustering dark energy, revealing that dark-energy fluctuations significantly impact observable structures and can distinguish models from standard cosmology.

Contribution

It introduces a novel approach to virialization incorporating dark-energy fluctuations and tidal effects, extending previous models and analyzing their observational implications.

Findings

Clustering dark energy models can be distinguished from b5b5CDM using large-scale surveys.

Dark-energy fluctuations significantly influence the abundance of weak-lensing, SZ, and X-ray peaks.

Differences in virial overdensity are small but detectable with high signal-to-noise observations.

Abstract

We extend the analysis of Pace et al., JCAP, 2019, 060, by considering the virialization process in the extended spherical collapse model for clustering dark-energy models, i.e., accounting for dark-energy fluctuations. Differently from the standard approach, here virialization is naturally achieved by properly modelling deviations from sphericity due to shear and rotation induced by tidal interactions. We investigate the time evolution of the virial overdensity $\Delta_\mathrm{vir}$ in seven clustering dynamical dark energy models and compare the results to the $\Lambda$CDM model and to the corresponding smooth dark-energy models. Taking into account all the appropriate corrections, we deduce the abundance of convergence peaks for Rubin Observatory-LSST and Euclid-like weak-lensing surveys, of Sunyaev-Zel'dovich peaks for a Simon Observatory-like CMB survey, and of X-ray peaks for an eROSITA-like survey. Despite the tiny differences in $\Delta_\mathrm{vir}$ between clustering and smooth dark-energy models, owing to the large volumes covered by these surveys, five out of seven clustering dark-energy models can be statistically distinguished from $\Lambda$CDM. The contribution of dark-energy fluctuation cannot be neglected, especially for the Chevallier-Polarski-Limber and Albrecht-Skordis models, provided the instrumental configurations provide high signal-to-noise ratio. These results are almost independent of the tidal virialization model.