The impact of galaxy formation on satellite kinematics and redshift-space distortions

TL;DR

This paper investigates how galaxy formation processes influence satellite galaxy kinematics and the modeling of redshift-space distortions, emphasizing the importance of accurate models for cosmological parameter estimation.

Contribution

It introduces a flexible parametrization for satellite kinematics that improves modeling of redshift-space distortions across different galaxy selection criteria.

Findings

Different galaxy selection criteria affect satellite distributions and velocities.

Emission line satellites are found in halo outskirts with net infall velocities.

A new parametrization accurately models correlation functions down to sub-Mpc scales.

Abstract

Galaxy surveys aim to map the large-scale structure of the Universe and use redshift space distortions to constrain deviations from general relativity and probe the existence of massive neutrinos. However, the amount of information that can be extracted is limited by the accuracy of theoretical models used to analyze the data. Here, by using the L-Galaxies semi-analytical model run over the MXXL N-body simulation, we assess the impact of galaxy formation on satellite kinematics and the theoretical modelling of redshift-space distortions. We show that different galaxy selection criteria lead to noticeable differences in the radial distributions and velocity structure of satellite galaxies. Specifically, whereas samples of stellar mass selected galaxies feature satellites that roughly follow the dark matter, emission line satellite galaxies are located preferentially in the outskirts of halos and display net infall velocities. We demonstrate that capturing these differences is crucial for modelling the multipoles of the correlation function in redshift space, even on large scales. In particular, we show how modelling small scale velocities with a single Gaussian distribution leads to a poor description of the measure clustering. In contrast, we propose a parametrization that is flexible enough to model the satellite kinematics, and that leads to and accurate description of the correlation function down to sub-Mpc scales. We anticipate that our model will be a necessary ingredient in improved theoretical descriptions of redshift space distortions, which together could result in significantly tighter cosmological constraints and a more optimal exploitation of future large datasets.