Improving the modelling of redshift-space distortions - II. A pairwise velocity model covering large and small scales

TL;DR

This paper introduces an advanced model for redshift-space correlation functions that accurately describes clustering on large and small scales by incorporating local skewness in velocity distributions, validated against N-body simulations.

Contribution

It extends previous Gaussian models by including local skewness, providing a more precise description of redshift-space distortions across a broad scale range.

Findings

Model matches N-body simulations well

Provides accurate clustering predictions on large and small scales

Extends Gaussian streaming models with skewness consideration

Abstract

We develop a model for the redshift-space correlation function, valid for both dark matter particles and halos on scales $>5\,h^{-1}$Mpc. In its simplest formulation, the model requires the knowledge of the first three moments of the line-of-sight pairwise velocity distribution plus two well-defined dimensionless parameters. The model is obtained by extending the Gaussian-Gaussianity prescription for the velocity distribution, developed in a previous paper, to a more general concept allowing for local skewness, which is required to match simulations. We compare the model with the well known Gaussian streaming model and the more recent Edgeworth streaming model. Using N-body simulations as a reference, we show that our model gives a precise description of the redshift-space clustering over a wider range of scales. We do not discuss the theoretical prescription for the evaluation of the velocity moments, leaving this topic to further investigation.