The Galaxy Number Density Profile of Haloes

TL;DR

This paper introduces a new galaxy number density profile for dark matter haloes, improving predictions of galaxy positions and clustering compared to the traditional NFW profile, validated through simulations and observational data.

Contribution

A novel galaxy number density profile model that better matches galaxy distribution and clustering than the NFW profile, validated with simulations and SDSS data.

Findings

Accurately reproduces halo occupation distribution and galaxy two-point correlation functions.

More precise predictions of galaxy positions within haloes.

Outperforms the NFW profile in modeling galaxy clustering.

Abstract

More precise measurements of galaxy clustering will be provided by the next generation of galaxy surveys such as DESI, WALLABY and SKA. To utilize this information to improve our understanding of the Universe, we need to accurately model the distribution of galaxies in their host dark matter halos. In this work we present a new galaxy number density profile of haloes, which makes predictions for the positions of galaxies in the host halo, different to the widely adopted Navarro-Frenk-White (NFW) profile, since galaxies tend to be found more in the outskirts of halos (nearer the virial radius) than an NFW profile. The parameterised galaxy number density profile model of haloes is fit and tested using the DARKSAGE semi-analytic model of galaxy formation. We find that our galaxy number density profile model of haloes can accurately reproduce the halo occupation distribution and galaxy two-point correlation function of the DARKSAGE simulation. We also derive the analytic expressions for the circular velocity and gravitational potential energy for this profile model. We use the SDSS DR10 galaxy group catalogue to validate this galaxy number density profile model of haloes. Compared to the NFW profile, we find that our model more accurately predicts the positions of galaxies in their host halo and the galaxy two-point correlation function.