Dark matter halo occupation: environment and clustering

TL;DR

This study uses a large dark matter simulation to explore how the number of substructures within halos influences their clustering and environment at redshift z=1, revealing significant dependencies and correlations.

Contribution

It demonstrates the environmental and occupation dependence of halo clustering, highlighting the strong bias related to substructure count at fixed mass.

Findings

Halos with more substructure are more clustered.

Halo bias strongly depends on substructure occupation at fixed mass.

Bias varies with halo mass when occupation is fixed.

Abstract

We use a large dark matter simulation of a LambdaCDM model to investigate the clustering and environmental dependence of the number of substructures in a halo. Focusing on redshift z=1, we find that the halo occupation distribution is sensitive at the tens of percent level to the surrounding density and to a lesser extent to asymmetry of the surrounding density distribution. We compute the autocorrelation function of halos as a function of occupation, building on the finding of Wechsler et al. (2006) and Gao and White (2007) that halos (at fixed mass) with more substructure are more clustered. We compute the relative bias as a function of occupation number at fixed mass, finding a strong relationship. At fixed mass, halos in the top 5% of occupation can have an autocorrelation function ~ 1.5-2 times higher than the mean. We also compute the bias as a function of halo mass, for fixed halo occupation. We find that for group and cluster sized halos, when the number of subhalos is held fixed, there is a strong anticorrelation between bias and halo mass. Such a relationship represents an additional challenge to the halo model.