The Most Bound Halo Particle-Galaxy Correspondence Model: Comparison between Models with Different Merger Timescales

TL;DR

This paper introduces a galaxy assignment scheme based on the most bound particles in dark matter halos, comparing different merger timescale models, and demonstrates its effectiveness in reproducing observed galaxy clustering and group properties.

Contribution

It presents a novel MBP-based galaxy assignment model that outperforms previous schemes and compares various merger timescale models using large cosmological simulations.

Findings

The MBP scheme accurately reproduces SDSS galaxy populations in massive groups.

The scheme matches small-scale two-point correlation functions well.

It outperforms previous subhalo-based models by more than 2 sigma.

Abstract

We develop a galaxy assignment scheme that populates dark matter halos with galaxies by tracing the most bound member particles (MBPs) of simulated halos. Several merger-timescale models based on analytic calculations and numerical simulations are adopted as the survival time of mock satellite galaxies. We build mock galaxy samples from halo merger data of the Horizon Run 4 $N$-body simulation from $z = 12-0$. We compare group properties and two-point correlation functions (2pCFs) of mock galaxies with those of volume-limited SDSS galaxies, with $r$-band absolute magnitudes of $\mathcal{M}_r - 5 \log h < -21$ and $-20$ at $z=0$. It is found that the MBP-galaxy correspondence scheme reproduces the observed population of SDSS galaxies in massive galaxy groups ($M > 10^{14} h^{-1} M_{\odot}$) and the small-scale 2pCF ($r_{\rm p} < 10 h^{-1} {\rm Mpc}$) quite well for the majority of the merger timescale models adopted. The new scheme outperforms the previous subhalo-galaxy correspondence scheme by more than $2\sigma$.