Generating Dark Matter Halo Merger Trees

TL;DR

This paper introduces a new Monte-Carlo algorithm for generating dark matter halo merger trees, aligned with Millennium Simulation data, enhancing semi-analytic galaxy formation models.

Contribution

A modified Monte-Carlo algorithm based on Extended Press-Schechter theory, accurately reproducing Millennium Simulation merger statistics for hierarchical structure formation.

Findings

Algorithm agrees well with Millennium Simulation data

Provides a useful tool for galaxy formation modeling

Applicable to various cosmological models

Abstract

We present a new Monte-Carlo algorithm to generate merger trees describing the formation history of dark matter halos. The algorithm is a modification of the algorithm of Cole et al (2000) used in the GALFORM semi-analytic galaxy formation model. As such, it is based on the Extended Press-Schechter theory and so should be applicable to hierarchical models with a wide range of power spectra and cosmological models. It is tuned to be in accurate agreement with the conditional mass functions found in the analysis of merger trees extracted from the LCDM Millennium N-body simulation. We present a comparison of its predictions not only with these conditional mass functions, but also with additional statistics of the Millennium Simulation halo merger histories. In all cases we find it to be in good agreement with the Millennium Simulation and thus it should prove to be a very useful tool for semi-analytic models of galaxy formation and for modelling hierarchical structure formation in general. We have made our merger tree generation code and code to navigate the trees available at http://star-www.dur.ac.uk/~cole/merger_trees .