Observing Merger Trees in a New Light

TL;DR

This paper introduces the dendogram, a new visualization tool for merger trees from cosmological simulations, enabling detailed comparison and assessment of different halo finders and tree-building algorithms.

Contribution

The paper presents the dendogram method for visualizing merger trees, facilitating unbiased comparison of halo finders and improving merger tree quality assessment.

Findings

Dendograms effectively visualize halo assembly histories.

Comparison reveals differences between halo finders and tree builders.

Dendogram analysis led to improvements in VELOCIraptor.

Abstract

Merger trees harvested from cosmological $N$-body simulations encode the assembly histories of dark matter halos over cosmic time, and are a fundamental component of semi-analytical models (SAMs) of galaxy formation. The ability to compare the tools used to construct merger trees, namely halo finders and tree building algorithms, in an unbiased and systematic manner is critical to assess the quality of merger trees. In this paper, we present the dendogram, a novel method to visualise merger trees, which provides a comprehensive characterisation of a halo's assembly history - tracking subhalo orbits, halo merger events, and the general evolution of halo properties. We show the usefulness of the dendogram as a diagnostic tool of merger trees by comparing halo assembly histories from a single $N$-Body simulation analysed with three different halo-finders -\textsc{VELOCIraptor}, \textsc{AHF} and \textsc{Rockstar} - and their associated tree-builders. Based on our analysis of the resulting dendograms, we highlight how they have been used to motivate improvements to \textsc{VELOCIraptor}. The dendogram software is publicly available online, at: https://github.com/rhyspoulton/MergerTree-Dendograms .