Building Halo Merger Trees from the Q Continuum Simulation

TL;DR

This paper introduces fast parallel algorithms for constructing halo merger trees and tracking substructures from large cosmological N-body simulations, enabling detailed analysis of galaxy formation histories.

Contribution

The authors develop and implement efficient MPI-based algorithms to generate halo merger trees and substructure tracking from large simulation datasets, improving analysis speed and scalability.

Findings

Algorithms successfully processed data from the Q Continuum simulation

Achieved scalable performance on up to 16,384 processes

Produced detailed merger trees and substructure information

Abstract

Cosmological N-body simulations rank among the most computationally intensive efforts today. A key challenge is the analysis of structure, substructure, and the merger history for many billions of compact particle clusters, called halos. Effectively representing the merging history of halos is essential for many galaxy formation models used to generate synthetic sky catalogs, an important application of modern cosmological simulations. Generating realistic mock catalogs requires computing the halo formation history from simulations with large volumes and billions of halos over many time steps, taking hundreds of terabytes of analysis data. We present fast parallel algorithms for producing halo merger trees and tracking halo substructure from a single-level, density-based clustering algorithm. Merger trees are created from analyzing the halo-particle membership function in adjacent snapshots, and substructure is identified by tracking the "cores" of merging halos -- sets of particles near the halo center. Core tracking is performed after creating merger trees and uses the relationships found during tree construction to associate substructures with hosts. The algorithms are implemented with MPI and evaluated on a Cray XK7 supercomputer using up to 16,384 processes on data from HACC, a modern cosmological simulation framework. We present results for creating merger trees from 101 analysis snapshots taken from the Q Continuum, a large volume, high mass resolution, cosmological simulation evolving half a trillion particles.