Constructing high-fidelity halo merger trees in AbacusSummit

Understand

Tracking the formation and evolution of dark matter haloes is a critical aspect of any analysis of cosmological $N$-body simulations.

• In particular, the mass assembly of a halo and its progenitors, encapsulated in the form of its merger tree, serves as a fundamental input for constructing semi-analytic models of galaxy formation and, more generally, for building mock catalogues that emulate galaxy surveys.
• We present an algorithm for constructing halo merger trees from AbacusSummit, the largest suite of cosmological $N$-body simulations performed to date consisting of nearly 60 trillion particles, and which has been designed to meet the Cosmological Simulation Requirements of the Dark Energy Spectroscopic Instrument (DESI) survey.
• Our method tracks the cores of haloes to determine associations between objects across multiple timeslices, yielding lists of halo progenitors and descendants for the several tens of billions of haloes identified across the entire suite.