Numerical convergence of pre-initial conditions on dark matter halo properties
Tianchi Zhang, Shihong Liao, Ming Li, Jiajun Zhang

TL;DR
This study examines how different initial particle arrangements in cosmological simulations affect dark matter halo properties, finding that convergence is generally good but varies with halo merging history and environment, and introducing CCVT as a viable initial load.
Contribution
It is the first to quantify the convergence of CCVT initial loads with other isotropic loads like glass in dark matter halo simulations.
Findings
Median halo properties agree within a few percent across different initial loads.
Poorly converged haloes are often merging or recently merged, with out-of-sync processes.
CCVT loads perform comparably to grid and glass loads in convergence tests.
Abstract
Generating pre-initial conditions (or particle loads) is the very first step to set up a cosmological N-body simulation. In this work, we revisit the numerical convergence of pre-initial conditions on dark matter halo properties using a set of simulations which only differs in initial particle loads, i.e. grid, glass, and the newly introduced capacity constrained Voronoi tessellation (CCVT). We find that the median halo properties agree fairly well (i.e. within a convergence level of a few per cent) among simulations running from different initial loads. We also notice that for some individual haloes cross-matched among different simulations, the relative difference of their properties sometimes can be several tens of per cent. By looking at the evolution history of these poorly converged haloes, we find that they are usually merging haloes or haloes have experienced recent merger…
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