Abundance and phase-space distribution of subhalos in cosmological N-body simulations: testing numerical convergence and correction methods

Abstract

Subhalos play a crucial role in accurately modeling galaxy formation and galaxy-based cosmological probes within the highly nonlinear, virialized regime. However, numerical convergence of subhalo evolution is difficult to achieve, especially in the inner regions of host halos where tidal forces are strongest. I investigate the numerical convergence and correction methods for the abundance, spatial, and velocity distributions of subhalos using two 61443-particle cosmological N-body simulations with different mass resolutions -- Jiutian-300 (1.0 × 107\,h-1M) and Jiutian-1G (3.7 × 108\,h-1M) -- with subhalos identified by HBT+. My study shows that the Surviving subhalo Peak Mass Function (SPMF) converges only for subhalos with mpeak above 5000 particles but can be accurately recovered by including orphan subhalos that survive according to the merger timescale model of Jiang et al., which outperforms other models. Including orphan subhalos also enables recovery of the real-space spatial and velocity distributions to 5--10\% accuracy down to scales of 0.1--0.2\,h-1Mpc. The remaining differences are likely due to cosmic variance and finite-box effects in the smaller Jiutian-300 simulation. Convergence below 0.1\,h-1Mpc remains challenging and requires more sophisticated modeling of orphan subhalos. I further highlight that redshift-space multipoles are more difficult to recover even at larger scales because unreliable small-scale pairs at rp < 0.1\,h-1Mpc in real space affect scales of tens of Mpc in redshift space due to elongated Fingers-of-God effects. Therefore, for redshift-space statistics, I recommend using modified or alternative measures that reduce sensitivity to small projected separations in subhalo-based studies.

0

Turn this paper into a full lesson

ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.

Discussion (0)

Sign in to join the discussion.

Loading comments…