Dissecting the Evolution of Dark Matter Subhaloes in the Bolshoi Simulation

TL;DR

This paper thoroughly analyzes the evolution of dark matter subhaloes in the Bolshoi simulation, revealing complex dynamics, frequent interactions, and significant numerical over-merging issues affecting subhalo demographics.

Contribution

It introduces a detailed classification of 12 subhalo evolution channels and quantifies the impact of numerical effects on subhalo disruption.

Findings

Subhaloes experience frequent penetrating encounters (~1 per dynamical time).

Approximately 80% of subhalo disruption is due to numerical over-merging.

Three main disruption channels identified: mass loss below resolution, mergers, and disintegration.

Abstract

We present a comprehensive analysis of the evolution of dark matter subhaloes in the cosmological Bolshoi simulation. We identify a complete set of 12 unique evolution channels by which subhaloes evolve in between simulation outputs, and study their relative importance and demographics. We show that instantaneous masses and maximum circular velocities of individual subhaloes are extremely noisy, despite the use of a sophisticated, phase-space-based halo finder. We also show that subhaloes experience frequent penetrating encounters with other subhaloes (on average about one per dynamical time), and that subhaloes whose apo-center lies outside the virial radius of their host (the 'ejected' or 'backsplash' haloes) experience tidal forces that modify their orbits. This results in an average fractional subhalo exchange rate among host haloes of roughly 0.01 per Gyr (at the present time). In addition, we show that there are three distinct disruption channels; one in which subhaloes drop below the mass resolution limit of the simulation, one in which subhaloes merge with their host halo largely driven by dynamical friction, and one in which subhaloes abruptly disintegrate. We estimate that roughly 80 percent of all subhalo disruption in the Bolshoi simulation is numerical, rather than physical. This over-merging is a serious road-block for the use of numerical simulations to interpret small scale clustering, or for any other study that is sensitive to the detailed demographics of dark matter substructure.