Making use of sub-resolution halos in N-body simulations

TL;DR

This paper introduces a simple weighting scheme that leverages sub-resolution halos in N-body simulations, significantly extending the effective resolution and improving clustering predictions at lower computational costs.

Contribution

The authors propose a novel method to utilize sub-resolution halos in N-body simulations, enhancing the effective resolution and accuracy of clustering measurements.

Findings

The scheme reproduces clustering within 5% for halos with 11 particles.

It extends useful halo resolution by a factor of ten.

Performance slightly decreases at higher redshift.

Abstract

Conservative mass limits are often imposed on the dark matter halo catalogues extracted from N-body simulations. By comparing simulations with different mass resolutions, at $z=0$ we find that even for halos resolved by 100 particles, the lower resolution simulation predicts a cumulative halo abundance that is 5 per cent lower than in the higher resolution simulation. We propose a simple weighting scheme to utilise the halos that are usually regarded as being `sub-resolution'. With the scheme, we are able to use halos which contain only 11 particles to reproduce the clustering measured in the higher resolution simulation to within 5 per cent on scales down to $2 h^{-1}$ Mpc, thereby extending the useful halo resolution by a factor of ten below the mass at which the mass functions in the two simulations first start to deviate. The performance of the method is slightly worse at higher redshift. Our method allows a simulation to be used to probe a wider parameter space in clustering studies, for example, in a halo occupation distribution analysis. This reduces the cost of generating many simulations to estimate the covariance matrix on measurements or using a larger volume simulation to make large-scale clustering predictions.