Simulations and symmetries

TL;DR

This paper presents a hybrid model combining N-body simulations and symmetry-based bias expansion to improve the accuracy of real-space power spectrum predictions for large-scale structure, especially at low redshifts and for moderately biased tracers.

Contribution

It introduces a hybrid approach that leverages N-body dynamics and symmetry principles, enhancing modeling accuracy without relying on halo identification or galaxy formation parameters.

Findings

N-body-based dynamics outperform perturbation theory by over a factor of two in scale at low redshifts.

The hybrid model simplifies emulation by removing the need for halo and galaxy-formation parameters.

Performance gains are more modest at high redshifts and for highly biased tracers.

Abstract

We investigate the range of applicability of a model for the real-space power spectrum based on N-body dynamics and a (quadratic) Lagrangian bias expansion. This combination uses the highly accurate particle displacements that can be efficiently achieved by modern N-body methods with a symmetries-based bias expansion which describes the clustering of any tracer on large scales. We show that at low redshifts, and for moderately biased tracers, the substitution of N-body-determined dynamics improves over an equivalent model using perturbation theory by more than a factor of two in scale, while at high redshifts and for highly biased tracers the gains are more modest. This hybrid approach lends itself well to emulation. By removing the need to identify halos and subhalos, and by not requiring any galaxy-formation-related parameters to be included, the emulation task is significantly simplified at the cost of modeling a more limited range in scale.