Learning the Universe: $3\ h^{-1}{\rm Gpc}$ Tests of a Field Level $N$-body Simulation Emulator

TL;DR

This paper evaluates a machine learning-based field-level emulator for non-linear cosmic structure formation at large volumes, demonstrating it can accurately replicate key statistics of N-body simulations while being significantly faster, aiding cosmological inference.

Contribution

The study extends the application of a previously developed emulator to larger volumes, showing it maintains accuracy and efficiency for next-generation survey scales.

Findings

Power spectrum, bispectrum, wavelet stats agree within 5% with N-body simulations.

Emulator replicates halo properties with similar accuracy, slight errors in particle positions.

Emulator runs a thousand times faster than traditional N-body simulations at large volumes.

Abstract

We apply and test a field-level emulator for non-linear cosmic structure formation in a volume matching next-generation surveys. Inferring the cosmological parameters and initial conditions from which the particular galaxy distribution of our Universe was seeded can be achieved by comparing simulated data to observational data. Previous work has focused on building accelerated forward models that efficiently mimic these simulations. One of these accelerated forward models uses machine learning to apply a non-linear correction to the linear $z=0$ Zeldovich approximation (ZA) fields, closely matching the cosmological statistics in the $N$-body simulation. This emulator was trained and tested at $(h^{-1}{\rm Gpc})^3$ volumes, although cosmological inference requires significantly larger volumes. We test this emulator at $(3\ h^{-1}{\rm Gpc})^3$ by comparing emulator outputs to $N$-body simulations for eight unique cosmologies. We consider several summary statistics, applied to both the raw particle fields and the dark matter (DM) haloes. We find that the power spectrum, bispectrum and wavelet statistics of the raw particle fields agree with the $N$-body simulations within ${\sim} 5 \%$ at most scales. For the haloes, we find a similar agreement between the emulator and the $N$-body for power spectrum and bispectrum, though a comparison of the stacked profiles of haloes shows that the emulator has slight errors in the positions of particles in the highly non-linear interior of the halo. At these large $(3\ h^{-1}{\rm Gpc})^3$ volumes, the emulator can create $z=0$ particle fields in a thousandth of the time required for $N$-body simulations and will be a useful tool for large-scale cosmological inference. This is a Learning the Universe publication.