An emulator-based halo model in modified gravity -- I. The halo concentration-mass relation and density profile

TL;DR

This paper introduces emulators for key halo properties in modified gravity cosmologies, enabling accurate modeling of galaxy clustering and density profiles using simulation data for $f(R)$ and DGP models.

Contribution

It presents the first emulators for halo mass function, concentration-mass relation, and halo-matter cross-correlation in modified gravity, trained on N-body simulations with high accuracy.

Findings

Emulators achieve less than 1% accuracy on test data.

Combined with galaxy-halo models, they predict galaxy clustering accurately.

Applicable to $f(R)$ and DGP gravity models.

Abstract

In this series of papers we present an emulator-based halo model for the non-linear clustering of galaxies in modified gravity cosmologies. In the first paper, we present emulators for the following halo properties: the halo mass function, concentration-mass relation and halo-matter cross-correlation function. The emulators are trained on data extracted from the \textsc{FORGE} and \textsc{BRIDGE} suites of $N$-body simulations, respectively for two modified gravity (MG) theories: $f(R)$ gravity and the DGP model, varying three standard cosmological parameters $\Omega_{\mathrm{m0}}, H_0, \sigma_8$, and one MG parameter, either $\bar{f}_{R0}$ or $r_{\mathrm{c}}$. Our halo property emulators achieve an accuracy of $\lesssim 1\%$ on independent test data sets. We demonstrate that the emulators can be combined with a galaxy-halo connection prescription to accurately predict the galaxy-galaxy and galaxy-matter correlation functions using the halo model framework.