Galaxy clustering in modified gravity from full-physics simulations. I: two-point correlation functions

TL;DR

This paper uses advanced galaxy-formation simulations in modified gravity to study galaxy clustering, revealing complex effects of the fifth force on observable signals and emphasizing the importance of hydrodynamical modeling for future surveys.

Contribution

It provides the first detailed analysis of galaxy clustering in $f(R)$ gravity using full-physics simulations, highlighting non-monotonic effects and environment dependence on galaxy formation.

Findings

Clustering signals do not depend monotonically on fifth-force strength.

Weaker $f(R)$ models can mimic stronger ones in galaxy clustering at lower redshifts.

Galaxy formation in $f(R)$ gravity shows significant environment dependence.

Abstract

We present an in-depth investigation of galaxy clustering based on a new suite of realistic large-box galaxy-formation simulations in $f(R)$ gravity, with a subgrid physics model that has been recalibrated to reproduce various observed stellar and gas properties. We focus on the two-point correlation functions of the luminous red galaxies (LRGs) and emission line galaxies (ELGs), which are primary targets of ongoing and future galaxy surveys such as DESI. One surprising result is that, due to several nontrivial effects of modified gravity on matter clustering and the galaxy-halo connection, the clustering signal does not depend monotonically on the fifth-force strength. For LRGs this complicated behaviour poses a challenge to meaningfully constraining this model. For ELGs, in contrast, this can be straightforwardly explained by the time evolution of the fifth force, which means that weaker $f(R)$ models can display nearly the same -- up to $25\%$ -- deviations from $\Lambda$CDM as the strongest ones, albeit at lower redshifts. This implies that even very weak $f(R)$ models can be strongly constrained, unlike with most other observations. Our results show that galaxy formation acquires a significant environment dependence in $f(R)$ gravity which, if not properly accounted for, may lead to biased constraints on the model. This highlights the essential role of hydrodynamical simulations in future tests of gravity exploring precision galaxy-clustering data from the likes of DESI and Euclid.