Distinguishing between $\Lambda$CDM and $f(R)$ gravity models using halo ellipticity correlations in simulations

TL;DR

This study demonstrates that intrinsic alignment statistics of dark matter halos can effectively distinguish between $ ext{Λ}$CDM and $f(R)$ gravity models, offering a new tool for testing gravity theories with large-scale structure data.

Contribution

First measurement of intrinsic alignment in $f(R)$ gravity simulations showing distinguishable features from $ ext{Λ}$CDM, enhancing gravity model discrimination.

Findings

IA statistics differ between $f(R)$ and $ ext{Λ}$CDM models.

IA correlations improve detection of $f(R)$ effects by ~40%.

Halo shape-orientation correlation is stronger in $f(R)$ gravity.

Abstract

There is a growing interest in utilizing intrinsic alignment (IA) of galaxy shapes as a geometric and dynamical probe of cosmology. In this paper we present the first measurements of IA in a modified gravity model using the gravitational shear-intrinsic ellipticity correlation (GI) and intrinsic ellipticity-ellipticity correlation (II) functions of dark-matter halos from $f(R)$ gravity simulations. By comparing them with the same statistics measured in $\Lambda$CDM simulations, we find that the IA statistics in different gravity models show distinguishable features, with a trend similar to the case of conventional galaxy clustering statistics. Thus, the GI and II correlations are found to be useful in distinguishing between the $\Lambda$CDM and $f(R)$ gravity models. More quantitatively, IA statistics enhance detectability of the imprint of $f(R)$ gravity on large scale structures by $\sim 40\%$ when combined with the conventional halo clustering in redshift space. We also find that the correlation between the axis ratio and orientation of halos becomes stronger in $f(R)$ gravity than that in $\Lambda$CDM. Our results demonstrate the usefulness of IA statistics as a probe of gravity beyond a consistency test of $\Lambda$CDM and general relativity.