# Growth index of matter perturbations in the light of Dark Energy Survey

## TL;DR

This study constrains the growth index of matter perturbations using Dark Energy Survey data, finding results consistent with but slightly deviating from General Relativity, and explores the evolution of this index with redshift.

## Contribution

It provides tight constraints on the growth index using DES bias measurements and growth data, and investigates its possible evolution with redshift.

## Key findings

- Best-fit growth index around 0.64-0.69 with ~10% accuracy.
- Small deviation from General Relativity at 1.3-2 sigma confidence level.
- Estimated dark matter halo mass range for LRGs.

## Abstract

We study how the cosmological constraints from growth data are improved by including the measurements of bias from Dark Energy Survey (DES). In particular, we utilize the biasing properties of the DES Luminous Red Galaxies (LRGs) and the growth data provided by the various galaxy surveys in order to constrain the growth index ($\gamma$) of the linear matter perturbations. Considering a constant growth index we can put tight constraints, up to $\sim 10\%$ accuracy, on $\gamma$. Specifically, using the priors of the Dark Energy Survey and implementing a joint likelihood procedure between theoretical expectations and data we find that the best fit value is in between $\gamma=0.64\pm 0.075$ and $0.65\pm 0.063$. On the other hand utilizing the Planck priors we obtain $\gamma=0.680\pm 0.089$ and $0.690\pm 0.071$. This shows a small but non-zero deviation from General Relativity ($\gamma_{\rm GR}\approx 6/11$), nevertheless the confidence level is in the range $\sim 1.3-2\sigma$. Moreover, we find that the estimated mass of the dark-matter halo in which LRGs survive lies in the interval $\sim 6.2 \times 10^{12} h^{-1} M_{\odot}$ and $1.2 \times 10^{13} h^{-1} M_{\odot}$, for the different bias models. Finally, allowing $\gamma$ to evolve with redshift [Taylor expansion: $\gamma(z)=\gamma_{0}+\gamma_{1}z/(1+z)$] we find that the $(\gamma_{0},\gamma_{1})$ parameter solution space accommodates the GR prediction at $\sim 1.7-2.9\sigma$ levels.