Cosmic relic abundance and f(R) gravity

TL;DR

This paper explores how $f(R)$ gravity models can explain the PAMELA positron excess by affecting dark matter relic abundance, suggesting certain $f(R)$ models are compatible with experimental data and cosmological constraints.

Contribution

It demonstrates that specific $f(R)$ gravity models can account for PAMELA data by modifying the early universe's expansion rate, expanding the range of viable dark matter scenarios.

Findings

$f(R)$ models can explain PAMELA positron excess.

For $f(R)=R+ ext{constant}$, the model aligns with data for dark matter masses below 100 GeV.

Relaxing BBN constraints allows broader $f(R)$ models to fit the data.

Abstract

The cosmological consequences of $f(R)$ gravity are reviewed in the framework of recent data obtained by PAMELA (Payload for Antimatter Matter Exploration and Light-nuclei Astrophysics) experiment. This collaboration has reported an excess of positron events that cannot be explained by conventional cosmology and particle physics, and are usually ascribed to the dark matter presence (in particular, weak interacting massive particles). The dark matter interpretation of PAMELA data has motivated the study of alternative cosmological models (with respect to the standard cosmology) owing to the fact that they predict an enhancement of the Hubble expansion rate, giving rise, in such a way, to thermal relics with a larger relic abundance. Our analysis shows that $f(R)$ cosmology allows to explain the PAMELA puzzle for dark matter relic particles with masses of the order or lesser than $10^2$ GeV in the regime $\rho^c \lesssim \rho^m $ where $\rho^c$ is the curvature density and $\rho^m$ the radiation density. For the model $f(R)=R+\alpha R^n$, it then follows that $n\simeq 1$ and small corrections with respect to General Relativity could lead indeed to address the experimental results. However other interesting cosmological models can be considered during the pre-BBN epoch as soon as the BBN constraints are relaxed. In such a case, the PAMELA data can be fitted for a larger class of $f(R)$-models.