Scalar field dark matter with two components: combined approach from particle physics and cosmology

TL;DR

This paper investigates scalar field dark matter models with one or two components, analyzing their cosmological implications and constraints from particle physics, BBN, and the Hubble flow, with potential relevance for dark matter detection.

Contribution

It introduces combined scalar field models from particle physics and cosmology, analyzing their consistency with observational data and deriving parameter restrictions.

Findings

Two scalar field models show different compatibility with $N_{\mathrm{eff}}$.

Strong parameter restrictions are found for Higgs-like and classical field combinations.

Results may inform dark matter detection strategies.

Abstract

In this work we explore the possibility of incorporating particle physics motivated scalar fields to the dark matter cosmological model. In this landscape, we consider the classical complex scalar field in a certain region in the parameter space of the model that increases the number of neutrino species $N_{\mathrm{eff}}$, in order to be consistent with the observed abundance of light elements produced at Big Bang Nucleosynthesis (BBN). We perform analyses using one and two scalar fields. We examine the difference between these models and the priors considered at the edges of the cosmic ladder, this with the purpose of studying the impact of such models on the Hubble cosmic flow. In the two scalar field models we explore the possibility of combining an axion and a Higgs-like field as well as a Higgs-like field and the classical field, we show that in the first case there is no set of parameters that allows us to be consistent with $N_\mathrm{eff}$, while in the second case a strong restriction to the set of parameters is obtained. This last restriction is given in terms of a maximum bound of the fraction of Higgs-like field that can be incorporated together with the classical field. Our results could be relevant in the direct dark matter detection programs.