Probing freeze-in via invisible Higgs decay

In this work, we explore Higgs boson decays into dark matter (DM) within the context of the freeze-in mechanism under stronger coupling scenarios. Our analysis focuses on scalar DM candidates interacting through the Higgs portal, where the coupling strength can be significant without establishing thermal equilibrium, owing to a suppressed reheating temperature. We find that for DM masses as low as the MeV scale, the observed relic density can be reproduced while remaining consistent with existing collider and cosmological constraints. Notably, the framework predicts invisible Higgs decays at the level of a few percent, providing exciting prospects for experimental verification at the HL-LHC and FCC.

Authors

Publication Details

Published
2025-02-12
DOI
https://doi.org/10.22323/1.474.0070
Citations
1
Primary Topic
Computational Physics and Python Applications
Type
article
Field-Weighted Citation Impact
2.48

Funders

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article

Probing freeze-in via invisible Higgs decay

Oleg Lebedev, A. Morais, Roman Pasechnik, Vinícius Oliveira
1 citations
Computational Physics and Python Applications
2.48
article

Probing freeze-in via invisible Higgs decay

Oleg Lebedev, A. Morais, Roman Pasechnik, Vinícius Oliveira
article en
1 citations

Abstract

In this work, we explore Higgs boson decays into dark matter (DM) within the context of the freeze-in mechanism under stronger coupling scenarios. Our analysis focuses on scalar DM candidates interacting through the Higgs portal, where the coupling strength can be significant without establishing thermal equilibrium, owing to a suppressed reheating temperature. We find that for DM masses as low as the MeV scale, the observed relic density can be reproduced while remaining consistent with existing collider and cosmological constraints. Notably, the framework predicts invisible Higgs decays at the level of a few percent, providing exciting prospects for experimental verification at the HL-LHC and FCC.

CERN, European Commission, Magnus Ehrnroothin Säätiö, Vetenskapsrådet, Center for Research and Development in Mathematics and Applications, Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 12%
Computational Physics and Python Applications
2.48
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