Examining scalar portal inelastic dark matter with lepton fixed target experiments
I. V. Voronchikhin, D. V. Kirpichnikov

TL;DR
This paper explores the potential of lepton fixed-target experiments to detect sub-GeV inelastic dark matter interacting through a scalar portal, providing projected sensitivities and highlighting the complementary roles of electron and muon beams.
Contribution
It introduces a detailed phenomenological analysis of inelastic dark matter with a scalar portal, including thermal target curves and experimental sensitivity projections.
Findings
Projected sensitivities for NA64e, LDMX, and NA64μ are derived.
The scalar portal interaction can be probed via missing-energy signatures.
Electron and muon experiments offer complementary detection capabilities.
Abstract
Inelastic dark matter scenarios have attracted considerable attention in contemporary particle physics. In this study, we investigate the phenomenology of sub-GeV inelastic dark matter interacting via a lepton-specific scalar portal. By solving the Boltzmann equations, we obtain thermal target curves for several inelastic DM mass splittings in the sub-GeV mediator-mass range. We study the discovery potential of lepton fixed-target experiments, particularly NA64e, LDMX, and NA64, via their missing-energy signatures. Our analysis focuses on the -strahlung process, , followed by the invisible decay of the scalar mediator into Majorana dark matter particles . We use this channel to probe the mediator coupling to charged leptons of the Standard Model. For phenomenologically viable parameters of the inelastic dark matter scenario, we derive…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsDark Matter and Cosmic Phenomena · Particle physics theoretical and experimental studies · Computational Physics and Python Applications
