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Self-Destructing Dark Matter

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arxiv 1712.00455 v1 pith:E4AOXNNF submitted 2017-12-01 hep-ph astro-ph.COhep-ex

classification hep-phastro-ph.COhep-ex
keywords darkmattermodelsdetectorsenergylargestateclass
verification ladder T0 review T1 audit T2 compute T3 formal

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We present Self-Destructing Dark Matter (SDDM), a new class of dark matter models which are detectable in large neutrino detectors. In this class of models, a component of dark matter can transition from a long-lived state to a short-lived one by scattering off of a nucleus or an electron in the Earth. The short-lived state then decays to Standard Model particles, generating a dark matter signal with a visible energy of order the dark matter mass rather than just its recoil. This leads to striking signals in large detectors with high energy thresholds. We present a few examples of models which exhibit self destruction, all inspired by bound state dynamics in the Standard Model. The models under consideration exhibit a rich phenomenology, possibly featuring events with one, two, or even three lepton pairs, each with a fixed invariant mass and a fixed energy, as well as non-trivial directional distributions. This motivates dedicated searches for dark matter in large underground detectors such as Super-K, Borexino, SNO+, and DUNE.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Dark Matter Energy Deposition and Production from the Table-Top to the Cosmos

    hep-ph 2019-07 unverdicted novelty 5.0 of 10

    The thesis presents a new 3-to-2 freezeout mechanism, bound-state effects on searches, a new axion interferometric search, reionization assessments, 21-cm constraints, and the DarkHistory code for ionization and therm...

  2. Rich Phenomenology from Simple Ingredients: A Review of Confining Dark Sectors

    hep-ph 2026-06 unverdicted novelty 2.0 of 10

    Review of confining dark sectors summarizing dark matter candidates, abundance mechanisms, discovery channels, and applications to the abundance similarity puzzle.

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