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Constraints on Lorentz-invariance violation in the neutrino sector from the ultrahigh-energy event KM3-230213A

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arxiv 2502.18256 v2 pith:LGISWYJQ submitted 2025-02-25 hep-ph astro-ph.HE

classification hep-phastro-ph.HE
keywords invariancelorentzneutrinoeventkm3-230213aspeedviolationallows
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abstract

Lorentz invariance is a fundamental symmetry of spacetime and serves as the cornerstone of modern physics, supporting the constancy of the speed of light. A crucial implication of this principle is that no particle can propagate faster than this universal speed limit. In this study, we present a stringent neutrino-based test of Lorentz invariance, utilizing the highest-energy neutrino ever detected, known as event KM3-230213A. The detection of this neutrino, with measured energy of approximately 220 PeV, allows us to establish a lower bound on the scale of second-order Lorentz invariance violation, quantified as \(\Lambda_2>5.0\times 10^{19}\) GeV at 90 \% confidence level.

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Cited by 3 Pith papers

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

  1. Earth rotation turns event timing into a geometric probe of UHE neutrino origin

    hep-ph 2026-07 conditional novelty 6.0 of 10

    Earth-rotation timing lowers the number of future KM3NeT events needed to exclude a dark-matter origin of KM3-230213A from ~22–27 to ~14–16.

  2. `Dark' Matter Effect as a Novel Solution to the KM3-230213A Puzzle

    hep-ph 2025-05 conditional novelty 6.0 of 10

    Dark matter scattering in the Earth, sourced by a flaring blazar, can explain the KM3-230213A event while yielding few or no IceCube events in a viable parameter space.

  3. Interpreting the KM3-230213A PeV Neutrino Event via Vector Dark Matter Decay and Its Multi-Messenger Signatures

    hep-ph 2025-07 conditional novelty 4.0 of 10

    A U(1)_X vector dark matter model explains the KM3-230213A PeV neutrino via DM decay and predicts a cosmic string gravitational wave background consistent with PTA observations, but with several parameters fitted to the data.

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