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Self-interacting neutrinos: solution to Hubble tension versus experimental constraints

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arxiv 2004.10868 v1 pith:L4MQVMPM submitted 2020-04-22 hep-ph astro-ph.CO

classification hep-phastro-ph.CO
keywords neutrinossolutionconstrainedpotentialproblemscenarioself-interactionsstandard-model
verification ladder T0 review T1 audit T2 compute T3 formal
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Exotic self-interactions among the Standard-Model neutrinos have been proposed as a potential reason behind the tension in the expansion rate, H0, of the universe inferred from different observations. We constrain this proposal using electroweak precision observables, rare meson decays, and neutrinoless double-\{beta} decay. In contrast to previous works, we emphasize the importance of carrying out this study in a framework with full Standard-Model gauge invariance. We implement this first by working with a relevant set of Standard- Model-Effective-Field-Theory operators and subsequently by considering a UV completion in the inverse See-Saw model. We find that the scenario in which all flavors of neutrinos self-interact universally is strongly constrained, disfavoring a potential solution to the H0 problem in this case. The scenario with self-interactions only among tau neutrinos is the least constrained and can potentially be consistent with a solution to the H0 problem.

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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. New Constraints on Neutrino-Dark Matter Interactions: A Comprehensive Analysis

    hep-ph 2025-07 conditional novelty 6.0 of 10

    Most benchmark neutrino-dark matter couplings adopted in previous studies are excluded when laboratory meson and Z decay bounds are combined with cosmological and astrophysical constraints, leaving only special galact...

  2. Hubble tension in k-essence: Evidence for robust tension alleviation

    astro-ph.CO 2026-07 conditional novelty 5.0 of 10

    Dilaton and tachyon k-essence models robustly reduce Planck–late-Universe H0 tension to 0.14σ and 0.69σ without dataset-dependent fine-tuning of model parameters.

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