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The Bayes factor surface for searches for new physics

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arxiv 2401.11710 v2 pith:464QGWJR submitted 2024-01-22 hep-ph astro-ph.COhep-exphysics.data-an

classification hep-phastro-ph.COhep-exphysics.data-an
keywords bayesfactorphysicssearchessurfaceevidenceparametersphenomenological
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The Bayes factor surface is a new way to present results from experimental searches for new physics. Searches are regularly expressed in terms of phenomenological parameters - such as the mass and cross-section of a weakly interacting massive particle. Bayes factor surfaces indicate the strength of evidence for or against models relative to the background only model in terms of the phenomenological parameters that they predict. They provide a clear and direct measure of evidence, may be easily reinterpreted, but do not depend on choices of prior or parameterization. We demonstrate the Bayes factor surface with examples from dark matter, cosmology, and collider physics.

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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. Deciphering compressed electroweakino excesses with MadAnalysis 5

    hep-ph 2025-07 conditional novelty 6.0 of 10

    MadAnalysis 5 v1.11 adds validated recasting of two ATLAS compressed-electroweakino searches and shows that a proposed NMSSM scenario fits the soft-lepton and monojet excesses less well than simpler models.

  2. A joint explanation for the soft lepton and monojet LHC excesses in the wino-bino model

    hep-ph 2025-06 conditional novelty 6.0 of 10

    A combined fit to four LHC Run 2 searches prefers a wino-bino supersymmetric spectrum with m(wino) ~ 320 GeV and mass splitting ~ 20 GeV, compatible with bino dark matter.

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