Nnaturalness generates neutrino mass matrices through multi-sector mixing, excludes democratic couplings, and yields a tower of neutrino eigenstates with theory-determined mass splittings.
µ → eγ at a Rate of One Out of 10 9 Muon Decays?,
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XGBoost machine learning improves discrimination in LHC searches for singlet vector-like leptons, yielding projected 2σ mass exclusion limits of 620 GeV (three-lepton) and 490 GeV (four-lepton) at 14 TeV with 3000 fb^{-1}.
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Neutrino Masses and Phenomenology in Nnaturalness
Nnaturalness generates neutrino mass matrices through multi-sector mixing, excludes democratic couplings, and yields a tower of neutrino eigenstates with theory-determined mass splittings.
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Machine Learning Study on Single Production of a Singlet Vector-like Lepton at the Large Hadron Collider
XGBoost machine learning improves discrimination in LHC searches for singlet vector-like leptons, yielding projected 2σ mass exclusion limits of 620 GeV (three-lepton) and 490 GeV (four-lepton) at 14 TeV with 3000 fb^{-1}.