Physical review. D/Physical review. D. · 2019 · 110 citations · 26 references
Natural SciencesPhysicsNuclear PhysicsParticle PhysicsRadiation DetectionAlpha DecayBeta DecayNeutrino PhysicsNuclear DecayParticle DetectorsRadioactive DecayHadron Decay ModesKaon PhysicsLimitsNeutrino Mixing ParametersNuclear Decay ModesTime Projection ChambersUpper Bounds
This paper reports on the search for heavy neutrinos with masses in the range $140<{M}_{N}<493\text{ }\text{ }\mathrm{MeV}/{\mathrm{c}}^{2}$ using the off-axis near detector ND280 of the T2K experiment. These particles can be produced from kaon decays in the standard neutrino beam and then subsequently decay in ND280. The decay modes under consideration are $N\ensuremath{\rightarrow}{\ensuremath{\ell}}_{\ensuremath{\alpha}}^{\ifmmode\pm\else\textpm\fi{}}{\ensuremath{\pi}}^{\ensuremath{\mp}}$ and $N\ensuremath{\rightarrow}{\ensuremath{\ell}}_{\ensuremath{\alpha}}^{+}{\ensuremath{\ell}}_{\ensuremath{\beta}}^{\ensuremath{-}}\stackrel{(\ensuremath{-})}{\ensuremath{\nu}}(\ensuremath{\alpha},\ensuremath{\beta}=e,\ensuremath{\mu})$. A search for such events has been made using the Time Projection Chambers of ND280, where the background has been reduced to less than two events in the current dataset in all channels. No excess has been observed in the signal region. A combined Bayesian statistical approach has been applied to extract upper limits on the mixing elements of heavy neutrinos to electron-, muon- and tau- flavored currents (${U}_{e}^{2}$, ${U}_{\ensuremath{\mu}}^{2}$, ${U}_{\ensuremath{\tau}}^{2}$) as a function of the heavy neutrino mass, e.g., ${U}_{e}^{2}<{10}^{\ensuremath{-}9}$ at 90% C.L. for a mass of $390\text{ }\text{ }\mathrm{MeV}/{\mathrm{c}}^{2}$. These constraints are competitive with previous experiments.
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The νMSM, dark matter and baryon asymmetry of the universe
T. Asaka, Mikhail Shaposhnikov · Physics Letters B · 2005 · 1K citations · Full text
The νMSM, dark matter and neutrino masses
T. Asaka, Steve Blanchet, Mikhail Shaposhnikov · Physics Letters B · 2005 · 861 citations · Full text
Natural Sciences, Physics, Cosmology +15
PyMC: Bayesian Stochastic Modelling in Python.
Anand P. Patil, David Huard, Christopher Fonnesbeck · PubMed · 2010 · 557 citations · Full text