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Bayesian Analysis of a Future Beta Decay Experiment's Sensitivity to Neutrino Mass Scale and Ordering

2021

Bayesian modeling techniques enable sensitivity analyses that incorporate detailed expectations regarding future experiments. A model-based approach also allows one to evaluate inferences and predicted outcomes, by calibrating (or measuring) the consequences incurred when certain results are reported. We present procedures for calibrating predictions of an experiment's sensitivity to both continuous and discrete parameters. Using these procedures and a new Bayesian model of the $\beta$-decay spectrum, we assess a high-precision $\beta$-decay experiment's sensitivity to the neutrino mass scale and ordering, for one assumed design scenario. We find that such an experiment could measure the el…

Semileptonic decaydata analysis methodParticle physicsBayesian probabilityFOS: Physical sciences[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]Bayesian inferenceBayesian01 natural sciencesMeasure (mathematics)statistics: Bayesianmass: scaleHigh Energy Physics - Phenomenology (hep-ph)0103 physical sciencesCalibrationneutrino: massSensitivity (control systems)Nuclear Experiment (nucl-ex)010306 general physicsNuclear ExperimentPhysics010308 nuclear & particles physicsElectroweak InteractionProbability and statisticssemileptonic decaycalibrationsensitivityneutrino: nuclear reactorHigh Energy Physics - Phenomenologymass: calibration[PHYS.HPHE]Physics [physics]/High Energy Physics - Phenomenology [hep-ph]Physics - Data Analysis Statistics and ProbabilityspectralHigh Energy Physics::ExperimentNeutrinoData Analysis Statistics and Probability (physics.data-an)[PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an]Symmetries
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