Diffuse Supernova Neutrino Background and Neutrino Non-Radiative Decay: a Bayesian Perspective
Noah Roux, M. Cristina Volpe

TL;DR
This paper uses Bayesian analysis to evaluate how well upcoming neutrino detectors can distinguish between standard supernova neutrino fluxes and those affected by non-radiative neutrino decay, considering various decay scenarios and uncertainties.
Contribution
It extends previous work by performing the first Bayesian analysis to disentangle neutrino decay effects in the diffuse supernova neutrino background across multiple experiments and decay patterns.
Findings
Bayesian methods can differentiate decay scenarios with current detector sensitivities.
Predicted neutrino fluxes vary significantly with decay patterns and mass orderings.
Uncertainties in supernova rates and failed supernova fractions impact detection prospects.
Abstract
Neutrinos being massive could undergo non-radiative decay, a property for which the diffuse supernova neutrino background has a unique sensitivity. We extend previous analyses to explore our ability to disentangle predictions for the diffuse supernova neutrino background in presence or absence of neutrino non-radiative two-body decay. In a three-neutrino framework, we give predictions of the corresponding neutrino fluxes and the expected number of events in the Super-Kamiokande+Gadolinium, the Hyper-Kamiokande, the JUNO and the DUNE experiments. In our analysis, we employ supernova simulations from different groups and include current uncertainties from both the evolving core-collapse supernova rate and the fraction of failed supernovae. We perform the first Bayesian analysis to see our ability to disentangle the cases in presence and absence of neutrino decay. To this aim we combine…
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Taxonomy
TopicsNeutrino Physics Research · Particle physics theoretical and experimental studies · Astrophysics and Cosmic Phenomena
