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Correlations and Distinguishability Challenges in Supernova Models: Insights from Future Neutrino Detectors
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This paper explores core-collapse supernovae as crucial targets for neutrino telescopes, addressing uncertainties in their simulation results. We comprehensively analyze eighteen modern simulations and discriminate among supernova models using realistic detectors and interactions. A significant correlation between the total neutrino energy and cumulative counts, driven by massive lepton neutrinos and oscillations, is identified, particularly noticeable with the DUNE detector. Bayesian techniques indicate strong potential for model differentiation during a Galactic supernova event, with HK excelling in distinguishing models based on equation of state, progenitor mass, and mixing scheme.
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Cited by 2 Pith papers
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Diffuse Supernova Neutrino Background and Neutrino Non-Radiative Decay: a Bayesian Perspective
A Bayesian forecast of upcoming DSNB detectors shows neutrino decay can be distinguished from stability for quasi-degenerate or inverted mass patterns, but not for strong normal hierarchy.
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What shall we learn from a future supernova?
A review of supernova neutrino and DSNB physics, with a reproduced Bayesian figure from the author's prior work, but no new analysis.
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