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Prospects for Distinguishing Supernova Models Using a Future Neutrino Signal

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arxiv 2202.09975 v1 pith:YXZGN6CM submitted 2022-02-21 astro-ph.HE hep-phnucl-th

classification astro-ph.HEhep-phnucl-th
keywords modelsneutrinodistancedetectordistinguishdistributionsknownsupernova
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abstract

The next Galactic core-collapse supernova (SN) should yield a large number of observed neutrinos. Using Bayesian techniques, we show that with an SN at a known distance up to 25 kpc, the neutrino events in a water Cherenkov detector similar to Super-Kamiokande (SK) could be used to distinguish between seven one-dimensional neutrino emission models assuming no flavor oscillations or the standard Mikheyev-Smirnov-Wolfenstein effect. Some of these models could still be differentiated with an SN at a known distance of 50 kpc. We also consider just the relative distributions of neutrino energy and arrival time predicted by the models and find that a detector like SK meets the requirement to distinguish between these distributions with an SN at an unknown distance up to $\sim 10$ kpc.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. What shall we learn from a future supernova?

    astro-ph.SR 2024-12 unverdicted novelty 1.0 of 10

    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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