Prospects for distinguishing supernova models using a future neutrino signal
The next Galactic core-collapse supernova (SN) should yield a large number of observed neutrinos. Here, using Bayesian techniques, we show that with a 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 a 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 a SN at an unknown distance up to $\mathrm{\sim 10 kpc.}$