Exploring Supernova Dynamics and Neutrino Properties via Comprehensive Spectral Analysis

Core-collapse supernovae release nearly all their energy as neutrinos, offering a unique view into supernova dynamics and proto-neutron star properties. We develop a pipeline to reconstruct neutrino spectra detected at Earth-based observatories, utilizing advanced machine learning techniques, which prove advantageous over traditional matrix inversion methods. This approach reveals essential features of supernova dynamics, enhancing our understanding of these powerful events and informing future studies in experimental neutrino physics.