Estimating amplitude of matter density fluctuations in solar and supernova models using neutrino flavor evolution

Neutrinos can undergo substantial flavor evolution between their production in astrophysical sources-such as the Sun and core-collapse supernovae-and their subsequent detection in terrestrial detectors. This flavor evolution is strongly influenced by the environment that the neutrinos interact with, making them useful astrophysical messengers capable of potentially carrying information about the properties of the source wherein they are produced. In this work, we apply the framework of statistical data assimilation (SDA) in order to ascertain the extent to which a neutrino signal at detection may contain information about matter density fluctuations along their path from the source. Using simplified models of neutrino flavor evolution and propagation in the sun and in a core-collapse supernova (CCSN), we find that the SDA method is able to extract information about the amplitude of density fluctuations in both the solar and CCSN scenarios, with the method showing relatively greater reliability in the solar neutrino case. Nonetheless, even in the CCSN neutrino model, the method proved effective at high fluctuation amplitudes