Speaker
Description
Core-collapse supernovae (CCSNe) play a significant role in our understanding of the Universe's dynamics. The time profile of neutrinos emitted during these supernovae offers valuable insights into the mechanism behind collapsing stars and the behavior of particles in extremely dense environments. The detection of neutrinos from the SN1987A supernova in the Large Magellanic Cloud marked a groundbreaking milestone in neutrino astronomy. However, due to the rarity of supernovae, no other observations of supernova neutrinos have been made thus far.
To maximize the information obtained from a galactic CCSN, it is essential to combine multiple experiments in real-time and transmit the data to telescopes. One notable example is the SNEWS system, which faces the challenge of promptly locating a supernova within minutes. Several methods are employed to measure the distance to the supernova, some of which rely on model- and distance- independent based observables. These observables depend on the accuracy of CCSN simulations and the neutrino flavor conversion mechanism. As an example, beyond the Standard Model mechanisms, such as neutrino decays, can potentially influence the accuracy of distance measurements by altering the neutrino flavor conversion process.
In this study, we propose a combination of model- and distance-independent observables from different experiments sensitive to various neutrino flavors: the DUNE experiment (sensitive to electronic neutrino flavors), the DarkSide detector (sensitive to all neutrino flavors equally), and water Cherenkov detectors (sensitive to anti-electronic neutrino flavors). This approach enables the identification of deviation in the flavor composition of observed neutrinos, providing valuable information about certain neutrino properties. The results obtained from this combined analysis will be incorporated into the SNEWS system, allowing for the correction of supernova distance measurements if necessary.
