Speaker
Description
P-ONE is a planned cubic-kilometer-scale neutrino detector in the Pacific ocean. It will measure high-energy astrophysical neutrinos to help characterize the nature of astrophysical accelerators. Using existing deep-sea infrastructure provided by Ocean Networks Canada (ONC), P-ONE will instrument the ocean with optical modules - which host PMTs as well as readout electronics - deployed on several vertical cables of about 1km length. While the first prototype cable is currently being assembled, the detector geometry of the final instrument is not yet fixed.
In this talk, I will present the progress of optimizing the detector design using ML-based surrogate models, which replace computationally expensive MC simulations, and, by providing gradients, allow efficient computation of the Fisher Information Matrix as an optimization target.
