Speaker
Qi Gao
Description
Extraterrestrial high-energy neutrinos serve as unique probes for unveiling extreme astrophysical processes and tracing the origins of cosmic rays, but their detection is highly challenging. This study simulates the lateral distribution characteristics of secondary particles，including in extensive air showers induced by protons and neutrinos within the energy range of 100 TeV to 100 PeV and the zenith angle range of 60°–89°. Machine learning is employed for multi-parameter cosmic rays/neutrino discrimination, providing a basis for neutrino event selection with ground-based cosmic rays experiments，like LHAASO-KM2A.
