Event triggering and deep learning for particle identification in KM3NeT ...

• Main Author: De Sio, Chiara
• Format: Article in Journal/Newspaper
• Language: English
• Published: Universita' degli studi di Salerno 2018
• Subjects: KM3Net; Deep learning; FIS/04 FISICA NUCLEARE E SUBNUCLEARE; Orca
• Online Access: https://dx.doi.org/10.14273/unisa-1369; http://elea.unisa.it/xmlui/handle/10556/3085

2016 - 2017 ... : Neutrino astronomy experiments like KM3NeT allow to survey the Universe leveraging the properties of neutrinos of being electrically neutral and weakly interacting particles, making them a suitable messenger. Observing neutrino emission in association with electromagnetic radiation allows evaluating models for the acceleration of particles occurring in high energy sources such as Supernovae or Active Galactic Nuclei. This is the main goal of the ARCA project in KM3NeT. In addition, KM3NeT has a program for lower energy neutrinos called ORCA, aimed at distinguishing between the scenarios of “normal hierarchy” and “inverted hierarchy” for neutrino mass eigenstates. The KM3NeT Collaboration is currently building a network of three Cherenkov telescopes in the Mediterranean sea, in deep water off the coasts of Capopassero, Italy; Toulon, France, and Pylos, Greece. The water overburden shields the detectors from down-going charged particles produced by the interactions of cosmic rays in the atmosphere, while ...