The KM3NeT research infrastructure comprises two submarine Cherenkov neutrino telescopes at two corresponding abyssal sites in the Mediterranean Sea. KM3NeT/ARCA is being built off Portopalo di Capo Passero, Sicily, Italy, at a depth of 3500 m. While collecting data already in a partial configuration, KM3NeT/ARCA aims at a volume of 1 km3 instrumented with a three-dimensional array of thousands of optical modules, whose geometric arrangement is optimised for the measurement of high energy neutrinos (> TeV) from astrophysical sources. In this contribution, the expectations of KM3NeT/ARCA for the detection of the diffuse flux of astrophysical neutrinos are presented. The analysis is performed using Monte Carlo simulated events assuming a complete detector configuration. Machine learning techniques are used for event selection, while for statistical analysis both a Bayesian and a frequentist method are employed.
Diffuse astrophysical neutrino flux studies with the completed KM3NeT/ARCA detector
Badaracco F.;Ellajosyula V.;Malerba L.;Marconi M.;Parisi V.;Sanguineti M.;Taiuti M.;Vannoye G.;
2025-01-01
Abstract
The KM3NeT research infrastructure comprises two submarine Cherenkov neutrino telescopes at two corresponding abyssal sites in the Mediterranean Sea. KM3NeT/ARCA is being built off Portopalo di Capo Passero, Sicily, Italy, at a depth of 3500 m. While collecting data already in a partial configuration, KM3NeT/ARCA aims at a volume of 1 km3 instrumented with a three-dimensional array of thousands of optical modules, whose geometric arrangement is optimised for the measurement of high energy neutrinos (> TeV) from astrophysical sources. In this contribution, the expectations of KM3NeT/ARCA for the detection of the diffuse flux of astrophysical neutrinos are presented. The analysis is performed using Monte Carlo simulated events assuming a complete detector configuration. Machine learning techniques are used for event selection, while for statistical analysis both a Bayesian and a frequentist method are employed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



