Tau neutrino appearance measurement in KM3NeT/ORCA 6

• Published in: Proceedings of XVIII International Conference on Topics in Astroparticle and Underground Physics — PoS(TAUP2023)
• Main Author: Lastoria, Chiara Filomena
• Other Authors: Centre de Physique des Particules de Marseille (CPPM), Aix Marseille Université (AMU)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), KM3NeT
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2023
• Subjects: neutrino: detector; neutrino: oscillation; detector: geometry; KM3NeT; topology; neutrino: mass; statistics; [PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]; [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]; Orca
• Online Access: https://hal.science/hal-04487758; https://doi.org/10.22323/1.441.0192

International audience KM3NeT/ORCA is a next-generation water Cherenkov neutrino telescope currently under construction in the Mediterranean Sea. By studying the oscillations of the atmospheric neutrino flux passing through the Earth, thanks to the detector geometry and its unprecedented statistics, KM3NeT/ORCA's primary physics goal is an early measurement of the neutrino mass ordering as well as the direct observation of tau neutrino appearance; the last, allowing for a test of the standard three-neutrino flavours paradigm. Due to the detector's modular structure, neutrino oscillation analyses are already possible with a partially instrumented volume. Given that the neutrino flux composition is dominated by muon neutrinos producing a track-like topology in the detector, the tau neutrinos can be identified as an excess into the shower-like topology, and the tau appearance, quantified in terms of the neutrino tau normalization, can be performed on statistical basis. In this summary, the focus will be given to the analysis of the data collected in the KM3NeT/ORCA 6 geometry (6 Detection Units, equivalent to 5% of the final geometry); the description of a novel Random Grid Search algorithm developed to optimize the track-shower selection will be reported.