TY - JOUR
T1 - Particle identification in KM3NeT/ORCA
AU - KM3NeT Collaboration
AU - Cerisy, L.
AU - Lazo, A.
AU - Lastoria, C.
AU - Perrin-Terrin, M.
AU - Brunner, J.
AU - Dabhi, V.
AU - Aiello, S.
AU - Albert, A.
AU - Alves Garre, S.
AU - Aly, Z.
AU - Ambrosone, A.
AU - Ameli, F.
AU - Andre, M.
AU - Androutsou, E.
AU - Anguita, M.
AU - Aphecetche, L.
AU - Ardid, M.
AU - Ardid, S.
AU - Atmani, H.
AU - Aublin, J.
AU - Bailly-Salins, L.
AU - Bardačová, Z.
AU - Baret, B.
AU - Bariego-Quintana, A.
AU - Basegmez du Pree, S.
AU - Becherini, Y.
AU - Bendahman, M.
AU - Benfenati, F.
AU - Benhassi, M.
AU - Benoit, D. M.
AU - Berbee, E.
AU - Bertin, V.
AU - Biagi, S.
AU - Boettcher, M.
AU - Bonanno, D.
AU - Boumaaza, J.
AU - Bouta, M.
AU - Bouwhuis, M.
AU - Bozza, C.
AU - Bozza, R. M.
AU - Brânzaş, H.
AU - Bretaudeau, F.
AU - Bruijn, R.
AU - Bruno, R.
AU - Buis, E.
AU - Buompane, R.
AU - Busto, J.
AU - Caiffi, B.
AU - Calvo, D.
AU - Razzaque, S.
N1 - Publisher Copyright:
© Copyright owned by the author(s) under the terms of the Creative Commons.
PY - 2024/9/27
Y1 - 2024/9/27
N2 - One of the main goals of KM3NeT/ORCA is to measure atmospheric neutrino oscillation parameters with competitive precision. To achieve this goal, good discrimination between track-like and shower-like events is necessary, with particular focus on the measurement of the tau neutrino normalisation. The track-like signal is mainly carried by muon neutrinos from charged current interactions, while the shower-like signal comes from charged current interactions of electron and tau neutrinos, and neutral current interactions of all flavours. A Random Grid Search algorithm is optimised to separate these channels and its performance is compared with machine learning methods using boosted decision trees. This contribution will report on the technical aspects of the algorithm and the performance of the particle identification with data recorded in 2020 and 2021 using an early six-lines configuration of the ORCA detector (ORCA6).
AB - One of the main goals of KM3NeT/ORCA is to measure atmospheric neutrino oscillation parameters with competitive precision. To achieve this goal, good discrimination between track-like and shower-like events is necessary, with particular focus on the measurement of the tau neutrino normalisation. The track-like signal is mainly carried by muon neutrinos from charged current interactions, while the shower-like signal comes from charged current interactions of electron and tau neutrinos, and neutral current interactions of all flavours. A Random Grid Search algorithm is optimised to separate these channels and its performance is compared with machine learning methods using boosted decision trees. This contribution will report on the technical aspects of the algorithm and the performance of the particle identification with data recorded in 2020 and 2021 using an early six-lines configuration of the ORCA detector (ORCA6).
UR - http://www.scopus.com/inward/record.url?scp=85212265202&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85212265202
SN - 1824-8039
VL - 444
JO - Proceedings of Science
JF - Proceedings of Science
M1 - 1191
T2 - 38th International Cosmic Ray Conference, ICRC 2023
Y2 - 26 July 2023 through 3 August 2023
ER -