Monte Carlo simulations for the ANTARES underwater neutrino telescope

Albert, A.; Andre, M.; Anghinolfi, M.; Anton, G.; Ardid, M.; Aubert, J. -J.; Aublin, J.; Baret, B.; Basa, S.; Belhorma, B.; Bertin, V.; Biagi, S.; Bissinger, M.; Boumaaza, J.; Bouta, M.; Bouwhuis, M. C.; Branzas, H.; Bruijn, R.; Brunner, J.; Busto, J.; Capone, A.; Caramete, L.; Carr, J.; Cecchini, S.; Celli, S.; Chabab, M.; Chau, T. N.; Cherkaoui El Moursli, R.; Chiarusi, T.; Circella, M.; Coleiro, A.; Colomer-Molla, M.; Coniglione, R.; Coyle, P.; Creusot, A.; Diaz, A. F.; De Wasseige, G.; Deschamps, A.; Distefano, C.; Di Palma, I.; Domi, A.; Donzaud, C.; Dornic, D.; Drouhin, D.; Eberl, T.; El Khayati, N.; Enzenhofer, A.; Ettahiri, A.; Fermani, P.; Ferrara, G.; Filippini, F.; Fusco, L.; Gay, P.; Glotin, H.; Gozzini, R.; Graf, K.; Guidi, C.; Hallmann, S.; Van Haren, H.; Heijboer, A. J.; Hello, Y.; Hernandez-Rey, J. J.; Hol, J.; Hofestadt, J.; Huang, F.; Illuminati, G.; James, C. W.; De Jong, M.; De Jong, P.; Jongen, M.; Kadler, M.; Kalekin, O.; Katz, U.; Khan-Chowdhury, N. R.; Kouchner, A.; Kreykenbohm, I.; Kulikovskiy, V.; Lahmann, R.; Le Breton, R.; Lefevre, D.; Leonora, E.; Levi, G.; Lincetto, M.; Lopez-Coto, D.; Loucatos, S.; Manczak, J.; Marcelin, M.; Margiotta, A.; Marinelli, A.; Martinez-Mora, J. A.; Mazzou, S.; Melis, K.; Migliozzi, P.; Moser, M.; Moussa, A.; Muller, R.; Nauta, L.; Navas, S.; Nezri, E.; Nunez-Castineyra, A.; O'Fearraigh, B.; Organokov, M.; Pavalas, G. E.; Pellegrino, C.; Perrin-Terrin, M.; Piattelli, P.; Poire, C.; Popa, V.; Pradier, T.; Randazzo, N.; Reck, S.; Riccobene, G.; Salesa, F.; Sanchez-Losa, A.; Samtleben, D. F. E.; Sanguineti, M.; Sapienza, P.; Schnabel, J.; Schussler, F.; Spurio, M.; Stolarczyk, Th.; Strandberg, B.; Taiuti, M.; Tayalati, Y.; Thakore, T.; Tingay, S. J.; Vallage, B.; Van Elewyck, V.; Versari, F.; Viola, S.; Vivolo, D.; Wilms, J.; Zegarelli, A.; Zornoza, J. D.; Zuniga, J.

doi:10.1088/1475-7516/2021/01/064

Monte Carlo simulations are a unique tool to check the response of a detector and to monitor its performance. For a deep-sea neutrino telescope, the variability of the environmental conditions that can affect the behaviour of the data acquisition system must be considered, in addition to a reliable description of the active parts of the detector and of the features of physics events, in order to produce a realistic set of simulated events. In this paper, the software tools used to produce neutrino and cosmic ray signatures in the telescope and the strategy developed to represent the time evolution of the natural environment and of the detector efficiency are described.