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  • A fast algorithm for muon t...
    Aguilar, J.A.; Al Samarai, I.; Albert, A.; Anghinolfi, M.; Anton, G.; Anvar, S.; Assis Jesus, A.C.; Astraatmadja, T.; Aubert, J.-J.; Baret, B.; Basa, S.; Bazzotti, M.; Bertin, V.; Biagi, S.; Bogazzi, C.; Brown, A.M.; Brunner, J.; Busto, J.; Camarena, F.; Carr, J.; Circella, M.; Coniglione, R.; Curtil, C.; Deschamps, A.; Distefano, C.; Donzaud, C.; Dornic, D.; Dorosti, Q.; Eberl, T.; Emanuele, U.; Ernenwein, J.-P.; Escoffier, S.; Flaminio, V.; Fritsch, U.; Fuda, J.-L.; Galatà, S.; Giacomelli, G.; Gómez-González, J.P.; Guillard, G.; Halladjian, G.; Hallewell, G.; van Haren, H.; Heijboer, A.J.; Hello, Y.; Hernández-Rey, J.J.; Herold, B.; Hößl, J.; Hsu, C.C.; de Jong, M.; Kadler, M.; Kalantar-Nayestanaki, N.; Kalekin, O.; Kappes, A.; Katz, U.; Kopper, C.; Kouchner, A.; Lahmann, R.; Lamare, P.; Larosa, G.; Lefèvre, D.; Lim, G.; Lo Presti, D.; Loehner, H.; Loucatos, S.; Marcelin, M.; Martinez-Mora, J.A.; Meli, A.; Montaruli, T.; Morganti, M.; Moscoso, L.; Motz, H.; Naumann, C.; Păvălaş, G.E.; Payre, P.; Petrovic, J.; Picq, C.; Popa, V.; Pradier, T.; Presani, E.; Racca, C.; Reed, C.; Richardt, C.; Richter, R.; Salesa, F.; Sapienza, P.; Schöck, F.; Schuller, J.-P.; Shanidze, R.; Spurio, M.; Steijger, J.J.M.; Stolarczyk, Th; Taiuti, M.; Tasca, L.; Toscano, S.; Vallage, B.; Van Elewyck, V.; Vernin, P.; Yepes, H.; Zaborov, D.; Zornoza, J.D.

    Astroparticle physics, 04/2011, Letnik: 34, Številka: 9
    Journal Article

    An algorithm is presented, that provides a fast and robust reconstruction of neutrino induced upward-going muons and a discrimination of these events from downward-going atmospheric muon background in data collected by the ANTARES neutrino telescope. The algorithm consists of a hit merging and hit selection procedure followed by fitting steps for a track hypothesis and a point-like light source. It is particularly well-suited for real time applications such as online monitoring and fast triggering of optical follow-up observations for multi-messenger studies. The performance of the algorithm is evaluated with Monte Carlo simulations and various distributions are compared with that obtained in ANTARES data.