The cosmic ray proton, helium and CNO fluxes in the 100 TeV energy region from TeV muons and EAS atmospheric Cherenkov light observations of MACRO and EAS-TOP
The primary cosmic ray (CR) proton, helium and CNO fluxes in the energy range 80-300 TeV are studied at the National Gran Sasso Laboratories by means of EAS-TOP (Campo Imperatore, 2005 m a.s.l.) and MACRO (deep underground, 3100 m w.e., the surface energy threshold for a muon reaching the detector being E μth ≈1.3 TeV). The measurement is based on: (a) the selection of primaries based on their energy/nucleon (i.e., with energy/nucleon sufficient to produce a muon with energy larger than 1.3 TeV) and the reconstruction of the shower geometry by means of the muons recorded by MACRO in the deep underground laboratories; (b) the detection of the associated atmospheric Cherenkov light (C.l.) signals by means of the C.l. detector of EAS-TOP. The C.l. density at core distance r>100 m is directly related to the total primary energy E 0 . Proton and helium ("p + He") and proton, helium and CNO ("p + He + CNO") primaries are thus selected at E 0 ≃80 TeV, and at E 0 ≃250 TeV, respectively. Their flux is measured: J p+He (80 Tev= (1.8±0.4)×10 -6 m -2 s -1 sr -1 TeV -1 , and J p+He+CNO (250 TeV)=(1.1±0.3)×10 -7 m -2 s -1 sr -1 TeV -1 , their relative weights being: J p+He /J p+He+CNO (250 TeV)=0.78±0.17. By using the measurements of the proton spectrum obtained from the direct experiments and hadron flux data in the atmosphere, we obtain for the relative weights of the three components at 250 TeV: J p :J He :J CNO =(0.20±0.08): (0.58±0.19):(0.22±0.17). This corresponds to the dominance of helium over proton primaries at 100-1000 TeV, and a possible non-negligible contribution from CNO.The lateral distribution of Cherenkov light in Extensive Air Showers (EASs), which is related to the rate of energy deposit of the primary in the atmosphere, is measured for a selected proton and helium primary beam, and good agreement is found when compared with the one calculated with the CORSIKA/QGSJET simulation model. © 2004 Elsevier B.V. All rights reserved.
Aglietta, M; Alessandro, B; Antonioli, P; Arneodo, F; Bergamasco, L; Bertaina, M; Castagnoli, C; Castellina, A; Chiavassa, A; Cini, G; D'Ettorre Piazzoli, B; di Sciascio, G; Fulgione, W; Galeotti, P; Ghia, PL; Iacovacci, M; Mannocchi, G; Morello, C; Navarra, G; Saavedra, O; Stamerra, A; Trinchero, GC; Valchierotti, S; Vallania, P; Vernetto, S; Vigorito, C; Ambrosio, M; Antolini, R; Baldini, A; Barbarino, GC; Barish, BC; Battistoni, G; Becherini, Y; Bellotti, R; Bemporad, C; Bernardini, P; Bilokon, H; Bower, C; Brigida, M; Bussino, S; Cafagna, F; Calicchio, M; Campana, D; Carboni, M; Caruso, R; Cecchini, S; Cei, F; Chiarella, V; Chiarusi, T; Choudhary, BC; Coutu, S; Cozzi, M; de Cataldo, G; Dekhissi, H; de Marzo, C; de Mitri, I; Derkaoui, J; de Vincenzi, M; di Credico, A; Erriquez, O; Favuzzi, C; Forti, C; Fusco, P; Giacomelli, G; Giannini, G; Giglietto, N; Giorgini, M; Grassi, M; Grillo, A; Guarino, F; Gustavino, C; Habig, A; Hanson, K; Heinz, R; Iarocci, E; Katsavounidis, E; Katsavounidis, I; Kearns, E; Kim, H; Kyriazopoulou, S; Lamanna, E; Lane, C; Levin, DS; Lipari, P; Longley, NP; Longo, MJ; Loparco, F; Maaroufi, F; Mancarella, G; Mandrioli, G; Margiotta, A; Marini, A; Martello, D; Marzari-Chiesa, A; Mazziotta, MN; Michael, DG; Monacelli, P; Montaruli, T; Monteno, M; Mufson, S
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