Abstract
IceCube is a neutrino observatory deployed in the glacial ice at the geographic South Pole. The νμ energy unfolding described in this paper is based on data taken with IceCube in its 79-string configuration. A sample of muon neutrino charged-current interactions with a purity of 99.5% was selected by means of a multivariate classification process based on machine learning. The subsequent unfolding was performed using the software Truee. The resulting spectrum covers an Eν-range of more than four orders of magnitude from 125 GeV to 3.2 PeV. Compared to the Honda atmospheric neutrino flux model, the energy spectrum shows an excess of more than 1.9σ in four adjacent bins for neutrino energies Eν≥177.8TeV. The obtained spectrum is fully compatible with previous measurements of the atmospheric neutrino flux and recent IceCube measurements of a flux of high-energy astrophysical neutrinos.
| Original language | English (US) |
|---|---|
| Article number | 692 |
| Journal | European Physical Journal C |
| Volume | 77 |
| Issue number | 10 |
| DOIs | |
| State | Published - Oct 1 2017 |
All Science Journal Classification (ASJC) codes
- Engineering (miscellaneous)
- Physics and Astronomy (miscellaneous)
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Measurement of the νμ energy spectrum with IceCube-79 : IceCube Collaboration. / Aartsen, M. G.; Ackermann, M.; Adams, J. et al.
In: European Physical Journal C, Vol. 77, No. 10, 692, 01.10.2017.Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Measurement of the νμ energy spectrum with IceCube-79
T2 - IceCube Collaboration
AU - Aartsen, M. G.
AU - Ackermann, M.
AU - Adams, J.
AU - Aguilar, J. A.
AU - Ahlers, M.
AU - Ahrens, M.
AU - Al Samarai, I.
AU - Altmann, D.
AU - Andeen, K.
AU - Anderson, T.
AU - Ansseau, I.
AU - Anton, G.
AU - Archinger, M.
AU - Argüelles, C.
AU - Auffenberg, J.
AU - Axani, S.
AU - Bagherpour, H.
AU - Bai, X.
AU - Barwick, S. W.
AU - Baum, V.
AU - Bay, R.
AU - Beatty, J. J.
AU - Becker Tjus, J.
AU - Becker, K. H.
AU - BenZvi, S.
AU - Berley, D.
AU - Bernardini, E.
AU - Besson, D. Z.
AU - Binder, G.
AU - Bindig, D.
AU - Blaufuss, E.
AU - Blot, S.
AU - Bohm, C.
AU - Börner, M.
AU - Bos, F.
AU - Bose, D.
AU - Böser, S.
AU - Botner, O.
AU - Bradascio, F.
AU - Braun, J.
AU - Brayeur, L.
AU - Bretz, H. P.
AU - Bron, S.
AU - Burgman, A.
AU - Carver, T.
AU - Casier, M.
AU - Cheung, E.
AU - Chirkin, D.
AU - Christov, A.
AU - Clark, K.
AU - Classen, L.
AU - Coenders, S.
AU - Collin, G. H.
AU - Conrad, J. M.
AU - Cowen, D. F.
AU - Cross, R.
AU - Day, M.
AU - de André, J. P.A.M.
AU - De Clercq, C.
AU - del Pino Rosendo, E.
AU - Dembinski, H.
AU - De Ridder, S.
AU - Desiati, P.
AU - de Vries, K. D.
AU - de Wasseige, G.
AU - de With, M.
AU - DeYoung, T.
AU - Díaz-Vélez, J. C.
AU - di Lorenzo, V.
AU - Dujmovic, H.
AU - Dumm, J. P.
AU - Dunkman, M.
AU - Eberhardt, B.
AU - Ehrhardt, T.
AU - Eichmann, B.
AU - Eller, P.
AU - Euler, S.
AU - Evenson, P. A.
AU - Fahey, S.
AU - Fazely, A. R.
AU - Feintzeig, J.
AU - Felde, J.
AU - Filimonov, K.
AU - Finley, C.
AU - Flis, S.
AU - Fösig, C. C.
AU - Franckowiak, A.
AU - Friedman, E.
AU - Fuchs, T.
AU - Gaisser, T. K.
AU - Gallagher, J.
AU - Gerhardt, L.
AU - Ghorbani, K.
AU - Giang, W.
AU - Gladstone, L.
AU - Glauch, T.
AU - Glüsenkamp, T.
AU - Goldschmidt, A.
AU - Gonzalez, J. G.
AU - Grant, D.
AU - Griffith, Z.
AU - Haack, C.
AU - Hallgren, A.
AU - Halzen, F.
AU - Hansen, E.
AU - Hansmann, T.
AU - Hanson, K.
AU - Hebecker, D.
AU - Heereman, D.
AU - Helbing, K.
AU - Hellauer, R.
AU - Hickford, S.
AU - Hignight, J.
AU - Hill, G. C.
AU - Hoffman, K. D.
AU - Hoffmann, R.
AU - Hoshina, K.
AU - Huang, F.
AU - Huber, M.
AU - Hultqvist, K.
AU - In, S.
AU - Ishihara, A.
AU - Jacobi, E.
AU - Japaridze, G. S.
AU - Jeong, M.
AU - Jero, K.
AU - Jones, B. J.P.
AU - Kang, W.
AU - Kappes, A.
AU - Karg, T.
AU - Karle, A.
AU - Katz, U.
AU - Kauer, M.
AU - Keivani, A.
AU - Kelley, J. L.
AU - Kheirandish, A.
AU - Kim, J.
AU - Kim, M.
AU - Kintscher, T.
AU - Kiryluk, J.
AU - Kittler, T.
AU - Klein, S. R.
AU - Kohnen, G.
AU - Koirala, R.
AU - Kolanoski, H.
AU - Konietz, R.
AU - Köpke, L.
AU - Kopper, C.
AU - Kopper, S.
AU - Koskinen, D. J.
AU - Kowalski, M.
AU - Krings, K.
AU - Kroll, M.
AU - Krückl, G.
AU - Krüger, C.
AU - Kunnen, J.
AU - Kunwar, S.
AU - Kurahashi, N.
AU - Kuwabara, T.
AU - Kyriacou, A.
AU - Labare, M.
AU - Lanfranchi, J. L.
AU - Larson, M. J.
AU - Lauber, F.
AU - Lennarz, D.
AU - Lesiak-Bzdak, M.
AU - Leuermann, M.
AU - Lu, L.
AU - Lünemann, J.
AU - Madsen, J.
AU - Maggi, G.
AU - Mahn, K. B.M.
AU - Mancina, S.
AU - Maruyama, R.
AU - Mase, K.
AU - Maunu, R.
AU - McNally, F.
AU - Meagher, K.
AU - Medici, M.
AU - Meier, M.
AU - Menne, T.
AU - Merino, G.
AU - Meures, T.
AU - Miarecki, S.
AU - Micallef, J.
AU - Momenté, G.
AU - Montaruli, T.
AU - Moulai, M.
AU - Nahnhauer, R.
AU - Naumann, U.
AU - Neer, G.
AU - Niederhausen, H.
AU - Nowicki, S. C.
AU - Nygren, D. R.
AU - Obertacke Pollmann, A.
AU - Olivas, A.
AU - O’Murchadha, A.
AU - Palczewski, T.
AU - Pandya, H.
AU - Pankova, D. V.
AU - Peiffer, P.
AU - Penek,
AU - Pepper, J. A.
AU - Pérez de los Heros, C.
AU - Pieloth, D.
AU - Pinat, E.
AU - Price, P. B.
AU - Przybylski, G. T.
AU - Quinnan, M.
AU - Raab, C.
AU - Rädel, L.
AU - Rameez, M.
AU - Rawlins, K.
AU - Reimann, R.
AU - Relethford, B.
AU - Relich, M.
AU - Resconi, E.
AU - Rhode, W.
AU - Richman, M.
AU - Riedel, B.
AU - Robertson, S.
AU - Rongen, M.
AU - Rott, C.
AU - Ruhe, T.
AU - Ryckbosch, D.
AU - Rysewyk, D.
AU - Sabbatini, L.
AU - Sanchez Herrera, S. E.
AU - Sandrock, A.
AU - Sandroos, J.
AU - Sarkar, S.
AU - Satalecka, K.
AU - Schlunder, P.
AU - Schmidt, T.
AU - Schoenen, S.
AU - Schöneberg, S.
AU - Schumacher, L.
AU - Seckel, D.
AU - Seunarine, S.
AU - Soldin, D.
AU - Song, M.
AU - Spiczak, G. M.
AU - Spiering, C.
AU - Stachurska, J.
AU - Stanev, T.
AU - Stasik, A.
AU - Stettner, J.
AU - Steuer, A.
AU - Stezelberger, T.
AU - Stokstad, R. G.
AU - Stößl, A.
AU - Ström, R.
AU - Strotjohann, N. L.
AU - Sullivan, G. W.
AU - Sutherland, M.
AU - Taavola, H.
AU - Taboada, I.
AU - Tatar, J.
AU - Tenholt, F.
AU - Ter-Antonyan, S.
AU - Terliuk, A.
AU - Tešić, G.
AU - Tilav, S.
AU - Toale, P. A.
AU - Tobin, M. N.
AU - Toscano, S.
AU - Tosi, D.
AU - Tselengidou, M.
AU - Tung, C. F.
AU - Turcati, A.
AU - Unger, E.
AU - Usner, M.
AU - Vandenbroucke, J.
AU - van Eijndhoven, N.
AU - Vanheule, S.
AU - van Rossem, M.
AU - van Santen, J.
AU - Vehring, M.
AU - Voge, M.
AU - Vogel, E.
AU - Vraeghe, M.
AU - Walck, C.
AU - Wallace, A.
AU - Wallraff, M.
AU - Wandkowsky, N.
AU - Waza, A.
AU - Weaver, Ch
AU - Weiss, M. J.
AU - Wendt, C.
AU - Westerhoff, S.
AU - Whelan, B. J.
AU - Wickmann, S.
AU - Wiebe, K.
AU - Wiebusch, C. H.
AU - Wille, L.
AU - Williams, D. R.
AU - Wills, L.
AU - Wolf, M.
AU - Wood, T. R.
AU - Woolsey, E.
AU - Woschnagg, K.
AU - Xu, D. L.
AU - Xu, X. W.
AU - Xu, Y.
AU - Yanez, J. P.
AU - Yodh, G.
AU - Yoshida, S.
AU - Zoll, M.
N1 - Funding Information: Grid and Compute/Calcul Canada; Swedish Research Council, Swedish Polar Research Secretariat, Swedish National Infrastructure for Computing (SNIC), and Knut and Alice Wallenberg Foundation, Sweden; German Ministry for Education and Research (BMBF), Deutsche Forschungsgemeinschaft (DFG), Helmholtz Alliance for Astroparti-cle Physics (HAP), Research Department of Plasmas with Complex Interactions (Bochum), Germany; Fund for Scientific Research (FNRS-FWO), FWO Odysseus programme, Flanders Institute to encourage scientific and technological research in industry (IWT), Belgian Federal Science Policy Office (Belspo); University of Oxford, United Kingdom; Marsden Fund, New Zealand; Australian Research Council; Japan Society for Promotion of Science (JSPS); the Swiss National Science Foundation (SNSF), Switzerland; National Research Foundation of Korea (NRF); Villum Fonden, Danish National Research Foundation (DNRF), Denmark Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecomm ons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Funded by SCOAP3. Funding Information: Acknowledgements We acknowledge the support from the following agencies: U.S. National Science Foundation-Office of Polar Programs, U.S. National Science Foundation-Physics Division, University of Wisconsin Alumni Research Foundation, the Grid Laboratory Of Wisconsin (GLOW) grid infrastructure at the University of Wisconsin-Madison, the Open Science Grid (OSG) grid infrastructure; U.S. Department of Energy, and National Energy Research Scientific Computing Center, the Louisiana Optical Network Initiative (LONI) grid computing resources; Natural Sciences and Engineering Research Council of Canada, West- Publisher Copyright: © 2017, The Author(s).
PY - 2017/10/1
Y1 - 2017/10/1
N2 - IceCube is a neutrino observatory deployed in the glacial ice at the geographic South Pole. The νμ energy unfolding described in this paper is based on data taken with IceCube in its 79-string configuration. A sample of muon neutrino charged-current interactions with a purity of 99.5% was selected by means of a multivariate classification process based on machine learning. The subsequent unfolding was performed using the software Truee. The resulting spectrum covers an Eν-range of more than four orders of magnitude from 125 GeV to 3.2 PeV. Compared to the Honda atmospheric neutrino flux model, the energy spectrum shows an excess of more than 1.9σ in four adjacent bins for neutrino energies Eν≥177.8TeV. The obtained spectrum is fully compatible with previous measurements of the atmospheric neutrino flux and recent IceCube measurements of a flux of high-energy astrophysical neutrinos.
AB - IceCube is a neutrino observatory deployed in the glacial ice at the geographic South Pole. The νμ energy unfolding described in this paper is based on data taken with IceCube in its 79-string configuration. A sample of muon neutrino charged-current interactions with a purity of 99.5% was selected by means of a multivariate classification process based on machine learning. The subsequent unfolding was performed using the software Truee. The resulting spectrum covers an Eν-range of more than four orders of magnitude from 125 GeV to 3.2 PeV. Compared to the Honda atmospheric neutrino flux model, the energy spectrum shows an excess of more than 1.9σ in four adjacent bins for neutrino energies Eν≥177.8TeV. The obtained spectrum is fully compatible with previous measurements of the atmospheric neutrino flux and recent IceCube measurements of a flux of high-energy astrophysical neutrinos.
UR - http://www.scopus.com/inward/record.url?scp=85032267568&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85032267568&partnerID=8YFLogxK
U2 - 10.1140/epjc/s10052-017-5261-3
DO - 10.1140/epjc/s10052-017-5261-3
M3 - Article
AN - SCOPUS:85032267568
SN - 1434-6044
VL - 77
JO - European Physical Journal C
JF - European Physical Journal C
IS - 10
M1 - 692
ER -