Hanson, K.
2D Convolutional Neural Network for Event Reconstruction in IceCube DeepCore
Peterson, J. H., Rodriguez, M. Prado, Hanson, K.
IceCube DeepCore is an extension of the IceCube Neutrino Observatory designed to measure GeV scale atmospheric neutrino interactions for the purpose of neutrino oscillation studies. Distinguishing muon neutrinos from other flavors and reconstructing inelasticity are especially difficult tasks at GeV scale energies in IceCube DeepCore due to sparse instrumentation. Convolutional neural networks (CNNs) have been found to have better success at neutrino event reconstruction than conventional likelihood-based methods. In this contribution, we present a new CNN model that exploits time and depth translational symmetry in IceCube DeepCore data and present the model's performance, specifically for flavor identification and inelasticity reconstruction.
Observation of high-energy neutrinos from the Galactic plane
Abbasi, R., Ackermann, M., Adams, J., Aguilar, J. A., Ahlers, M., Ahrens, M., Alameddine, J. M., Alves, A. A. Jr., Amin, N. M., Andeen, K., Anderson, T., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Axani, S., Bai, X., V., A. Balagopal, Barwick, S. W., Basu, V., Baur, S., Bay, R., Beatty, J. J., Becker, K. -H., Tjus, J. Becker, Beise, J., Bellenghi, C., Benda, S., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Binder, G., Bindig, D., Blaufuss, E., Blot, S., Boddenberg, M., Bontempo, F., Book, J. Y., Borowka, J., Böser, S., Botner, O., Böttcher, J., Bourbeau, E., Bradascio, F., Braun, J., Brinson, B., Bron, S., Brostean-Kaiser, J., Burley, R. T., Busse, R. S., Campana, M. A., Carnie-Bronca, E. G., Chen, C., Chen, Z., Chirkin, D., Choi, K., Clark, B. A., Clark, K., Classen, L., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Correa, P., Cowen, D. F., Cross, R., Dappen, C., Dave, P., De Clercq, C., DeLaunay, J. J., López, D. Delgado, Dembinski, H., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Dujmovic, H., Dunkman, M., DuVernois, M. A., Ehrhardt, T., Eller, P., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Fienberg, A. T., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Friedman, E., Fritz, A., Fürst, P., Gaisser, T. K., Gallagher, J., Ganster, E., Garcia, A., Garrappa, S., Gerhardt, L., Ghadimi, A., Glaser, C., Glauch, T., Glüsenkamp, T., Goehlke, N., Goldschmidt, A., Gonzalez, J. G., Goswami, S., Grant, D., Grégoire, T., Griswold, S., Günther, C., Gutjahr, P., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Minh, M. Ha, Hanson, K., Hardin, J., Harnisch, A. A., Haungs, A., Helbing, K., Henningsen, F., Hettinger, E. C., Hickford, S., Hignight, J., Hill, C., Hill, G. C., Hoffman, K. D., Hoshina, K., Hou, W., Huang, F., Huber, M., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., In, S., Iovine, N., Ishihara, A., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katz, U., Kauer, M., Kellermann, M., Kelley, J. L., Kheirandish, A., Kin, K., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Kopper, S., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krupczak, E., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lanfranchi, J. L., Larson, M. J., Lauber, F., Lazar, J. P., Lee, J. W., Leonard, K., Leszczyńska, A., Li, Y., Lincetto, M., Liu, Q. R., Liubarska, M., Lohfink, E., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Ludwig, A., Luszczak, W., Lyu, Y., Ma, W. Y., Madsen, J., Mahn, K. B. M., Makino, Y., Mancina, S., Mariş, I. C., Martinez-Soler, I., Maruyama, R., McCarthy, S., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Meighen-Berger, S., Merckx, Y., Micallef, J., Mockler, D., Montaruli, T., Moore, R. W., Morik, K., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nahnhauer, R., Naumann, U., Necker, J., Nguyen, L. V., Niederhausen, H., Nisa, M. U., Nowicki, S. C., Nygren, D., Pollmann, A. Obertacke, Oehler, M., Oeyen, B., Olivas, A., O'Sullivan, E., Pandya, H., Pankova, D. V., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Peters, L., Peterson, J., Philippen, S., Pieper, S., Pizzuto, A., Plum, M., Popovych, Y., Porcelli, A., Rodriguez, M. Prado, Pries, B., Przybylski, G. T., Raab, C., Rack-Helleis, J., Raissi, A., Rameez, M., Rawlins, K., Rea, I. C., Rechav, Z., Rehman, A., Reichherzer, P., Reimann, R., Renzi, G., Resconi, E., Reusch, S., Rhode, W., Richman, M., Riedel, B., Roberts, E. J., Robertson, S., Roellinghoff, G., Rongen, M., Rott, C., Ruhe, T., Ryckbosch, D., Cantu, D. Rysewyk, Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Herrera, S. E. Sanchez, Sandrock, A., Santander, M., Sarkar, S., Sarkar, S., Satalecka, K., Schaufel, M., Schieler, H., Schindler, S., Schmidt, T., Schneider, A., Schneider, J., Schröder, F. G., Schumacher, L., Schwefer, G., Sclafani, S., Seckel, D., Seunarine, S., Sharma, A., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Sogaard, A., Soldin, D., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stein, R., Stettner, J., Stezelberger, T., Stokstad, B., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Thwaites, J., Tilav, S., Tischbein, F., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Tselengidou, M., Tung, C. F., Turcati, A., Turcotte, R., Turley, C. F., Twagirayezu, J. P., Ty, B., Elorrieta, M. A. Unland, Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Veitch-Michaelis, J., Verpoest, S., Walck, C., Wang, W., Watson, T. B., Weaver, C., Weigel, P., Weindl, A., Weiss, M. J., Weldert, J., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Willey, N., Williams, D. R., Wolf, M., Wrede, G., Wulff, J., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P.
The origin of high-energy cosmic rays, atomic nuclei that continuously impact Earth's atmosphere, has been a mystery for over a century. Due to deflection in interstellar magnetic fields, cosmic rays from the Milky Way arrive at Earth from random directions. However, near their sources and during propagation, cosmic rays interact with matter and produce high-energy neutrinos. We search for neutrino emission using machine learning techniques applied to ten years of data from the IceCube Neutrino Observatory. We identify neutrino emission from the Galactic plane at the 4.5$\sigma$ level of significance, by comparing diffuse emission models to a background-only hypothesis. The signal is consistent with modeled diffuse emission from the Galactic plane, but could also arise from a population of unresolved point sources.