1. A Convolutional Neural Network based Cascade Reconstruction for the IceCube Neutrino Observatory
- Author
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J. Werthebach, A. Franckowiak, Chujie Chen, Ioana Codrina Maris, K. Hoshina, A. Steuer, A. Weindl, Maryon Ahrens, P. Schlunder, Saskia Philippen, Glenn Spiczak, G. Momenté, Segev BenZvi, Spencer Klein, M. Rameez, Sam De Ridder, Frederik Tenholt, R. Nagai, D. F. Cowen, Martin Unland Elorrieta, Stephen L. Hauser, Christoph Raab, Nadège Iovine, Barbara Skrzypek, Kara Hoffman, Sarah Mancina, N. van Eijndhoven, U. Naumann, Raamis Hussain, D. Berley, G. C. Hill, Tobias Hoinka, Vedant Basu, Steve Sclafani, J. Kiryluk, B. J. P. Jones, Andres Medina, D. Mockler, Bunheng Ty, Ralph Engel, Moritz Kellermann, U. Katz, Emily Dvorak, Timo Karg, K. Andeen, D. R. Nygren, Marek Kowalski, D. Kang, Giovanni Renzi, K. D. de Vries, M. Stamatikos, Hershal Pandya, Wolfgang Rhode, Robert Stein, A.A. Alves, Pablo Correa, D. Seckel, S. Fahey, Javier Gonzalez, Roxanne Turcotte, Maximilian Karl Scharf, Alexander Trettin, P. B. Price, I. Taboada, Gisela Anton, Michael O. Wolf, Lenka Tomankova, Max Renschler, Y. Makino, Matthias Vraeghe, Tyce DeYoung, K. Tollefson, D. J. Koskinen, K. Rawlins, Nathan Whitehorn, C. Weaver, T. Anderson, B. A. Clark, Francesco Lucarelli, Brandom Pries, L. Schumacher, Devyn Rysewyk Cantu, P. Peiffer, J. Kim, Daria Pankova, E. Friedman, M. Kauer, Alan Coleman, John Hardin, Shefali Shefali, Nora Valtonen-Mattila, M. E. Huber, D. B. Fox, Alexander Fritz, D. Z. Besson, T. O. B. Schmidt, E. Bourbeau, Suyong Choi, M. Silva, Najia Moureen Binte Amin, J. P. Lazar, Sebastian Böser, R. Morse, Spencer Griswold, Jakob Bottcher, T. Montaruli, David A. Williams, A. Goldschmidt, K. Mase, Abdul Rehman, David Kappesser, Kurt Woschnagg, Paul Evenson, Clara E. Hill, Le Viet Nguyen, Sebastian Sanchez Herrera, Marcos Santander, Carsten Rott, L. Gerhardt, Y. Popovych, J. Evans, Maria Tselengidou, D. Soldin, J. B. Tjus, Chiara Bellenghi, Alexander A. Harnisch, Benjamin Bastian, Anastasia Maria Barbano, Markus Ackermann, S. W. Barwick, Matti Jansson, Immacolata Carmen Rea, P. Eller, Simone Garrappa, H. Schieler, Dmitry Chirkin, Kael Hanson, A. Kyriacou, A. Olivas, Hermann Kolanoski, Simeon Reusch, A. O. Pollmann, Elisa Bernardini, K. Meagher, S. Hickford, J. C. Gallagher, Kirill Filimonov, Mehmet Gunduz, Agnieszka Leszczyńska, R. C. Bay, Alexander Kappes, Pranav Dave, Jan Soedingrekso, K. Krings, Xianwu Xu, J. Sandroos, James Madsen, Lu Lu, M. J. Weiss, Stef Verpoest, H. Dujmovic, Austin Schneider, Juan Carlos Diaz-Velez, Jenni Adams, K.-H. Becker, Yiqian Xu, M. Plum, A. Wallace, Katharina Morik, J. Stettner, Daniel Bindig, Ramesh Koirala, Gerrit Wrede, C.P. de los Heros, Thomas Huber, Ek Narayan Paudel, Allan Hallgren, Matt Dunkman, R. Joppe, T. Stezelberger, Colin Turley, S. Kopper, Christian Glaser, Paolo Desiati, S. Sarker, C. Alispach, Damian Pieloth, R. G. Stokstad, Ali Kheirandish, Sreetama Goswami, Minjin Jeong, Martin Ha Minh, T. Glüsenkamp, Janet Conrad, G. Krückl, Jannis Necker, Sebastian Baur, R. Cross, Sebastian Fiedlschuster, Surujhdeo Seunarine, Ken'ichi Kin, Jannes Brostean-Kaiser, Chunfai Tung, Alejandro Diaz, M. J. Larson, M. U. Nisa, Tim Ruhe, E. O'Sullivan, René Reimann, Chad Finley, Federica Bradascio, A. V. Balagopal, Alexander Burgman, M. Meier, Michael Campana, F. Huang, Christoph Tönnis, Benjamin Hokanson-Fasig, E. Blaufuss, Leander Fischer, Gerrit Roellinghoff, Mirco Hunnefeld, Marie Oehler, Thomas Stuttard, William Luszczak, G. H. Collin, Sarah Pieper, Dirk Ryckbosch, S. Robertson, R. Snihur, A. Ludwig, Wing Yan Ma, Yang Lyu, Grant Parker, L. Köpke, Karl J. Clark, Juanan Aguilar, I. Safa, Merlin Schaufel, James DeLaunay, Marjon Moulai, Olga Botner, Cristian Jesus Lozano Mariscal, Kendall Mahn, L. Classen, Johan Wulff, K. Wiebe, Timothyblake Watson, J. J. Beatty, Tianlu Yuan, Stephan Meighen-Berger, S. Yoshida, Kayla Leonard, A. Ishihara, V. Baum, H. Niederhausen, Won Nam Kang, Joshua Hignight, A. Sharma, Sukeerthi Dharani, Francis Halzen, J. Merz, Paras Koundal, Mike Richman, X. Bai, Konstancja Satalecka, F. McNally, Emma C. Hettinger, I. Ansseau, Michael Kovacevich, Theo Glauch, Juliana Stachurska, H. Dembinski, Reina H. Maruyama, Frank G. Schröder, Summer Blot, Thomas Ehrhardt, D. Tosi, D. van Eijk, Mark Weyrauch, Spencer Axani, Elisa Lohfink, Aaron Fienberg, Amirreza Raissi, S. Tilav, Michael DuVernois, Carlos Arguelles, Jessie Micallef, Stephanie Bron, R. S. Busse, Y. L. Li, J. P. Yanez, Gerald Przybylski, Christian Haack, Christopher Wiebusch, R. Halliday, Kunal Deoskar, K. Helbing, Alexander Sandrock, N. Kurahashi, Todor Stanev, Benedikt Riedel, Cristina Lagunas Gualda, C. Wendt, G. W. Sullivan, A. Karle, James E. Braun, Philipp Furst, D. Hebecker, G. de Wasseige, George Japaridze, Roger Moore, Paul Coppin, Andrea Turcati, T. Gregoire, J. van Santen, R. Hoffmann, Alex Pizzuto, Gary Binder, J. Bourbeau, Richard Naab, Zhedong Zhang, C. Walck, Thomas K. Gaisser, Ava Ghadimi, Franziska Tischbein, Seongjin In, Elisa Resconi, Alessio Porcelli, P. Mallik, Catherine De Clercq, M. Rongen, Qinrui Liu, Martina Karl, Jochen M. Schneider, Christian Spiering, Justin Vandenbroucke, Maria Prado Rodriguez, Abhishek Desai, Xinyue Kang, Claudio Kopper, S. C. Nowicki, Subir Sarkar, T. Kintscher, Frederik Hermann Lauber, Justin Lanfranchi, David Vannerom, Ben Smithers, Jean Pierre Twagirayezu, A. Haungs, Rui An, Nahee Park, K. Hultqvist, Darren Grant, T. Stürwald, Z. Griffith, Felix Henningsen, A. R. Fazely, Simona Toscano, J. L. Kelley, Markus Ahlers, Erik Ganster, Samvel Ter-Antonyan, Rasha Abbasi, B. J. Whelan, Jan Weldert, L. Halve, Physics, Faculty of Sciences and Bioengineering Sciences, Vriendenkring VUB, Elementary Particle Physics, and collaboration, The IceCube
- Subjects
FOS: Computer and information sciences ,Computer Science - Machine Learning ,Astrophysics::High Energy Astrophysical Phenomena ,cs.LG ,Data analysis ,FOS: Physical sciences ,Fitting methods ,01 natural sciences ,Convolutional neural network ,Calibration ,Cluster finding ,Neutrino detectors ,Pattern recognition ,High Energy Physics - Experiment ,IceCube Neutrino Observatory ,Machine Learning (cs.LG) ,High Energy Physics - Experiment (hep-ex) ,0103 physical sciences ,010303 astronomy & astrophysics ,Instrumentation ,Mathematical Physics ,010308 nuclear & particles physics ,business.industry ,hep-ex ,Deep learning ,Detector ,Neutrino detector ,Computer engineering ,Orders of magnitude (time) ,13. Climate action ,Cascade ,Pattern recognition (psychology) ,Artificial intelligence ,business - Abstract
Continued improvements on existing reconstruction methods are vital to the success of high-energy physics experiments, such as the IceCube Neutrino Observatory. In IceCube, further challenges arise as the detector is situated at the geographic South Pole where computational resources are limited. However, to perform real-time analyses and to issue alerts to telescopes around the world, powerful and fast reconstruction methods are desired. Deep neural networks can be extremely powerful, and their usage is computationally inexpensive once the networks are trained. These characteristics make a deep learning-based approach an excellent candidate for the application in IceCube. A reconstruction method based on convolutional architectures and hexagonally shaped kernels is presented. The presented method is robust towards systematic uncertainties in the simulation and has been tested on experimental data. In comparison to standard reconstruction methods in IceCube, it can improve upon the reconstruction accuracy, while reducing the time necessary to run the reconstruction by two to three orders of magnitude., Comment: 39 pages, 15 figures, submitted to Journal of Instrumentation; added references
- Published
- 2021