12-Years Observation of Seasonal Variation of Atmospheric Neutrino Flux with IceCube

The IceCube Neutrino Observatory is a cubic-kilometer detector located in the Antarctic ice at the geographic South Pole. It reads out over 5,000 photomultiplier tubes (PMTs) to detect Cherenkov light produced by secondary particles, enabling IceCube to identify both atmospheric and astrophysical neutrinos. One of the main challenges in this effort is effectively distinguishing between muons induced by neutrinos and those generated by cosmic-ray air showers. To address this challenge, the Advanced Northern Tracks Selection (ANTS) employs a graph convolutional neural network. This network is designed to utilize both the sensor data and the geometric arrangement of the detector's photomultiplier tubes (PMTs). By representing each module as a node in a graph and extracting features from each module, the network can capture and integrate both local and global features. This work details the implementation of the network architecture and highlights the improvements in background rejection efficiency compared to existing methods for selecting muon tracks.

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Publication Details

Published
2025-09-23
DOI
https://doi.org/10.22323/1.501.0241
Primary Topic
Astrophysics and Cosmic Phenomena
Type
article
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article

12-Years Observation of Seasonal Variation of Atmospheric Neutrino Flux with IceCube

Lars Philipp Heuermann, L. Schumacher, L. Köpke, Sofia Athanasiadou et al.
Astrophysics and Cosmic Phenomena
article

12-Years Observation of Seasonal Variation of Atmospheric Neutrino Flux with IceCube

Lars Philipp Heuermann, L. Schumacher, L. Köpke, Sofia Athanasiadou, Kiara Carloni, Sarah Mechbal, Rishi Babu, Philip Weigel, Arun Vaidyanathan, Thijs van Eeden, Diego Alberto Coloma Borja, G. M. Spiczak, Christy Love, M. Lamoureux, Krishnamoorthi Jayakumar, Thien Nhan Chau, Spencer Griswold, Woosik Kang, I. Taboada, Daniel Salazar-Gallegos, S. R. Klein, Michael Campana, James DeLaunay, Frank Schröder, Jonathan Mauro, Felix Schlüter, C. H. Wiebusch, P. Desiati, Lukas Hennig, Abdul Rehman, C. De Clercq, John Evans, K. D. de Vries, Alexander Sandrock, Sebastian Schindler, Yuriy Popovych, Federico Bontempo, Hershal Pandya, Ek Narayan Paudel, A. Parenti, G. de Wasseige, Veronika Palušová, A. Haungs, Erik Ganster, Leonora Kardum, Shefali Shefali, J. Vandenbroucke, Colton Hill, Laurent Arnaud, Frederik Hermann Lauber, J. C. Díaz–Vélez, Richard Naab, Julian Saffer, Axel Ponten, Christoph Raab, J. V. Santen, Félix Carbonell, Matheus Hostert, Miaochen Jin, Karriem Upshaw, Diyaselis Delgado, G. C. Hill, Carolin Klein, Felix Henningsen, Markus Dittmer, J. M. Conrad, P. Eller, S. Yoshida, Julia Book, D. F. Cowen, Aswathi Balagopal, Nils Heyer, Joelle Savelberg, S. Sarkar, A. R. Fazely, Finn Mayhew, Kaustav Dutta, Bennett Brinson, F. Halzen, Elena Manao, Martin Wolf, S. Griffin, E. Bernardini, Alicia Mand, J. V. Mead, Alan Coleman, Leon Hamacher, John Rack-Helleis, Thomas Ehrhardt, Agnieszka Leszczyńska, Maximilian Meier, Martina Karl, C. Pérez de los Heros, Cristina Lagunas Gualda, Uwe Naumann, Emma Kun, Sreetama Goswami, Sanjib Kumar Agarwalla, T. Glüsenkamp, C. Finley, Anna Eimer, Matthias Thiesmeyer, Jan Soedingrekso, C. Argüelles, Satoshi Fukami, Aishwarya Vijai, Attila Hidvégi, Kathrine Mørch Groth, Christian Spannfellner, Fahim Varsi, Lucas Bloom, Jan Weldert, Barbara Skrzypek, X. Bai, Gaurav Garg, Yuya Makino, M. Kowalski, E. Blaufuss, Seowon Choi, Shannon Gray, V. A. Parrish, Claudio Kopper, D. Chirkin, Vedant Basu, Oliver Janik, S. 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Abstract

The IceCube Neutrino Observatory is a cubic-kilometer detector located in the Antarctic ice at the geographic South Pole. It reads out over 5,000 photomultiplier tubes (PMTs) to detect Cherenkov light produced by secondary particles, enabling IceCube to identify both atmospheric and astrophysical neutrinos. One of the main challenges in this effort is effectively distinguishing between muons induced by neutrinos and those generated by cosmic-ray air showers. To address this challenge, the Advanced Northern Tracks Selection (ANTS) employs a graph convolutional neural network. This network is designed to utilize both the sensor data and the geometric arrangement of the detector's photomultiplier tubes (PMTs). By representing each module as a node in a graph and extracting features from each module, the network can capture and integrate both local and global features. This work details the implementation of the network architecture and highlights the improvements in background rejection efficiency compared to existing methods for selecting muon tracks.

National Science Foundation, U.S. Department of Energy, University of Wisconsin-Madison, Nvidia, Michigan State University, Villum Fonden, Polarforskningssekretariatet, Marquette University, Western Canada Research Grid, European Commission, National Research Foundation, Deutsche Forschungsgemeinschaft, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Fonds De La Recherche Scientifique - FNRS, Belgian Federal Science Policy Office, Fonds Wetenschappelijk Onderzoek, National Research Foundation of Korea, Knut och Alice Wallenbergs Stiftelse, Vetenskapsrådet, RWTH Aachen University, Chiba University, Helmholtz Alliance for Astroparticle Physics, Alliance de recherche numérique du Canada, College of Engineering, Michigan State University, Natural Sciences and Engineering Research Council of Canada, Deutsches Elektronen-Synchrotron, Japan Society for the Promotion of Science, Marsden Fund, Institute for Global Prominent Research, Chiba University, Office of Polar Programs, Office of Advanced Cyberinfrastructure, Office of Experimental Program to Stimulate Competitive Research
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Astrophysics and Cosmic Phenomena
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