Search for Sub-Relativistic Magnetic Monopoles with the IceCube Neutrino Observatory

Magnetic monopoles are beyond standard model particles, predicted by Grand Unified Theories (GUTs) to be created during the early universe. At typical masses of the GUT-scale - above $10^{14}$ GeV - these particles would move at sub-relativistic speeds. The Rubakov-Callan effect predicts that magnetic monopoles can catalyze nucleon decays, in particular the decay of protons. This results in a unique signature of small particle cascades along the trajectory of the slow moving magnetic monopole. Since 2012, a dedicated Slow-Particle Filter has been implemented in the IceCube Neutrino Observatory for the detection of magnetic monopoles. Current limits set an upper bound for the monopole flux at $\Phi_{\mathrm{90}}\leq 10^{-17}$ to $10^{-18} \mathrm{cm}^{-2}\mathrm{s}^{-1}\mathrm{sr}^{-1}$ depending on the catalysis cross section for the proton decay. A detection of the monopole flux thus requires exceptional background rejection and signal efficiency. This is accomplished using machine learning methods. In this analysis, we use a multi-level boosted decision tree classifier. We present the strategy behind the background and signal simulation, the classification efficiency, and IceCube’s projected sensitivity for the detection of sub-relativistic magnetic monopoles.

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Publication Details

Published
2025-09-24
DOI
https://doi.org/10.22323/1.501.0492
Primary Topic
Astrophysics and Cosmic Phenomena
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article
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Search for Sub-Relativistic Magnetic Monopoles with the IceCube Neutrino Observatory

Lars Philipp Heuermann, Delaney Butterfield, L. Schumacher, L. Köpke et al.
Astrophysics and Cosmic Phenomena
article

Search for Sub-Relativistic Magnetic Monopoles with the IceCube Neutrino Observatory

Lars Philipp Heuermann, Delaney Butterfield, L. Schumacher, L. Köpke, Sofia Athanasiadou, Kiara Carloni, Sarah Mechbal, Rishi Babu, Philip Weigel, Arun Vaidyanathan, Thijs van Eeden, Diego Alberto Coloma Borja, Allan Hallgren, G. M. Spiczak, Christy Love, M. Lamoureux, Thien Nhan Chau, Spencer Griswold, Woosik Kang, I. Taboada, Daniel Salazar-Gallegos, Andrés Martínez-Medina, James DeLaunay, Frank Schröder, Jonathan Mauro, Felix Schlüter, Ali Kheirandish, C. H. Wiebusch, P. Desiati, Lukas Hennig, C. De Clercq, Hershal Pandya, Alexander Sandrock, Anil Kumar, Felix Henningsen, Sebastian Schindler, Yuriy Popovych, Federico Bontempo, Axel Ponten, Claudio Kopper, Samvel Ter-Antonyan, Ek Narayan Paudel, A. Parenti, G. de Wasseige, Emre Burak Yildizci, Veronika Palušová, A. Haungs, Benedikt Riedel, Erik Ganster, Kareem Ramadan Farrag, Leonora Kardum, Shefali Shefali, Colton Hill, Frederik Hermann Lauber, J. C. Díaz–Vélez, Alexander Kappes, Richard Naab, Julian Saffer, Christoph Raab, J. V. 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Abstract

Magnetic monopoles are beyond standard model particles, predicted by Grand Unified Theories (GUTs) to be created during the early universe. At typical masses of the GUT-scale - above $10^{14}$ GeV - these particles would move at sub-relativistic speeds. The Rubakov-Callan effect predicts that magnetic monopoles can catalyze nucleon decays, in particular the decay of protons. This results in a unique signature of small particle cascades along the trajectory of the slow moving magnetic monopole. Since 2012, a dedicated Slow-Particle Filter has been implemented in the IceCube Neutrino Observatory for the detection of magnetic monopoles. Current limits set an upper bound for the monopole flux at $\Phi_{\mathrm{90}}\leq 10^{-17}$ to $10^{-18} \mathrm{cm}^{-2}\mathrm{s}^{-1}\mathrm{sr}^{-1}$ depending on the catalysis cross section for the proton decay. A detection of the monopole flux thus requires exceptional background rejection and signal efficiency. This is accomplished using machine learning methods. In this analysis, we use a multi-level boosted decision tree classifier. We present the strategy behind the background and signal simulation, the classification efficiency, and IceCube’s projected sensitivity for the detection of sub-relativistic magnetic monopoles.

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