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Main Authors: Gutjahr, Pascal, Witthaus, Lucas
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2507.14525
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author Gutjahr, Pascal
Witthaus, Lucas
author_facet Gutjahr, Pascal
Witthaus, Lucas
contents Atmospheric muons produced in cosmic-ray air showers are classified as conventional muons from pion and kaon decays and prompt muons from heavy hadron decays. Conventional muons dominate at lower energies, and the prompt component becomes dominant at PeV energies and above. Precisely measuring the atmospheric muon flux from a few GeV to several PeV is valuable for advancing our understanding of cosmic-ray interactions and testing hadronic interaction models. Low-energy muons that stop within the IceCube in-ice array provide valuable information about the energy spectrum of muons from a few hundred GeV up to 10 TeV. Machine learning techniques are employed to enhance event reconstruction and selection to provide insights into the conventional and prompt components. This contribution presents the unfolding of the energy spectrum of stopping muons in IceCube as well as the unfolding of high-energy muons to probe the prompt component.
format Preprint
id arxiv_https___arxiv_org_abs_2507_14525
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Unfolding the Atmospheric Muon Flux with IceCube: Investigating Stopping Muons and High-Energy Prompt Contributions
Gutjahr, Pascal
Witthaus, Lucas
High Energy Astrophysical Phenomena
High Energy Physics - Experiment
Atmospheric muons produced in cosmic-ray air showers are classified as conventional muons from pion and kaon decays and prompt muons from heavy hadron decays. Conventional muons dominate at lower energies, and the prompt component becomes dominant at PeV energies and above. Precisely measuring the atmospheric muon flux from a few GeV to several PeV is valuable for advancing our understanding of cosmic-ray interactions and testing hadronic interaction models. Low-energy muons that stop within the IceCube in-ice array provide valuable information about the energy spectrum of muons from a few hundred GeV up to 10 TeV. Machine learning techniques are employed to enhance event reconstruction and selection to provide insights into the conventional and prompt components. This contribution presents the unfolding of the energy spectrum of stopping muons in IceCube as well as the unfolding of high-energy muons to probe the prompt component.
title Unfolding the Atmospheric Muon Flux with IceCube: Investigating Stopping Muons and High-Energy Prompt Contributions
topic High Energy Astrophysical Phenomena
High Energy Physics - Experiment
url https://arxiv.org/abs/2507.14525