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Seasonal variations of the atmospheric muon neutrino spectrum measured with IceCube

  • Icecube Collaboration
  • Department of Physics
  • TU Dortmund University
  • University of Wisconsin-Madison
  • Harvard University
  • Stony Brook University
  • Michigan State University
  • Ruhr University Bochum
  • University of Utah
  • University of Kansas
  • Chiba University
  • University of Alberta
  • Southern University and A&M College
  • Friedrich-Alexander University Erlangen-Nürnberg
  • Technical University of Munich
  • University of Alabama
  • RWTH Aachen University
  • Karlsruhe Institute of Technology
  • Pennsylvania State University
  • Massachusetts Institute of Technology
  • Georgia Institute of Technology
  • Oskar Klein Centre
  • University of Maryland, College Park
  • Columbia University
  • University of Delaware
  • University of Canterbury
  • Université catholique de Louvain
  • University of Münster
  • German Electron Synchrotron
  • Vrije Universiteit Brussel
  • Uppsala University
  • Marquette University
  • Institute of Physics Bhubaneswar

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This study presents an analysis of seasonal variations in the atmospheric muon neutrino flux, using 11.3 years of data from the IceCube Neutrino Observatory. By leveraging a novel spectral unfolding method, we explore the energy range from 125 GeV to 10 TeV for zenith angles from 90∘ to 110∘, corresponding to the Antarctic atmosphere. Our findings reveal that the differential measurement of the amplitudes of the seasonal variation is consistent with an energy-dependent decrease reaching (-4.5 ± 1.2)% during Austral winter and increase to (+ 3.9 ± 1.3)% during Austral summer relative to the annual average at 10 TeV. While the unfolded flux exceeds the model predictions by up to 30%, the differential measurement of the seasonal to annual average flux remains unaffected. The measured seasonal variations of the muon neutrino spectrum are consistent with theoretical predictions using the MCEq code and the NRLMSISE-00 atmospheric model.

Original languageEnglish
Article number1368
JournalEuropean Physical Journal C
Volume85
Issue number12
DOIs
StatePublished - Dec 2025

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