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Study of Mass Composition of Cosmic Rays with IceTop and IceCube

  • The IceCube Collaboration
  • Karlsruhe Institute of Technology
  • Marquette University
  • Loyola University Chicago
  • German Electron Synchrotron
  • University of Canterbury
  • Université libre de Bruxelles
  • University of Copenhagen
  • Oskar Klein Centre
  • University of Geneva
  • University of Delaware
  • Harvard University
  • Pennsylvania State University
  • Friedrich-Alexander University Erlangen-Nürnberg
  • University of Wisconsin-Madison
  • Massachusetts Institute of Technology
  • South Dakota School of Mines & Technology
  • University of California at Irvine
  • University of California at Berkeley
  • Ohio State University
  • University of Wuppertal
  • Ruhr University Bochum
  • Technical University of Munich
  • University of Rochester
  • University of Maryland, College Park
  • University of Padua
  • University of Kansas
  • Moscow Engineering Physics Institute
  • Lawrence Berkeley National Laboratory
  • RWTH Aachen University
  • Johannes Gutenberg University Mainz
  • Uppsala University

Research output: Contribution to journal › Conference article › peer-review

Abstract

The IceCube Neutrino Observatory is a multi-component detector at the South Pole which detects high-energy particles emerging from astrophysical events. These particles provide us with insights into the fundamental properties and behaviour of their sources. Besides its principal usage and merits in neutrino astronomy, using IceCube in conjunction with its surface array, IceTop, also makes it a unique three-dimensional cosmic-ray detector. This distinctive feature helps facilitate detailed cosmic-ray analysis in the transition region from galactic to extragalactic sources. We will present the progress made on multiple fronts to establish a framework for mass-estimation of primary cosmic rays. The first technique relies on a likelihood-based analysis of the surface signal distribution and improves upon the standard reconstruction technique. The second uses advanced methods in graph neural networks to use the full in-ice shower footprint, in addition to global shower-footprint features from IceTop. A comparison between the two methods for composition analysis as well as a possible extension of the analysis techniques for sub-PeV cosmic-ray air-showers will also be discussed.

Original languageEnglish
Article number245
JournalProceedings of Science
Volume395
StatePublished - Mar 18 2022
Event37th International Cosmic Ray Conference, ICRC 2021 - Virtual, Berlin, Germany
Duration: Jul 12 2021 → Jul 23 2021

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