JOURNAL ARTICLE

Latest results and outlook of the KM3NeT neutrino telescope.

  • Published In: International Journal of Modern Physics A: Particles & Fields; Gravitation; Cosmology; Nuclear Physics, 2025, v. 40, n. 8. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Romanov, Andrey 3 of 3

Abstract

The KM3NeT research infrastructure includes two underwater Cherenkov telescopes in the Mediterranean Sea, KM3NeT/ARCA and KM3NeT/ORCA. The detectors are under construction but are currently taking data and the first physics results were already obtained. The detection technology is the same for both telescopes but the detector geometries are different as they have been tailored to different scientific goals. The KM3NeT/ARCA telescope, located off-shore the Sicilian coast in Italy, focuses on studying the high-energy cosmic neutrinos in the TeV–PeV energy range. The KM3NeT/ORCA location is off-shore Toulon in France and its main goal is to explore the atmospheric neutrino oscillations in the GeV energy range. An overview of the recent results achieved with the KM3NeT detectors in their partial configurations is given in this work. Also, the sensitivity to the cosmic neutrino measurements and the oscillation studies with the completed KM3NeT/ARCA and KM3NeT/ORCA telescopes are presented. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Modern Physics A: Particles & Fields; Gravitation; Cosmology; Nuclear Physics. 2025/03, Vol. 40, Issue 8, p1
  • Document Type:Article
  • Subject Area:Astronomy and Astrophysics
  • Publication Date:2025
  • ISSN:0217-751X
  • DOI:10.1142/S0217751X24430279
  • Accession Number:184145758
  • Copyright Statement:Copyright of International Journal of Modern Physics A: Particles & Fields; Gravitation; Cosmology; Nuclear Physics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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