Tuning parametric models of the atmospheric muon flux in MUPAGE to data from the KM3NeT detector

The muons produced by cosmic ray interactions in the upper atmosphere constitute the most abundant signal for underwater neutrino detectors such as KM3NeT (the Cubic Kilometre Neutrino Telescope), which is currently being deployed in the Mediterranean Sea at two distinct locations. Situated at diffe...

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Published in:Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021)
Main Authors: Ó Fearraigh, Brían, Bozza, Cristiano
Other Authors: Keilhauer, Bianca
Format: Conference Object
Language:English
Published: SISSA 2022
Subjects:
Online Access:https://hdl.handle.net/11386/4877433
https://doi.org/10.22323/1.395.1176
https://pos.sissa.it/395/1176/pdf
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author Ó Fearraigh, Brían
Bozza, Cristiano
author2 Keilhauer, Bianca
Ó Fearraigh, Brían
Bozza, Cristiano
author_facet Ó Fearraigh, Brían
Bozza, Cristiano
author_sort Ó Fearraigh, Brían
collection EleA@Unisa (Università degli Studi di Salerno)
container_start_page 1176
container_title Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021)
description The muons produced by cosmic ray interactions in the upper atmosphere constitute the most abundant signal for underwater neutrino detectors such as KM3NeT (the Cubic Kilometre Neutrino Telescope), which is currently being deployed in the Mediterranean Sea at two distinct locations. Situated at different depths, the KM3NeT/ARCA and KM3NeT/ORCA detectors experience a different flux of muons, and thus are uniquely positioned to study their evolution and propagation from cosmic ray showers. It is imperative to the main physics goals of the experiment that the atmospheric muon background is modelled correctly, which aids in benchmarking and understanding the detector response to the constant flux of these particles. In this study, the data from the KM3NeT/ORCA detector is used and compared with the Monte Carlo (MC) prediction from the MUPAGE (MUons from PArametric formulas: a fast GEnerator for neutrino telescopes) software package, which generates the energy spectrum, lateral distribution, and muon multiplicity of muon bundles according to a specific parametrisation at different depths below sea level. This parametrisation consists of many free parameters which can be tuned such that simulated physical observables in the detector agree with those measured in data. In this way, improvements to the data-MC agreement are achieved by quantitatively comparing the level of agreement between simulated and measured observables in the KM3NeT detector.
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spelling ftunisalernoiris:oai:www.iris.unisa.it:11386/4877433 2025-01-17T00:09:49+00:00 Tuning parametric models of the atmospheric muon flux in MUPAGE to data from the KM3NeT detector Ó Fearraigh, Brían Bozza, Cristiano Keilhauer, Bianca Ó Fearraigh, Brían Bozza, Cristiano 2022 ELETTRONICO https://hdl.handle.net/11386/4877433 https://doi.org/10.22323/1.395.1176 https://pos.sissa.it/395/1176/pdf eng eng SISSA info:eu-repo/semantics/altIdentifier/wos/WOS:001081844904018 ispartofbook:37th International Cosmic Ray Conference 37th International Cosmic Ray Conference volume:395 firstpage:1 lastpage:10 numberofpages:10 journal:POS PROCEEDINGS OF SCIENCE https://hdl.handle.net/11386/4877433 doi:10.22323/1.395.1176 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85145259535 https://pos.sissa.it/395/1176/pdf MUPAGE KM3NeT atmospheric muon flux info:eu-repo/semantics/conferenceObject 2022 ftunisalernoiris https://doi.org/10.22323/1.395.1176 2024-09-17T23:33:15Z The muons produced by cosmic ray interactions in the upper atmosphere constitute the most abundant signal for underwater neutrino detectors such as KM3NeT (the Cubic Kilometre Neutrino Telescope), which is currently being deployed in the Mediterranean Sea at two distinct locations. Situated at different depths, the KM3NeT/ARCA and KM3NeT/ORCA detectors experience a different flux of muons, and thus are uniquely positioned to study their evolution and propagation from cosmic ray showers. It is imperative to the main physics goals of the experiment that the atmospheric muon background is modelled correctly, which aids in benchmarking and understanding the detector response to the constant flux of these particles. In this study, the data from the KM3NeT/ORCA detector is used and compared with the Monte Carlo (MC) prediction from the MUPAGE (MUons from PArametric formulas: a fast GEnerator for neutrino telescopes) software package, which generates the energy spectrum, lateral distribution, and muon multiplicity of muon bundles according to a specific parametrisation at different depths below sea level. This parametrisation consists of many free parameters which can be tuned such that simulated physical observables in the detector agree with those measured in data. In this way, improvements to the data-MC agreement are achieved by quantitatively comparing the level of agreement between simulated and measured observables in the KM3NeT detector. Conference Object Orca EleA@Unisa (Università degli Studi di Salerno) Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021) 1176
spellingShingle MUPAGE
KM3NeT
atmospheric muon flux
Ó Fearraigh, Brían
Bozza, Cristiano
Tuning parametric models of the atmospheric muon flux in MUPAGE to data from the KM3NeT detector
title Tuning parametric models of the atmospheric muon flux in MUPAGE to data from the KM3NeT detector
title_full Tuning parametric models of the atmospheric muon flux in MUPAGE to data from the KM3NeT detector
title_fullStr Tuning parametric models of the atmospheric muon flux in MUPAGE to data from the KM3NeT detector
title_full_unstemmed Tuning parametric models of the atmospheric muon flux in MUPAGE to data from the KM3NeT detector
title_short Tuning parametric models of the atmospheric muon flux in MUPAGE to data from the KM3NeT detector
title_sort tuning parametric models of the atmospheric muon flux in mupage to data from the km3net detector
topic MUPAGE
KM3NeT
atmospheric muon flux
topic_facet MUPAGE
KM3NeT
atmospheric muon flux
url https://hdl.handle.net/11386/4877433
https://doi.org/10.22323/1.395.1176
https://pos.sissa.it/395/1176/pdf