RECONSTRUCTION OF MUON BUNDLES IN KM3NET DETECTORS USING MACHINE LEARNING METHODS
on behalf of the KM3NeT collaboration
DOI:
https://doi.org/10.7494/csci.2025.26.SI.7062Abstract
The KM3NeT Collaboration is installing the ARCA and ORCA neutrino detectors
at the bottom of the Mediterranean Sea. The focus of ARCA is neutrino
astronomy, while ORCA is optimised for neutrino oscillation studies. Both
detectors are already operational in their intermediate states and collect valuable
data, including the measurements of the muons produced by cosmic ray
interactions in the atmosphere. This work explores the potential of machine
learning models for the reconstruction of muon bundles, which are multi-muon
events. For this, data collected with intermediate detector configurations of
ARCA and ORCA was used in addition to simulated data from the envisaged
final configurations of those detectors. Prediction of the total number of muons
in a bundle as well as their total energy and even the energy of the primary
cosmic ray is presented.
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