Heidelberg 2022 – wissenschaftliches Programm

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T: Fachverband Teilchenphysik

T 107: Data Analysis, Information Technology and Artificial Intelligence 5

T 107.2: Vortrag

Donnerstag, 24. März 2022, 16:30–16:45, T-H39

Cosmic ray composition measurement with Graph Neural Networks in KM3NeT/ORCA — •Stefan Reck for the ANTARES-KM3NET-ERLANGEN collaboration — Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), ECAP

KM3NeT/ORCA is a water-Cherenkov neutrino detector, currently under construction in the Mediterranean Sea at a depth of 2450 meters. The project's main goal is the determination of the neutrino mass hierarchy by measuring the energy- and zenith-angle-resolved oscillation probabilities of atmospheric neutrinos traversing the Earth. Additionally, the detector observes atmospheric muons, which can be used to study the properties of extensive air showers and cosmic ray particles.

This contribution will present a deep-learning based approach to analyse the signatures of muon bundles traversing the detector using graph convolutional networks. Even though the detector is still in an early stage of construction, this reconstruction can already be used to measure the composition of cosmic ray primary particles.