Bonn 2020 – scientific programme

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T: Fachverband Teilchenphysik

T 91: Machine Learning: Event and jet reconstruction

T 91.8: Talk

Friday, April 3, 2020, 12:45–13:00, H-HS I

Muon bundle reconstruction with KM3NeT/ORCA using Deep Learning techniques — •Stefan Reck for the ANTARES-KM3NeT-Erlangen collaboration — Friedrich-Alexander-Universität Erlangen-Nürnberg, ECAP

KM3NeT/ORCA is a water-Cherenkov neutrino detector, currently under construction in the Mediterranean Sea at a sea depth of 2450 meters. The projects 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.

Deep Learning techniques provide promising methods to analyse the signatures induced by the particles traversing the detector. Despite being in an early stage of construction, the data taken so far already provide large statistics to investigate the signatures from atmospheric muons. This talk will cover a deep-learning based approach using convolutional networks to reconstruct atmospheric muon bundles, and results on both simulations and data will be presented. Furthermore, the performances are compared to the ones of classical approaches, showing good agreement.