Bonn 2020 – scientific programme

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T: Fachverband Teilchenphysik

T 91: Machine Learning: Event and jet reconstruction

T 91.1: Talk

Friday, April 3, 2020, 11:00–11:15, H-HS I

Event reconstruction for ANTARES using Convolutional Neural Networks — •Nicole Geißelbrecht for the ANTARES-KM3NeT-Erlangen collaboration — FAU Erlangen-Nürnberg, ECAP

ANTARES is the largest undersea neutrino detector, installed in the Mediterranean Sea, and is primarily sensitive to neutrinos in the TeV-PeV energy range. Data taking with the telescope has been continous since 2008. One of the central goals of ANTARES, next to searches for neutrino signals from point, transient, and extended sources, is an independent detection and investigation of the diffuse cosmic neutrino flux discovered by IceCube. The suppression of backgrounds, in particular of atmospheric muons, is essential to further increase the sensitivity of the data analysis. The contribution reports on the design and application of deep Convolutional Neural Networks to ANTARES telescope data. Data preprocessing concepts, image generation, and first performance investigations of an event-topology classificator will be presented.