Aachen 2019 – scientific programme
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AKPIK: Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz
AKPIK 3: Machine-learning methods and computing in astroparticle physics
AKPIK 3.7: Talk
Wednesday, March 27, 2019, 17:00–17:10, H06
Towards online triggering for the radio detection of air showers using deep neural networks — •Florian Führer1,2 and Anne Zilles1 — 1Institut d'Astrophysique de Paris — 2Institut Lagrange de Paris
The future Giant Radio Array for Neutrino Detection (GRAND) is designed as a huge standalone radio array to detect UHE neutrinos.
The detection of air-shower events induced by high-energetic particles via the emitted radio signals only requires the development of a trigger algorithm for a clean discrimination between signal and background events.
In this contribution we will describe an approach to trigger air-shower events on a single-antenna level as well as performing an online reconstruction of the shower parameters using neural networks. If time permits we will outline strategies to compress and hence speed-up the evaluation of neural networks, hence allowing to apply neural network based triggers in real-time.