https://doi.org/10.1051/epjconf/201921603004
Towards online triggering for the radio detection of air showers using deep neural networks
1
Sorbonne Université, UPMC Univ. Paris 6 et CNRS, UMR 7095, Institut d’Astrophysique de Paris, 98 bisbd Arago
75014 Paris, France
2
Sorbonne Université, Institut Lagrange de Paris, 98bis boulevard Arago, 75014 Paris, France
3
Instituto de Fésica La Plata - CONICET/CCT- La Plata.Calle 49 esq 115. La Plata, Buenos Aires, Argentina
★ e-mail: fuhrer@iap.fr
Published online: 24 September 2019
The detection of air-shower events via radio signals requires the development of a trigger algorithm for clean discrimination between signal and background events in order to reduce the data stream coming from false triggers. In this contribution we will describe an approach to trigger air-shower events on a single-antenna level aswell as performing an online reconstruction of the shower parameters using neural networks.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
