Towards online triggering for the radio detection of air showers using deep neural networks

Jun 13, 2018, 3:50 PM


Florian Führer (Institut d'Astrophysique de Paris)


The detection of air-shower events via radio signals requires to develop a trigger algorithm for a 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 as well as performing an online reconstruction of the shower parameters using neural networks.

Primary author

Florian Führer (Institut d'Astrophysique de Paris)


Anne Zilles (IAP) Matias Tueros (Universidad de Santiago de Compostela) Tom Charnock (Institut d'astrophysique de Paris)

Presentation materials