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

Jun 13, 2018, 3:50 PM
20m

Speaker

Florian Führer (Institut d'Astrophysique de Paris)

Description

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)

Co-authors

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

Presentation materials