Multiplier-less approach in the neural network trigger algorithm for a detection of cosmic rays

0549098 - FZÚ 2022 RIV US eng C - Conference Paper (international conference)
Szadkowski, Z.
Multiplier-less approach in the neural network trigger algorithm for a detection of cosmic rays.
Proceedings of 11th International Conference on Computational Intelligence and Communication Networks (CICN 2019). Danvers: IEEE, 2019, s. 13-18. ISBN 978-1-5386-8440-5.
[International Conference on Computational Intelligence and Communication Networks (CICN 2019) /11./. Honolulu, HI (US), 03.01.2019-04.01.2019]
Research Infrastructure: AUGER-CZ - 90038
Keywords : Pierre Auger Observatory * neural networks * FPGA
OECD category: Particles and field physics
https://doi.org/10.1109/CICN.2019.8902417

Nowadays astrophysics is focused on understand the origin of the ultrahigh-energy cosmic rays (UHECR). Finding sources of UHECR is difficult, due to deflection of charged particles in intergalactic magnetic fields. This problem can be, however, avoided by detecting electrically neutral particles, such as neutrinos, which are created by the UHECR particles in interactions during propagation. Due to the very low cross section of the neutrinos, the detection technique requires a very sophisticated algorithm.Our trigger algorithm is based on an analysis of signal shapes by an artificial neural network (ANN). This approach can efficiently separate air showers which started at the top of the atmosphere.
Permanent Link: http://hdl.handle.net/11104/0325125