Optimization of an FPGA trigger based on an artificial neural network for the detection of neutrino-induced air showers

0550942 - FZÚ 2022 RIV US eng J - Článek v odborném periodiku
Szadkowski, Z. … celkem 4 autorů
Optimization of an FPGA trigger based on an artificial neural network for the detection of neutrino-induced air showers.
IEEE Transactions on Nuclear Science. Roč. 64, č. 6 (2017), s. 1271-1281. ISSN 0018-9499. E-ISSN 1558-1578
Výzkumná infrastruktura: AUGER-CZ - 90038
Klíčová slova: discrete cosine transform (DCT) * field-programmable gate array (FPGA)
Obor OECD: Particles and field physics
Impakt faktor: 1.440, rok: 2017
Způsob publikování: Omezený přístup
https://doi.org/10.1109/TNS.2017.2706184

Neutrinos play a fundamental role in the understanding of the origin of ultrahigh-energy cosmic rays. They interact through charged and neutral currents in the atmosphere generating extensive air showers. However, the very low rate of events potentially generated by neutrinos is a significant challenge for detection techniques and requires both sophisticated algorithms and high-resolution hardware. Air showers initiated by protons and muon neutrinos at various altitudes, angles, and energies were simulated in CORSIKA and the Auger OffLine event reconstruction platforms, giving analog-to-digital convertor (ADC) patterns in Auger water Cherenkov detectors on the ground.
Trvalý link: http://hdl.handle.net/11104/0326231