Trigger based on the artificial neural network implemented in the cyclone V FPGA for a detection of neutrino-origin showers in the Pierre Auger surface detector

摘要

Observations of ultra-high energy neutrinos became a priority in experimental astroparticle physics. Up to now, the Pierre Auger Observatory did not find any candidate on a neutrino event. This imposes competitive limits to the diffuse flux of ultra-high energy neutrinos in the EeV range and above. The prototype Front-End boards for Auger-Beyond-2015 with Cyclone V E can test the neural network algorithm in real pampas conditions in 2015. Showers for muon and tau neutrino initiating particles on various altitudes, angles and energies were simulated in CORSIKA and OffLine platforms giving pattern of ADC traces in Auger water Cherenkov detectors. The 3-layer 12-10-1 neural network was taught in MATLAB by simulated ADC traces according the Levenberg - Marquardt algorithm. New sophisticated trigger implemented in Cyclone V E FPGAs with large amount of DSP blocks, embedded memory running with 120 - 160 MHz sampling may support to discover neutrino events in the Pierre Auger Observatory.