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

著录项

• 来源
  《Federated Conference on Computer Science and Information Systems》|2015年|693-700|共8页
• 会议地点
• 作者

  Szadkowski Zbigniew; Głas Dariusz; Pytel Krzysztof;

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• 会议组织
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• 正文语种
• 中图分类
• 关键词

  Cherenkov counters; cosmic ray apparatus; cosmic ray neutrinos; cosmic ray showers; high-energy cosmic ray interactions; neural nets; 3-layer neural network; ADC traces; Auger water Cherenkov detectors; CORSIKA platforms; Cyclone V FPGA; Levenberg-Marquardt algorithm; OffLine platforms; Pierre Auger Observatory; Pierre Auger surface detector; artificial neural network; experimental astroparticle physics; muon initiating particles; neural network algorithm; neutrino event; neutrino-origin showers detection; prototype Front-End boards; real pampas conditions; tau neutrino initiating particles; ultra-high energy neutrinos; Artificial neural networks; Atmosphere; Detectors; Mesons; Neutrino sources; Protons; Training;

  机译：Cherenkov计数器;宇宙​​射线设备;宇宙射线中微子;宇宙射线阵雨;高能宇宙射线相互作用;神经网络; 3层神经网络; ADC迹线; Auger水Cherenkov探测器; CORSIKA平台; Cyclone V FPGA; Levenberg-Marquardt算法;离线平台; Pierre Auger天文台; Pierre Auger表面探测器;人工神经网络;实验性天体物理学;介子引发粒子;神经网络算法;中微子事件;中微子起源的阵雨检测;原型前端板;真实的潘帕斯条件; tau中微子引发粒子;超高能中微子;人工神经网络;大气;检测器;介子;中微子源;质子;训练;