Fast Muon Tracking with Machine Learning Implemented in FPGA

In this work, we present a new approach for fast tracking on multiwire proportional chambers with neural networks. The tracking networks are developed and adapted for the first-level trigger at hadron collider experiments. We use Monte Carlo samples generated by Geant4 with a custom muon chamber, wh...

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Veröffentlicht in:	arXiv.org 2022-11
Hauptverfasser:	Chang, Sun, Nakajima, Takumi, Mitsumori, Yuki, Horii, Yasuyuki, Tomoto, Makoto
Format:	Artikel
Sprache:	eng
Schlagworte:	Angular resolution Artificial neural networks Chambers Field programmable gate arrays Firmware Hardware description languages Machine learning Multilayer perceptrons Muons Network latency Neural networks Performance evaluation Physics - Instrumentation and Detectors Radiation counters Tracking networks
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