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Barrel muon track reconstruction with deep learning for Level-1 trigger data scouting in the CMS experiment

Fabio Cufino · CERN

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About

The study uses the Run-3 data scouting demonstrator to refine muon track reconstruction in the barrel region at the Level-1 trigger. By applying machine learning algorithms designed for FPGA deployment, the study improves online reconstruction of muon parameters using stub-only data..

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The talk

  1. Barrel muon track reconstruction with deep learning for Level-1 trigger data scouting in the CMS experiment 2024-08-13 · 9 min · CERN's player

Credits and licence

Institution
CERN
Department
CERN openlab Summer Student Programme 2024
Speaker
Fabio Cufino
Year
2024
Language
English
Source
CERN
Licence
CERN, as CERN states it. CERN's terms
Attribution
© CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
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