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FPGA-based muon shower identification and graph neural network tracking algorithms for HL-LHC triggers

Estrada, Daniel et al.
arXiv (All) · Papers
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high-energy-physics-experimentinstrumentation-and-detectors
This work presents two hardware-accelerated strategies for the upgrade of the CMS Level-1 Trigger (L1T) to target efficiency losses due to highly energetic radiating muons and unconventional physics signatures, such as Long-Lived Particles (LLPs). Operating directly on low-level detector hits, the f
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