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FPGA-based Real-time Charged Particle Trajectory Reconstruction at the Large Hadron Collider
The upgrades of the Compact Muon Solenoid particle physics experiment at CERN's Large Hadron Collider provide a major challenge for the real-time collision data selection. This paper presents a novel approach to pattern recognition and charged particle trajectory reconstruction using an all-FP...
Autores principales: | , , , , , , , , , , , , , , , |
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Lenguaje: | eng |
Publicado: |
2017
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2271094 |
Sumario: | The upgrades of the Compact Muon Solenoid particle physics
experiment at CERN's Large Hadron Collider provide a major challenge
for the real-time collision data selection. This paper presents a
novel approach to pattern recognition and charged particle
trajectory reconstruction using an all-FPGA solution. The challenges
include a large input data rate of about 20 to 40~Tbps, processing a
new batch of input data every 25~ns, each consisting of
about 10,000 precise position measurements of particles (`stubs'),
perform the pattern recognition on these stubs to find the
trajectories, and produce the list of parameters describing these
trajectories within 4~$\mu$s. A proposed
solution to this problem is described, in particular, the implementation of the
pattern recognition and particle trajectory determination using an
all-FPGA system. The results of an end-to-end demonstrator system
based on Xilinx Virtex-7 FPGAs that meets timing and performance
requirements are presented. |
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