Abstract
The high instantaneous luminosities expected following the upgrade of the Large Hadron Collider (LHC) to the High-Luminosity LHC (HL-LHC) pose major experimental challenges for the CMS experiment. A central component to allow efficient operation under these conditions is the reconstruction of charged particle trajectories and their inclusion in the hardware-based trigger system. There are many challenges involved in achieving this: a large input data rate of about 20-40 Tb/s processing a new batch of input data every 25 ns, each consisting of about 15,000 precise position measurements and rough transverse momentum measurements of particles ("stubs"); performing the pattern recognition on these stubs to find the trajectories; and producing the list of trajectory parameters within 4 μs. This paper describes a proposed solution to this problem, specifically, it presents a novel approach to pattern recognition and charged particle trajectory reconstruction using an all-FPGA solution. The results of an end-to-end demonstrator system, based on Xilinx Virtex-7 FPGAs, that meets timing and performance requirements are presented along with a further improved, optimized version of the algorithm together with its corresponding expected performance.
Original language | English (US) |
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Article number | P06024 |
Journal | Journal of Instrumentation |
Volume | 15 |
Issue number | 6 |
DOIs | |
State | Published - Jun 2020 |
Keywords
- Particle tracking detectors (Solid-state detectors)
- Pattern recognition
- Trigger algorithms
- Trigger concepts and systems (hardware and software)
- calibration and fitting methods
- cluster finding
ASJC Scopus subject areas
- Instrumentation
- Mathematical Physics