Real-time pattern recognition with FPGA at LHCb, an

The LHCb collaboration is planning an upgrade (LHCb “Upgrade- II”) to collect data during Run 5 at an instantaneous luminosity an order of magnitude larger than the current one (Run 3). LHCb relies on a complete realtime reconstruction of all collision events at LHC-Point 8, which will have to cope with both the luminosity increase and the introduction of correspondingly more granular and complex detectors. After an intensive R&D programme, LHCb approved a FPGA-based system to pre-reconstruct tracks in the SciFi detector at readout level during Run 4, as an intermediate step towards a system that could be extended to other tracking detectors in the future. It is based on the “artificial retina”, an extremely parallel architecture. Using simulated data, the performance of a hardware demonstrator of this architecture has been tested as a function of instantaneous luminosity and system size, and was found to have O(n) complexity, which is a crucial feature for high luminosity applications.

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Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-10-07
DOI
https://doi.org/10.1051/epjconf/202533701311/pdf
Primary Topic
Particle Detector Development and Performance
Type
article
Field-Weighted Citation Impact
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article

Real-time pattern recognition with FPGA at LHCb, an

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Springer Link (Chiba Institute of Technology)
Particle Detector Development and Performance
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Real-time pattern recognition with FPGA at LHCb, an

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article en

Abstract

The LHCb collaboration is planning an upgrade (LHCb “Upgrade- II”) to collect data during Run 5 at an instantaneous luminosity an order of magnitude larger than the current one (Run 3). LHCb relies on a complete realtime reconstruction of all collision events at LHC-Point 8, which will have to cope with both the luminosity increase and the introduction of correspondingly more granular and complex detectors. After an intensive R&D programme, LHCb approved a FPGA-based system to pre-reconstruct tracks in the SciFi detector at readout level during Run 4, as an intermediate step towards a system that could be extended to other tracking detectors in the future. It is based on the “artificial retina”, an extremely parallel architecture. Using simulated data, the performance of a hardware demonstrator of this architecture has been tested as a function of instantaneous luminosity and system size, and was found to have O(n) complexity, which is a crucial feature for high luminosity applications.

Springer Link (Chiba Institute of Technology)
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Particle Detector Development and Performance
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