Charged particle tracking in real-time using a full-mesh data delivery architecture and associative memory techniques

• Published in: Journal of instrumentation Vol. 17; no. 12; p. P12002
• Main Authors: Ajuha, Sudha, Akira Shinoda, Ailton, Arruda Ramalho, Lucas, Baulieu, Guillaume, Boudoul, Gaelle, Casarsa, Massimo, Cascadan, Andre, Clement, Emyr, Costa de Paiva, Thiago, Das, Souvik, Dutta, Suchandra, Eusebi, Ricardo, Fedi, Giacomo, Finotti Ferreira, Vitor, Hahn, Kristian, Hu, Zhen, Jindariani, Sergo, Konigsberg, Jacobo, Liu, Tiehui, Fu Low, Jia, MacDonald, Emily, Olsen, Jamieson, Palla, Fabrizio, Pozzobon, Nicola, Rathjens, Denis, Ristori, Luciano, Rossin, Roberto, Sung, Kevin, Tran, Nhan, Trovato, Marco, Ulmer, Keith, Vaz, Mario, Viret, Sebastien, Wu, Jin-Yuan, Xu, Zijun, Zorzetti, Silvia
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.12.2022; Institute of Physics (IOP)
• Subjects: Algorithms; Associative memory; Charged particles; data acquisition concepts; Finite element method; hardware; High Energy Physics - Experiment; Large Hadron Collider; Memory devices; online farms and online filtering; OTHER INSTRUMENTATION; Particle collisions; Particle tracking; Pattern recognition; Physics; PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; Reconstruction; software; Time measurement; trigger algorithms; trigger concepts and systems; efficiency; performance; density; momentum resolution; FPGA; charged particle; trigger; integrated circuit; track data analysis; trajectory; hardware; tracking detector
• ISSN: 1748-0221; 1748-0221
• DOI: 10.1088/1748-0221/17/12/P12002

Abstract We present a flexible and scalable approach to address the challenges of charged particle track reconstruction in real-time event filters (Level-1 triggers) in collider physics experiments. The method described here is based on a full-mesh architecture for data distribution and relies on the Associative Memory approach to implement a pattern recognition algorithm that quickly identifies and organizes hits associated to trajectories of particles originating from particle collisions. We describe a successful implementation of a demonstration system composed of several innovative hardware and algorithmic elements. The implementation of a full-size system relies on the assumption that an Associative Memory device with the sufficient pattern density becomes available in the future, either through a dedicated ASIC or a modern FPGA. We demonstrate excellent performance in terms of track reconstruction efficiency, purity, momentum resolution, and processing time measured with data from a simulated LHC-like tracking detector.