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

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 th...

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Published inJournal 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
LanguageEnglish
Published Bristol IOP Publishing 01.12.2022
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Abstract 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.
AbstractList We present a flexible and scalable approach to address thechallenges of charged particle track reconstruction in real-timeevent filters (Level-1 triggers) in collider physicsexperiments. The method described here is based on a full-mesharchitecture for data distribution and relies on the AssociativeMemory approach to implement a pattern recognition algorithm thatquickly identifies and organizes hits associated to trajectories ofparticles originating from particle collisions. We describe asuccessful implementation of a demonstration system composed ofseveral innovative hardware and algorithmic elements. Theimplementation of a full-size system relies on the assumption thatan Associative Memory device with the sufficient pattern densitybecomes available in the future, either through a dedicated ASIC ora modern FPGA. We demonstrate excellent performance in terms oftrack reconstruction efficiency, purity, momentum resolution, andprocessing time measured with data from a simulated LHC-liketracking detector.
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.
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.
Author Vaz, Mario
Fedi, Giacomo
Olsen, Jamieson
Akira Shinoda, Ailton
Hu, Zhen
Tran, Nhan
Wu, Jin-Yuan
Zorzetti, Silvia
Costa de Paiva, Thiago
Konigsberg, Jacobo
Palla, Fabrizio
Ristori, Luciano
Jindariani, Sergo
Cascadan, Andre
Finotti Ferreira, Vitor
Boudoul, Gaelle
Xu, Zijun
MacDonald, Emily
Clement, Emyr
Sung, Kevin
Das, Souvik
Rossin, Roberto
Fu Low, Jia
Liu, Tiehui
Arruda Ramalho, Lucas
Dutta, Suchandra
Ajuha, Sudha
Rathjens, Denis
Casarsa, Massimo
Ulmer, Keith
Viret, Sebastien
Pozzobon, Nicola
Baulieu, Guillaume
Eusebi, Ricardo
Hahn, Kristian
Trovato, Marco
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Issue 12
Keywords efficiency
performance
density
momentum resolution
FPGA
charged particle
trigger
integrated circuit
track data analysis
trajectory
hardware
tracking detector
Language English
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Snippet Abstract We present a flexible and scalable approach to address the challenges of charged particle track reconstruction in real-time event filters (Level-1...
We present a flexible and scalable approach to address thechallenges of charged particle track reconstruction in real-timeevent filters (Level-1 triggers) in...
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...
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StartPage P12002
SubjectTerms 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
Title Charged particle tracking in real-time using a full-mesh data delivery architecture and associative memory techniques
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