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 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.
Keywords
Cite
@article{arxiv.2210.02489,
title = {Charged Particle Tracking in Real-Time Using a Full-Mesh Data Delivery Architecture and Associative Memory Techniques},
author = {Sudha Ajuha and Ailton Akira Shinoda and Lucas Arruda Ramalho and Guillaume Baulieu and Gaelle Boudoul and Massimo Casarsa and Andre Cascadan and Emyr Clement and Thiago Costa de Paiva and Souvik Das and Suchandra Dutta and Ricardo Eusebi and Giacomo Fedi and Vitor Finotti Ferreira and Kristian Hahn and Zhen Hu and Sergo Jindariani and Jacobo Konigsberg and Tiehui Liu and Jia Fu Low and Emily MacDonald and Jamieson Olsen and Fabrizio Palla and Nicola Pozzobon and Denis Rathjens and Luciano Ristori and Roberto Rossin and Kevin Sung and Nhan Tran and Marco Trovato and Keith Ulmer and Mario Vaz and Sebastien Viret and Jin-Yuan Wu and Zijun Xu and Silvia Zorzetti},
journal= {arXiv preprint arXiv:2210.02489},
year = {2022}
}