Charged particle tracking in real-time using a full-mesh data delivery architecture and associative memory techniques. (1st December 2022) - 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; et al.
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.