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

• Autor(a) principal: Ajuha, Sudha [UNESP]
• Data de Publicação: 2022
• Outros Autores: Akira Shinoda, Ailton [UNESP], Arruda Ramalho, Lucas [UNESP], Baulieu, Guillaume, Boudoul, Gaelle, Casarsa, Massimo, Cascadan, Andre [UNESP], Clement, Emyr, Costa de Paiva, Thiago [UNESP], Das, Souvik, Dutta, Suchandra, Eusebi, Ricardo, Fedi, Giacomo, Finotti Ferreira, Vitor [UNESP], 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 [UNESP], Viret, Sebastien, Wu, Jin-Yuan, Xu, Zijun, Zorzetti, Silvia
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1088/1748-0221/17/12/P12002; http://hdl.handle.net/11449/246469
• topic: Data acquisition concepts; Online farms and online filtering; Trigger algorithms; Trigger concepts and systems (hardware and software)

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.