Author:
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
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.
Subject
Mathematical Physics,Instrumentation
Reference18 articles.
1. VLSI structures for track finding;Dell'Orso;Nucl. Instrum. Meth. A,1989
2. The CDF silicon vertex trigger;Ashmanskas;Nucl. Instrum. Meth. A,2004