An extension of Associative Memory approach to tracking with a drift-tube detector using timing information and its demonstration for HL-LHC ATLAS muon trigger: On behalf of the ATLAS Collaboration
Autor: | Yasuyuki Okumura, Yunjian He, Takafumi Kodama, Masaya Ishino, Masahiro Kuze, Yohei Yamaguchi |
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Rok vydání: | 2020 |
Předmět: |
Large Hadron Collider
Physics::Instrumentation and Detectors 010308 nuclear & particles physics Computer science Detector Real-time computing Iterative reconstruction Content-addressable memory Tracking (particle physics) 01 natural sciences 030218 nuclear medicine & medical imaging Set (abstract data type) 03 medical and health sciences 0302 clinical medicine 0103 physical sciences Pattern recognition (psychology) Benchmark (computing) |
Zdroj: | 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). |
Popis: | High-speed online pattern recognition has been a fundamental challenge for triggering in High Energy Physics (HEP) experiments. The Associative Memory (AM) approach has been developed and used in HEP experiments for online track-finding with silicon detectors. We intend to extend the AM approach to tracking with a drift-tube detector, using the drift-time as a “new dimension” of observables in addition to spatial information. Our benchmark study demonstrates the feasibility of the extended AM concept, aiming at the online muon reconstruction with the ATLAS Monitored Drift-Tube (MDT) detector for the Phase-II Level-0muon trigger system for High-Luminosity Large Hadron Collider. The online muon reconstruction will consist of two parts: (1) a fast track-segment finding, and (2) the following track reconstruction to estimate the momentum of the muons. It is found that timing information can be integrated into the AM approach in a natural way, and the AM approach can fit the needs for the fast track segment finding. In terms of hardware specifications expected for the Phase-II Level-0 muon trigger system, an optimal pattern training scheme is developed to prepare an effective set of AM patterns that provide high efficiency in the track-segment finding while keeping a good resolution. Based on the system-level design of electronics, an optimal algorithm chain has been developed to minimise the latency for the track segment finding. The detailed design and performance study shows that the AM approach has the capability of a high-speed and high-performance track-finding with drift-tube detectors. |
Databáze: | OpenAIRE |
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