Design and Performance of the ALICE Muon Trigger System

2006 ◽  
Vol 158 ◽  
pp. 21-24 ◽  
Author(s):  
R. Arnaldi ◽  
A. Baldit ◽  
V. Barret ◽  
N. Bastid ◽  
G. Blanchard ◽  
...  
2001 ◽  
Vol 16 (supp01c) ◽  
pp. 1172-1174
Author(s):  
◽  
KENNETH BLOOM

In the upcoming Fermilab Tevatron collider run, [Formula: see text] collisions will occur at 132 ns intervals, and the CDF II trigger system requires that information about drift chamber tracks be provided within 2.2 μs of every collision, so that tracking information can be used in conjunction with data from other detector components to trigger on physics objects with little background. We have developed a fast online track processor for locating high-momentum tracks in the chamber. The design is highly parallel, and is implemented in programmable logic devices. We describe the design of the system and performance tests.


2017 ◽  
Author(s):  
Dinyar Rabady ◽  
Carlo Battilana ◽  
Roberto Carlin ◽  
Giuseppe Codispoti ◽  
Marco Dallavalle ◽  
...  
Keyword(s):  

2020 ◽  
Vol 35 (34n35) ◽  
pp. 2044008
Author(s):  
Carlos Moreno Martínez

During Run 2 (2015–2018) the Large Hadron Collider has provided, at the World’s highest energy frontier, proton–proton collisions to the ATLAS experiment with high instantaneous luminosity (up to [Formula: see text]), placing stringent operational and physics requirements on the ATLAS trigger system in order to reduce the 40 MHz collision rate to a manageable event storage rate of 1 kHz, while not rejecting interesting collisions. The Level-1 trigger is the first rate-reducing step in the ATLAS trigger system with an output rate of up to 100 kHz and decision latency of less than 2.5 [Formula: see text]s. In Run 2, an important role was played by the Level-1 Topological Processor (L1Topo). This innovative system consists of two blades designed in AdvancedTCA form factor, mounting four individual state-of-the-art processors, and providing high input bandwidth and low latency data processing. Up to 128 topological trigger algorithms can be implemented to select interesting events by applying kinematic and angular requirements on electromagnetic clusters, hadronic jets, muons and total energy reconstructed in the ATLAS apparatus. This resulted in a significantly improved background rejection and enhanced acceptance of physics signal events, despite the increasing luminosity. The L1Topo system has become more and more important for physics analyses making use of low energy objects, commonly present in the Heavy Flavor or Higgs physics events, for example. An overview of the L1Topo architecture, simulation and performance results during Run 2 is presented alongside with upgrade plans for the L1Topo system to be installed for the future Run 3 data taking period.


2006 ◽  
Vol 53 (2) ◽  
pp. 500-505
Author(s):  
S. Armstrong ◽  
K.A. Assamagan ◽  
J.T.M. Baines ◽  
C.P. Bee ◽  
M. Bellomo ◽  
...  

Author(s):  
John T. Anderson ◽  
Karen Byrum ◽  
Gary Drake ◽  
Frank Krennrich ◽  
Andrew Kreps ◽  
...  

2021 ◽  
Vol 251 ◽  
pp. 04031
Author(s):  
Rustem Ospanov ◽  
Changqing Feng ◽  
Wenhao Dong ◽  
Wenhao Feng ◽  
Shining Yang

Effective selection of muon candidates is the cornerstone of the LHC physics programme. The ATLAS experiment uses a two-level trigger system for real-time selection of interesting collision events. The first-level hardware trigger system uses the Resistive Plate Chamber detector (RPC) for selecting muon candidates in the central (barrel) region of the detector. With the planned upgrades, the entirely new FPGA-based muon trigger system will be installed in 2025-2026. In this paper, neural network regression models are studied for potential applications in the new RPC trigger system. A simple simulation model of the current detector is developed for training and testing neural network regression models. Effects from additional cluster hits and noise hits are evaluated. Efficiency of selecting muon candidates is estimated as a function of the transverse muon momentum. Several models are evaluated and their performance is compared to that of the current detector, showing promising potential to improve on current algorithms for the ATLAS Phase-II barrel muon trigger upgrade.


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