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Real Time Data Analysis With the ATLAS Trigger at the LHC in Run-2.
- Source :
-
IEEE Transactions on Nuclear Science . Sep2020, Vol. 67 Issue 9, p2128-2135. 8p. - Publication Year :
- 2020
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Abstract
- The trigger selection capabilities of the ATLAS detector have been significantly enhanced for the Large Hadron Collider (LHC) Run-2 in order to cope with the higher event rates and with a large number of simultaneous interactions (pile-up) per proton–proton bunch crossing. A new hardware system, designed to analyze real-time event-topologies at level-1, came to full use in 2017. A hardware-based track reconstruction system, expected to be used real time in run-3, is designed to provide track information to the high-level software trigger at its full input rate. The high-level trigger (HLT) selections largely rely on off-line-like reconstruction techniques and in some cases multivariate analysis methods. Despite the sudden change in LHC operations during the second half of 2017, which caused an increase in pile-up and, therefore, also in CPU usage of the trigger algorithms, the set of triggers (so-called trigger menu) running online has undergone only minor modifications thanks to the robustness and redundancy of the trigger system and the use of a leveling luminosity scheme in agreement with LHC and other experiments. This article gives a brief yet comprehensive review of the real-time performance of the ATLAS trigger system in 2017. Considerations will be presented on the most relevant parameters of the trigger (efficiency to collect signal and output data rate) and details on some aspects of the algorithms which are run real time on the HLT CPU farm will be presented. [ABSTRACT FROM AUTHOR]
- Subjects :
- *LARGE Hadron Collider
*DATA analysis
*ATLASES
*MULTIVARIATE analysis
Subjects
Details
- Language :
- English
- ISSN :
- 00189499
- Volume :
- 67
- Issue :
- 9
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Nuclear Science
- Publication Type :
- Academic Journal
- Accession number :
- 146012840
- Full Text :
- https://doi.org/10.1109/TNS.2020.2967761