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Comparison of two hardware-based hit filtering methods for trackers in high-pileup environments
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy. Univ Grenoble Alpes, LPSC, 53 Ave Martyrs, F-38026 Grenoble, France.
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, High Energy Physics.
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, High Energy Physics.
2018 (English)In: Journal of Instrumentation, ISSN 1748-0221, E-ISSN 1748-0221, Vol. 13, article id P04019Article in journal (Refereed) Published
Abstract [en]

As experiments in high energy physics aim to measure increasingly rare processes, the experiments continually strive to increase the expected signal yields. In the case of the High Luminosity upgrade of the LHC, the luminosity is raised by increasing the number of simultaneous proton-proton interactions, so-called pileup. This increases the expected yields of signal and background processes alike. The signal is embedded in a large background of processes that mimic that of signal events. It is therefore imperative for the experiments to develop new triggering methods to effectively distinguish the interesting events from the background.& para;& para;We present a comparison of two methods for filtering detector hits to be used for triggering on particle tracks: one based on a pattern matching technique using Associative Memory (AM) chips and the other based on the Hough transform. Their efficiency and hit rejection are evaluated for proton-proton collisions with varying amounts of pileup using a simulation of a generic silicon tracking detector. It is found that, while both methods are feasible options for a track trigger with single muon efficiencies around 98-99%, the AM based pattern matching produces a lower number of hit combinations with respect to the Hough transform whilst keeping more of the true signal hits. We also present the effect on the two methods of increasing the amount of support material in the detector and of introducing inefficiencies by deactivating detector modules. The increased support material has negligable effects on the efficiency for both methods, while dropping 5% (10%) of the available modules decreases the efficiency to about 95% (87%) for both methods, irrespective of the amount of pileup.

Place, publisher, year, edition, pages
2018. Vol. 13, article id P04019
Keywords [en]
Data reduction methods, Online farms and online filtering, Trigger algorithms, Particle tracking detectors
National Category
Accelerator Physics and Instrumentation
Identifiers
URN: urn:nbn:se:uu:diva-353216DOI: 10.1088/1748-0221/13/04/P04019ISI: 000430374800001OAI: oai:DiVA.org:uu-353216DiVA, id: diva2:1217340
Available from: 2018-06-13 Created: 2018-06-13 Last updated: 2018-06-13Bibliographically approved

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Mårtensson, MikaelBrenner, Richard

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