Online selection of short-lived particles on many-core computer architectures in the CBM experiment at FAIR

Modern experiments in heavy ion collisions operate with huge data rates that can not be fully stored on the currently available storage devices. Therefore the data flow should be reduced by selecting those collisions tha
Modern experiments in heavy ion collisions operate with huge data rates that can not be fully stored on the currently available storage devices. Therefore the data flow should be reduced by selecting those collisions that potentially carry the information of the physics interest. The future CBM experiment will have no simple criteria for selecting such collisions and requires the full online reconstruction of the collision topology including reconstruction of short-lived particles.
In this work the KF Particle Finder package for online reconstruction and selection of short-lived particles is proposed and developed. It reconstructs more than 70 decays, covering signals from all the physics cases of the CBM experiment: strange particles, strange resonances, hypernuclei, low mass vector mesons, charmonium, and open-charm particles.
The package is based on the Kalman filter method providing a full set of the particle parameters together with their errors including position, momentum, mass, energy, lifetime, etc. It shows a high quality of the reconstructed particles, high efficiencies, and high signal to background ratios.
The KF Particle Finder is extremely fast for achieving the reconstruction speed of 1.5 ms per minimum-bias AuAu collision at 25 AGeV beam energy on single CPU core. It is fully vectorized and parallelized and shows a strong linear scalability on the many-core architectures of up to 80 cores. It also scales within the First Level Event Selection package on the many-core clusters up to 3200 cores.
The developed KF Particle Finder package is a universal platform for short- lived particle reconstruction, physics analysis and online selection.
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Metadaten
Author:Maksym Zyzak
URN:urn:nbn:de:hebis:30:3-414288
Place of publication:Frankfurt am Main
Referee:Ivan Kisel, Volker Lindenstruth
Advisor:Ivan Kisel
Document Type:Doctoral Thesis
Language:English
Date of Publication (online):2016/08/17
Year of first Publication:2015
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Granting Institution:Johann Wolfgang Goethe-Universität
Date of final exam:2016/07/07
Release Date:2016/08/17
Tag:High energy physics; Kalman filter; Many-core computer architectures; Parallel and SIMD calculations; Short-lived particles
Pagenumber:165
HeBIS PPN:385874006
Institutes:Informatik
Dewey Decimal Classification:004 Datenverarbeitung; Informatik
Sammlungen:Universitätspublikationen
Licence (German):License Logo Veröffentlichungsvertrag für Publikationen

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