Reconstruction of Long-Lived Particles in LHCb CERN Project by Data Analysis and Computational Intelligence Methods View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2021-06-09

AUTHORS

Grzegorz Gołaszewski , Piotr Kulczycki , Tomasz Szumlak , Szymon Łukasik

ABSTRACT

LHCb at CERN, Geneva is a world-leading high energy physics experiment dedicated to searching for New Physics phenomena. The experiment is undergoing a major upgrade and will rely entirely on a flexible software trigger to process the data in real-time. In this paper a novel approach to reconstructing (detecting) long-lived particles using a new pattern matching procedure is presented. A large simulated data sample is applied to build an initial track pattern by an unsupervised approach. The pattern is then updated and verified by real collision data. As a performance index, the difference between density estimated by nonparametric methods using experimental streaming data and the one based on theoretical premises is used. Fuzzy clustering methods are applied for a pattern size reduction. A final decision is made in a real-time regime with rigorous time boundaries. More... »

PAGES

293-300

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-77961-0_25

DOI

http://dx.doi.org/10.1007/978-3-030-77961-0_25

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1138781675


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