JEDI-net: a jet identification algorithm based on interaction networks
| Autor: | Javier Duarte, Thong Q. Nguyen, Olmo Cerri, Maria Spiropulu, Harvey Newman, Jean-Roch Vlimant, Aidana Serikova, Avikar Periwal, Eric A. Moreno, Maurizio Pierini |
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| Rok vydání: | 2020 |
| Předmět: |
Physics and Astronomy (miscellaneous)
FOS: Physical sciences lcsh:Astrophysics 01 natural sciences High Energy Physics - Experiment Set (abstract data type) High Energy Physics - Experiment (hep-ex) High Energy Physics - Phenomenology (hep-ph) lcsh:QB460-466 0103 physical sciences lcsh:Nuclear and particle physics. Atomic energy. Radioactivity 010306 general physics Representation (mathematics) Engineering (miscellaneous) Particle Physics - Phenomenology Physics Jet (fluid) Large Hadron Collider hep-ex 010308 nuclear & particles physics High Energy Physics::Phenomenology hep-ph Net (mathematics) Hadronization Identification (information) High Energy Physics - Phenomenology Quark–gluon plasma lcsh:QC770-798 High Energy Physics::Experiment Algorithm Particle Physics - Experiment |
| Zdroj: | The European Physical Journal C European Physical Journal European Physical Journal C: Particles and Fields, Vol 80, Iss 1, Pp 1-15 (2020) |
| ISSN: | 1434-6044 |
| DOI: | 10.1140/epjc/s10052-020-7608-4 |
| Popis: | We investigate the performance of a jet identification algorithm based on interaction networks (JEDI-net) to identify all-hadronic decays of high-momentum heavy particles produced at the LHC and distinguish them from ordinary jets originating from the hadronization of quarks and gluons. The jet dynamics are described as a set of one-to-one interactions between the jet constituents. Based on a representation learned from these interactions, the jet is associated to one of the considered categories. Unlike other architectures, the JEDI-net models achieve their performance without special handling of the sparse input jet representation, extensive pre-processing, particle ordering, or specific assumptions regarding the underlying detector geometry. The presented models give better results with less model parameters, offering interesting prospects for LHC applications. 16 pages, 9 figures, 7 tables |
| Databáze: | OpenAIRE |
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