JEDI-net: a jet identification algorithm based on interaction networks
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 dyna...
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Veröffentlicht in: | The European physical journal. C, Particles and fields Particles and fields, 2020-01, Vol.80 (1) |
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Hauptverfasser: | , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 1434-6044 |