Deep learning exotic hadrons

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dc.contributor.authorNg, L.
dc.contributor.authorBibrzycki, Ł
dc.contributor.authorNys, J.
dc.contributor.authorFernandez-Ramirez, César
dc.contributor.authorPillon, Alessandro
dc.contributor.authorMathieu, Vicent
dc.contributor.authorRasmusson, A. J.
dc.contributor.authorSzczepaniak, Adam Pawel
dc.date.accessioned2023-01-26T12:14:11Z
dc.date.available2023-01-26T12:14:11Z
dc.date.issued2022-05-17
dc.date.updated2023-01-26T12:14:12Z
dc.description.abstractWe perform the first amplitude analysis of experimental data using deep neural networks to determine the nature of an exotic hadron. Specifically, we study the line shape of the Pc(4312) signal reported by the LHCb collaboration, and we find that its most likely interpretation is that of a virtual state. This method can be applied to other near-threshold resonance candidates.
dc.format.extent6 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec725660
dc.identifier.issn1550-7998
dc.identifier.urihttps://hdl.handle.net/2445/192647
dc.language.isoeng
dc.publisherAmerican Physical Society
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1103/PhysRevD.105.L091501
dc.relation.ispartofPhysical Review D, 2022, vol. 105, num. 9, p. L091501-1-L091501-6
dc.relation.urihttps://doi.org/10.1103/PhysRevD.105.L091501
dc.rights(c) American Physical Society, 2022
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.sourceArticles publicats en revistes (Física Quàntica i Astrofísica)
dc.subject.classificationQuarks
dc.subject.classificationPartícules (Matèria)
dc.subject.otherQuarks
dc.subject.otherParticles
dc.titleDeep learning exotic hadrons
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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