Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/192647
Title: Deep learning exotic hadrons
Author: Ng, L.
Bibrzycki, Ł
Nys, J.
Fernandez-Ramirez, César
Pillon, Alessandro
Mathieu, Vicent
Rasmusson, A. J.
Szczepaniak, Adam Pawel
Keywords: Quarks
Partícules (Matèria)
Quarks
Particles
Issue Date: 17-May-2022
Publisher: American Physical Society
Abstract: We 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.
Note: Reproducció del document publicat a: https://doi.org/10.1103/PhysRevD.105.L091501
It is part of: Physical Review D, 2022, vol. 105, num. 9, p. L091501-1-L091501-6
URI: http://hdl.handle.net/2445/192647
Related resource: https://doi.org/10.1103/PhysRevD.105.L091501
ISSN: 1550-7998
Appears in Collections:Articles publicats en revistes (Física Quàntica i Astrofísica)

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