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  • Letter
  • Open Access

Deep learning exotic hadrons

L. Ng1,*, Ł. Bibrzycki2,†, J. Nys3,‡, C. Fernández-Ramírez4,5,§, A. Pilloni6,7,8,∥, V. Mathieu9,10, A. J. Rasmusson11, and A. P. Szczepaniak11,12,13 (Joint Physics Analysis Center)

  • 1Department of Physics, Florida State University, Tallahassee, Florida 32306, USA
  • 2Pedagogical University of Krakow, 30-084 Kraków, Poland
  • 3Institute of Physics, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
  • 4Departamento de Física Interdisciplinar, Universidad Nacional de Educación a Distancia (UNED), Madrid E-28040, Spain
  • 5Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
  • 6Dipartimento di Scienze Matematiche e Informatiche, Scienze Fisiche e Scienze della Terra, Università degli Studi di Messina, Messina I-98166, Italy
  • 7INFN Sezione di Catania, Catania I-95123, Italy
  • 8INFN Sezione di Roma, Roma I-00185, Italy
  • 9Departament de Física Quàntica i Astrofísica and Institut de Ciències del Cosmos, Universitat de Barcelona, Martí i Franquès 1, E08028, Spain
  • 10Departamento de Física Teórica, Universidad Complutense de Madrid and IPARCOS, E-28040 Madrid, Spain
  • 11Department of Physics, Indiana University, Bloomington, Indiana 47405, USA
  • 12Theory Center, Thomas Jefferson National Accelerator Facility, Newport News, Virginia 23606, USA
  • 13Center for Exploration of Energy and Matter, Indiana University, Bloomington, Indiana 47403, USA

  • *ln16@my.fsu.edu
  • †lukasz.bibrzycki@up.krakow.pl
  • ‡jannes.nys@epfl.ch
  • §cesar@jlab.org
  • ∥alessandro.pilloni@unime.it
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Phys. Rev. D 105, L091501 – Published 17 May, 2022

DOI: https://doi.org/10.1103/PhysRevD.105.L091501

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.

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References (26)

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Phys. Rev. D 105, L091501– Published 17 May, 2022
  • Received 4 November 2021
  • Accepted 2 May 2022
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