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research article

Machine learning exotic hadrons

Ng, L.
•
Bibrzycki, None
•
Nys, J.  
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2024
Nuovo Cimento della Societa Italiana di Fisica C

We show that a neural network trained with synthetic differential intensities calculated with scattering length approximated amplitudes classifies the Pc(4312)+ signal as a virtual state located at the 4th Riemann sheet with very high certainty. This is in line with the results of other analyses but surpasses them by providing a simultaneous evaluation of probabilities of competing scenarios, like, e.g., the interpretation as a bound state. Using the Shapley Additive Explanations we identified the energy bins which are key for the physical interpretation.

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Type
research article
DOI
10.1393/ncc/i2024-24207-8
Scopus ID

2-s2.0-85198269563

Author(s)
Ng, L.

College of Arts and Sciences

Bibrzycki, None

AGH University of Krakow

Nys, J.  

École Polytechnique Fédérale de Lausanne

Fernández-Ramírez, C.

Universidad Nacional de Educacion a Distancia

Pilloni, A.

Università degli Studi di Messina

Mathieu, V.

Universitat de Barcelona

Rasmusson, A. J.

Indiana University Bloomington

Szczepaniak, A. P.

Jefferson Lab Theory Center

Date Issued

2024

Published in
Nuovo Cimento della Societa Italiana di Fisica C
Volume

47

Issue

4

Article Number

207

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CQSL  
FunderFunding(s)Grant NumberGrant URL

Marie SkłodowskaCurie

European Union's Horizon 2020 research and innovation programme

European Union’s Horizon 2020 research and innovation programme

754496

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Available on Infoscience
January 24, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/243368
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