Deep Learning Exotic Hadrons

Abstract

We perform the first model independent analysis of experimental data using Deep Neural Networks to determine the nature of an exotic hadron. Specifically, we study the line shape of the $P_c(4312)$ 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.

arXiv commentManuscript: 5 pages, 5 figures, 1 table; Supplemental material: 7 pages, 7 figures, 1 table

References in corpus (24)

• Parton distributions for the LHC Run II
• Hadronic molecules
• The $XYZ$ states: experimental and theoretical status and perspectives
• Multiquark Resonances
• Non-Standard Heavy Mesons and Baryons, an Experimental Review
• Heavy-Quark QCD Exotica
• Observation of a narrow pentaquark state, $P_c(4312{)}^{+}$, and of two-peak structure of the $P_c(4450{)}^{+}$
• Threshold cusps and triangle singularities in hadronic reactions
• Multiquark States
• Neural Network Parametrization of Deep-Inelastic Structure Functions
• Interpretation of the LHCb $P_c$ States as Hadronic Molecules and Hints of a Narrow $P_c(4380)$
• An $a_0$ resonance in strongly coupled $\pi \eta$, $K\overline{K}$ scattering from lattice QCD
• Interpretation of the LHCb Pc(4312) Signal
• Variational Monte Carlo calculations of $\mathbf{A}\le 4$ nuclei with an artificial neural-network correlator ansatz
• Revisiting the nature of the $P_c$ pentaquarks
• Machine learning the deuteron
• Neural network parametrization of spectral functions from hadronic tau decays and determination of QCD vacuum condensates
• $P_c(4312{)}^{+}$, $P_c(4380{)}^{+}$, and $P_c(4457{)}^{+}$ as double triangle cusps
• A Genetic Algorithm Analysis of N* Resonances in $p(\gamma ,K^{+})\Lambda$ Reactions
• Model Selection for Pion Photoproduction
• Properties of Nucleon Resonances by means of a Genetic Algorithm
• Constraints on a possible dineutron state from pionless EFT
• Classifying Pole of Amplitude Using Deep Neural Network
• Model independent analysis of coupled-channel scattering: a deep learning approach

Cited by in corpus (7)

• Novel approaches in Hadron Spectroscopy
• Physics-Driven Learning for Inverse Problems in Quantum Chromodynamics
• Strongly Bound Dibaryon with Maximal Beauty Flavor from Lattice QCD
• Revealing the nature of hidden charm pentaquarks with machine learning
• Substructure of Multiquark Hadrons (Snowmass 2021 White Paper)
• Interpretation of near-threshold peaks using the method of independent S-matrix poles
• Learning Pole Structures of Hadronic States using Predictive Uncertainty Estimation