Publication | Open Access
Deep learning exotic hadrons
17
Citations
22
References
2022
Year
Deep Neural NetworksFirst Amplitude AnalysisEngineeringPhysicsTheoretical High-energy PhysicNatural SciencesHadron PhysicParticle PhysicsExotic StateComputer ScienceLepton-nucleon ScatteringDark MatterDeep LearningVirtual StateHadron Physics
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 ${P}_{c}(4312)$ 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.
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