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.
Machine learning exotic hadrons
Pilloni A.;
2024-01-01
Abstract
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.File in questo prodotto:
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