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Deep Learning Exotic Hadrons

Academic Article
Publication Date:
2022
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.
Iris type:
14.a.1 Articolo su rivista
Keywords:
High Energy Physics - Phenomenology; High Energy Physics - Phenomenology; High Energy Physics - Experiment; Nuclear Theory
List of contributors:
Ng, L.; Bibrzycki, L.; Nys, J.; Fernandez-Ramirez, C.; Pilloni, A.; Mathieu, V.; Rasmusson, A. J.; Szczepaniak, A. P.
Authors of the University:
JLab
PILLONI Alessandro
Handle:
https://iris.unime.it/handle/11570/3232151
Published in:
PHYSICAL REVIEW D
Journal
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