Deep learning exotic hadrons

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Ng, L. and Bibrzycki, Ł. and Nys, J. and Fernández Ramírez, C. and Pilloni, A. and Mathieu, V. and Rasmusson, A. J. and Szczepaniak, A. P. (2022) Deep learning exotic hadrons. Physical Review D, 105 (9). ISSN 2470-0010

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Official URL: https://doi.org/10.1103/PhysRevD.105.L091501



Abstract

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.


Item Type:Article
Subjects:Sciences > Physics > Particles
ID Code:74477
Deposited On:08 Sep 2022 14:28
Last Modified:09 Sep 2022 08:23

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