RT Journal Article
T1 Deep learning exotic hadrons
A1 Ng, L.
A1 Bibrzycki, Ł.
A1 Nys, J.
A1 Fernández Ramírez, César
A1 Pilloni, A.
A1 Mathieu, Vincent
A1 Rasmusson, A. J.
A1 Szczepaniak, A. P.
AB 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.
PB APS Physics
SN 2470-0010
YR 2022
FD 2022-05-17
LK https://hdl.handle.net/20.500.14352/71951
UL https://hdl.handle.net/20.500.14352/71951
LA eng
NO Unión Europea. Horizonte 2020
NO Ministerio de Ciencia e Innovación (MICINN)
NO T
DS Docta Complutense
RD 9 abr 2025