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October 14, 2024 to November 15, 2024
YITP
Asia/Tokyo timezone

Machine learning on exotic hadrons

Oct 15, 2024, 3:30 PM
1h
Panasonic Auditorium, Yukawa Hall (YITP)

Panasonic Auditorium, Yukawa Hall

YITP

1st and 2nd weeks (Hadron structure and interactions) Seminar (1,2 week)

Speaker

Qian Wang (South China Normal University)

Description

We study the nature of the hidden charm pentaquarks, i.e. the Pc(4312), Pc(4440) and Pc(4457), with a neural network approach in pionless effective field theory. In this framework, the normal fitting approach cannot distinguish the quantum numbers of the Pc(4440) and Pc(4457). In contrast to that, the neural network-based approach can discriminate them. In addition, we also illustrate the role of each experimental data bin of the invariant J/ψp mass distribution on the underlying physics in both neural network and fitting methods. Their similarities and differences demonstrate that neural network methods can use data information more effectively and directly. This study provides more insights about how the neural network-based approach predicts the nature of exotic states from the mass spectrum.

Primary authors

Mr Jifeng Hu (South China Normal University) Qian Wang (South China Normal University) Prof. Ulf-G. Meissner (Bonn University)

Presentation materials