Revealing the nature of hidden charm pentaquarks with machine learning
| Autor: | Zhang, Zhenyu, Liu, Jiahao, Hu, Jifeng, Wang, Qian, Meißner, Ulf-G. |
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| Rok vydání: | 2023 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1016/j.scib.2023.04.018 |
| Popis: | We study the nature of the hidden charm pentaquarks, i.e. the $P_c(4312)$, $P_c(4440)$ and $P_c(4457)$, with a neural network approach in pionless effective field theory. In this framework, the normal $\chi^2$ fitting approach cannot distinguish the quantum numbers of the $P_c(4440)$ and $P_c(4457)$. 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 $J/\psi p$ 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. Comment: accepted by Science Bulletin |
| Databáze: | arXiv |
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