Guangdong Provincial Key Laboratory of Nuclear Science, Institute of Quantum Matter, South China Normal University, Guangzhou 510006, China; Guangdong-Hong Kong Joint Laboratory of Quantum Matter, Southern Nuclear Science Computing Center, South China Normal University, Guangzhou 510006, China.
Guangdong Provincial Key Laboratory of Nuclear Science, Institute of Quantum Matter, South China Normal University, Guangzhou 510006, China; Guangdong-Hong Kong Joint Laboratory of Quantum Matter, Southern Nuclear Science Computing Center, South China Normal University, Guangzhou 510006, China.
Sci Bull (Beijing). 2023 May 30;68(10):981-989. doi: 10.1016/j.scib.2023.04.018. Epub 2023 Apr 20.
We study the nature of the hidden charm pentaquarks, i.e., the P4312,P4440 and P(4457), with a neural network approach in pionless effective field theory. In this framework, the normal χ fitting approach cannot distinguish the quantum numbers of the P(4440) and P(4457). In contrast to that, the neural network-based approach can discriminate them, which still cannot be seen as a proof of the spin of the states since pion exchange is not considered in the approach. 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.
我们使用无π有效场论中的神经网络方法研究了隐藏魅力五夸克态，即 P4312、P4440 和 P(4457)的性质。在该框架中，常规 χ 拟合方法无法区分 P(4440)和 P(4457)的量子数。相比之下，基于神经网络的方法可以对它们进行区分，但这仍然不能被视为对这些状态自旋的证明，因为在该方法中没有考虑π交换。此外，我们还说明了神经网络和拟合方法中 J/ψp 质量分布不变量每个实验数据 bin 对潜在物理的作用。它们的相似和不同之处表明，神经网络方法可以更有效地和直接地利用数据信息。这项研究提供了更多关于神经网络方法如何从质量谱中预测奇异态性质的见解。
