arXiv:2506.20555hep-phcs.AI2025-06被引 11

用深度神经网络求解多夸克束缚态,突破传统方法计算瓶颈。

DeepQuark: A Deep-Neural-Network Approach to Multiquark Bound States

  • 设计新型神经网络架构DeepQuark,高效处理多夸克系统强关联与禁闭问题。
  • 在核子、重夸克四夸克及五夸克态中性能媲美顶尖方法,五夸克态更优。
  • 可无偏描述分子型与紧凑型四夸克态,适合研究非微扰量子色动力学。

首次将基于深度神经网络的变分蒙特卡洛方法应用于多夸克束缚态,其复杂性因强SU(3)色相互作用远超电子或核子体系。我们设计了新型高效架构DeepQuark,应对多夸克系统中的强关联、额外离散量子数及难以处理的禁闭相互作用。该方法在核子、双重重四夸克和全重四夸克体系中表现与扩散蒙特卡洛及高斯展开法相当,尤其在五夸克态上优于现有计算,如三重重五夸克态。对于核子,成功引入三体弦管禁闭相互作用且无额外计算成本。在四夸克体系中,以无偏波函数形式一致描述了分子态$T_{cc}$与紧凑态$T_{bb}$。在五夸克区,得到弱束缚的$ar D^*Ξ_{cc}^*$分子态$P_{ccar c}(5715)$(自旋$S=\frac{5}{2}$)及其底夸克对应态$P_{bbar b}(15569)$,可类比于分子态$T_{cc}$。建议实验在D波$J/ψΛ_c$通道中搜索$P_{ccar c}(5715)$。DeepQuark有望拓展至更大多夸克体系,突破传统方法计算障碍,也为超越两体相互作用的禁闭机制研究提供强大框架,有助于理解非微扰量子色动力学与广义多体物理。

原文摘要 · Abstract (English)

For the first time, we implement the deep-neural-network-based variational Monte Carlo approach for the multiquark bound states, whose complexity surpasses that of electron or nucleon systems due to strong SU(3) color interactions. We design a novel and high-efficiency architecture, DeepQuark, to address the unique challenges in multiquark systems such as stronger correlations, extra discrete quantum numbers, and intractable confinement interaction. Our method demonstrates competitive performance with state-of-the-art approaches, including diffusion Monte Carlo and Gaussian expansion method, in the nucleon, doubly heavy tetraquark, and fully heavy tetraquark systems. Notably, it outperforms existing calculations for pentaquarks, exemplified by the triply heavy pentaquark. For the nucleon, we successfully incorporate three-body flux-tube confinement interactions without additional computational costs. In tetraquark systems, we consistently describe hadronic molecule $T_{cc}$ and compact tetraquark $T_{bb}$ with an unbiased form of wave function ansatz. In the pentaquark sector, we obtain weakly bound $\bar D^*Ξ_{cc}^*$ molecule $P_{cc\bar c}(5715)$ with $S=\frac{5}{2}$ and its bottom partner $P_{bb\bar b}(15569)$. They can be viewed as the analogs of the molecular $T_{cc}$. We recommend experimental search of $P_{cc\bar c}(5715)$ in the D-wave $J/ψΛ_c$ channel. DeepQuark holds great promise for extension to larger multiquark systems, overcoming the computational barriers in conventional methods. It also serves as a powerful framework for exploring confining mechanism beyond two-body interactions in multiquark states, which may offer valuable insights into nonperturbative QCD and general many-body physics.

多夸克态神经网络量子色动力学计算物理

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