AI 中文总结
研究利用基于Pfaffian-Jastrow神经量子态的变分蒙特卡罗方法计算轻到中等质量核的基态能量和电荷半径，考虑不同相互作用，评估神经量子态性能及相互作用修正影响，分析计算缩放以用于未来大规模计算。
AI 中文摘要
我们利用基于Pfaffian-Jastrow神经量子态的变分蒙特卡罗方法，计算了多达\(A = 58\)个核子的轻到中等质量核的基态能量和电荷半径。为进一步理解核哈密顿量中哪些元素对于预测全核图表上具有百分之几误差的结合能和电荷半径是“必不可少的”，我们考虑了受无π介子有效场理论启发的不同相互作用。具体而言，除了[《物理评论C》103, 054003 (2021)]中的模型“o”，我们还研究了核子 - 核子力中电荷对称性破缺和电荷依赖项以及\(p\)波贡献的影响，这些已被发现对\(p\)壳层核的稳定性至关重要。除了其内在意义，我们的工作评估了神经量子态在中等质量区域的性能，并研究了这些相互作用修正的影响。利用由此得到的基态模拟，我们分析了具有神经量子态的变分蒙特卡罗作为系统大小和计算资源函数的计算缩放，为未来大规模计算提供了预测。
英文摘要
We compute ground-state energies and charge radii of light- to medium-mass nuclei with up to $A=58$ nucleons, leveraging a variational Monte Carlo method based on Pfaffian-Jastrow neural quantum states. To further understand which elements of the nuclear Hamiltonian are "essential" to predict binding energies and charge radii across the nuclear chart with few-percent errors, we consider different interactions inspired by pionless effective field theory. Specifically, in addition to model "o" of [Phys. Rev. C 103, 054003 (2021)], we study the impact of charge-symmetry-breaking and charge-dependent terms in the nucleon-nucleon force, as well as $p$-wave contributions, which have been found to be critical for the stability of $p$-shell nuclei. In addition to its intrinsic interest, our work assesses the performance of neural quantum states in the medium-mass regime and examines the impact of these interaction modifications. Using the resulting ground-state simulations, we analyze the computational scaling of variational Monte Carlo with neural quantum states as a function of system size and computational resources, enabling projections for future large-scale calculations.
Comments15 pages, 5 figures
