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arXiv 2608.26988nucl-th

优化人工神经网络以用于轻核中的偶极强度预测

Optimizing artificial neural networks for dipole strength predictions in light nuclei

Tim Egert, Weiguang Jiang, Sonia Bacca

AI总结:

本研究提出优化的人工神经网络方法,用于预测A<50轻核的电偶极强度,其稳定性提升、变异性降低,可捕捉同位素依赖规律,计算的极化率对能量区间敏感,可补充光核数据库并更新⁹Be极化率。

AI中文摘要:

我们提出了一种优化的人工神经网络方法,用于预测质量数A<50的原子核中的电偶极强度函数。在先前的一项全局研究[Phys.Rev.C 111 (2025) 5, L051308]的基础上,本研究聚焦于偶极响应结构更复杂的轻核区域。新网络采用了两阶段训练流程、质子数的学习嵌入、明确的低能偶极起始点、不确定性加权训练以及高能正则化。集成预测结果显示,与早期的全局神经网络相比,经独立初始化的网络之间的稳定性有所提升,变异性大幅降低。对训练集中未包含的选定同位素的测试表明,对于训练集中已有的元素,该优化网络能够捕捉到主要的同位素依赖偶极强度系统学规律。作为进一步的测试,我们计算了选定轻核的电偶极极化率,并与文献值进行了比较,结果显示其对所覆盖的能量区间具有显著敏感性。由此得到的A<50原子核的连续电偶极强度函数集合,是现有光核数据库的实用补充,尤其适用于需要在宽能量区间内呈现平滑响应函数的应用场景。作为一项应用,我们更新了⁹Be的电偶极极化率数据。

英文摘要:

We present an optimized artificial neural network approach for predicting electric dipole strength functions in nuclei with $A < 50$. Building upon a previous global study [Phys.Rev.C $\textbf{111}$ (2025) 5, L051308], we focus here on the region of light nuclei where dipole responses are more structured. The new network incorporates a two-stage training process, a learned embedding of the proton number, explicit low-energy dipole onsets, uncertainty-weighted training, and high-energy regularization. Ensemble predictions show improved stability and substantially reduced variability across independently initialized networks compared with the earlier global neural network. Tests on selected isotopes withheld from training show that, for elements represented in the training set, the optimized network captures the main isotope dependent dipole strength systematics. As a further test, we compute electric dipole polarizabilities for selected light nuclei and compare them with literature values revealing a pronounced sensitivity to the covered energy interval. The resulting set of continuous electric dipole strength functions for nuclei with $A < 50$ provides a practical complement to existing tabulated photonuclear databases and is particularly suited for applications requiring smooth response functions over broad energy intervals. As an application, we provide an update on the electric dipole polarizability of $^9$Be.

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