近日，兰州大学的韦峥教授及其研究团队取得一项新进展。经过不懈努力，他们实现能量依赖中子诱导裂变产额的贝叶斯评价。相关研究成果已于2023年12月15日在国际知名学术期刊《中国物理C》上发表。

该研究团队应用贝叶斯神经网络（BNN）方法来学习现有的中子诱导裂变产额，并对未知的不确定量化进行预测。研究人员将预测结果与实验数据进行比较，发现BNN评估结果在裂变产额的分布位置和能量依赖关系上是令人满意的。他们对几种锕系元素的碎片质量分布进行了预测，这些预测结果可能对今后的实验有用。

据悉，从基础和应用的角度来看，碎片质量分布是裂变的重要观测值。

附：英文原文

Title: Bayesian evaluation of energy dependent neutron induced fission yields

Author: Ming-Xiang Xiao, Xiao-Jun Bao, Zheng Wei, Ze-En Yao

Issue&Volume: 2023-12-15

Abstract: From both the fundamental and applied perspectives, fragment mass distributions are important observables of fission. We apply the Bayesian neural network (BNN) approach to learn the existing neutron induced fission yields and predict unknowns with uncertainty quantification. Comparing the predicted results with experimental data, the BNN evaluation results are found to be satisfactory for the distribution positions and energy dependencies of fission yields. Predictions are made for the fragment mass distributions of several actinides, which may be useful for future experiments.

DOI: 10.1088/1674-1137/acf7b5

Source: http://hepnp.ihep.ac.cn/article/doi/10.1088/1674-1137/acf7b5