Bayesian evaluation of energy dependent neutron induced fission yields  

作　　者：肖名翔 包小军 韦峥 姚泽恩 Ming-Xiang Xiao;Xiao-Jun Bao;Zheng Wei;Ze-En Yao(Department of Physics,Hunan Normal University,Changsha 410081,China;School of Nuclear Science and Technology,Lanzhou University,Lanzhou 730000,China)

机构地区：[1]Department of Physics,Hunan Normal University,Changsha 410081,China [2]School of Nuclear Science and Technology,Lanzhou University,Lanzhou 730000,China

出　　处：《Chinese Physics C》2023年第12期96-101,共6页中国物理C（英文版）

基　　金：the National Natural Science Foundation of China(12175064,U2167203);the Outstanding Youth Science Foundation of Hunan Province,China(2022JJ10031)。

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

关 键 词：Bayesian evaluation energy dependent neutron induced fission yields 

分 类 号：O571.43[理学—粒子物理与原子核物理]