Differential Cross Sections and the Impact of Model Defects in Nuclear Data Evaluation
Differential Cross Sections and the Impact of Model Defects in Nuclear Data Evaluation
复制标题
核数据评估中的微分截面和模型缺陷的影响
DOI：
10.1051/epjconf/201611109001
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
H. Leeb
中科院分区：
文献类型：
--
作者：
G. Schnabel;H. Leeb
提出了一种基于扩展建模的贝叶斯评估方法中包含所谓的模型缺陷的统计一致性方法。该方法使用高斯过程来定义可能的模型缺陷的先验概率分布。列入是特别重要的微分数据，即角度微分截面和光谱的喷射物的正确评价。该方法被成功地应用到一个简单的现实的例子，清楚地显示了模型缺陷的影响，同时评估的角度微分和角度集成的横截面。
A statistically consistent method for the inclusion of the so-called model defects into Bayesian evaluation methods based on extensive modeling is presented. The method uses Gaussian processes to define a-priori probability distributions for possible model defects. The inclusion is of particular importance for the proper evaluation of differential data, i.e. angle-differential cross sections and spectra of ejectiles. The method is successfully applied to a simple realistic example which clearly shows the impact of model defects in a simultaneous evaluation of angle-differential and angle-integrated cross sections.