论文标题
核数据评估管道的概念和软件实施
Conception and software implementation of a nuclear data evaluation pipeline
论文作者
论文摘要
我们讨论了针对$^{56} $ fe的中子诱导的横截面的核数据评估管道的设计和软件实施,该核对截面是使用核模型代码talys与相关的实验数据相结合的$^{56} $ fe。重点放在管道的数学和技术方面,而不是对$^{56} $ fe的评估,这是暂定的。详细讨论了在管道中组合和使用的数学构建块。实验数据,系统和统计误差,模型参数和缺陷的统一表示,可以在大量实验数据中应用一般最小二乘(GLS)及其自然扩展,即Levenberg-Marquardt(LM)算法。针对核数据评估量身定制的LM算法涉及确切的非线性物理模型,以确定核量的最佳估计。相关的不确定性信息是从泰勒扩张以最大后验分布的形式得出的。我们还根据其IT(=信息技术)的构建块讨论管道,例如有效管理和检索Exfor库的实验数据并在科学群集上分发计算的块。依靠数学和IT构建区块,我们详细介绍了管道中的一系列步骤以执行评估,例如检索实验数据,使用边际可能性优化(MLO)的实验不确定性(MLO)的纠正以及在筛查千层talys参数之后 - 包括豪斯级别的参数,包括对能量依赖的依赖性参数,即在150上进行拟合的参数,即拟合的参数 - 该管道的代码在www.nuclearldata.com上提供了简化安装的手册和dockerfile的代码。
We discuss the design and software implementation of a nuclear data evaluation pipeline applied for a fully reproducible evaluation of neutron-induced cross sections of $^{56}$Fe above the resolved resonance region using the nuclear model code TALYS combined with relevant experimental data. The emphasis is on the mathematical and technical aspects of the pipeline and not on the evaluation of $^{56}$Fe, which is tentative. The mathematical building blocks combined and employed in the pipeline are discussed in detail. A unified representation of experimental data, systematic and statistical errors, model parameters and defects enables the application of the Generalized Least Squares (GLS) and its natural extension, the Levenberg-Marquardt (LM) algorithm, on a large collection of experimental data. The LM algorithm tailored to nuclear data evaluation accounts for the exact non-linear physics model to determine best estimates of nuclear quantities. Associated uncertainty information is derived from a Taylor expansion at the maximum of the posterior distribution. We also discuss the pipeline in terms of its IT (=information technology) building blocks, such as those to efficiently manage and retrieve experimental data of the EXFOR library and to distribute computations on a scientific cluster. Relying on the mathematical and IT building blocks, we elaborate on the sequence of steps in the pipeline to perform the evaluation, such as the retrieval of experimental data, the correction of experimental uncertainties using marginal likelihood optimization (MLO) and after a screening of thousand TALYS parameters -- including Gaussian process priors on energy dependent parameters -- the fitting of about 150 parameters using the LM algorithm. The code of the pipeline including a manual and a Dockerfile for a simplified installation is available at www.nucleardata.com.