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arXiv 1806.07950hep-ph
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Hessian方法中误差PDF的更新和优化

Updating and Optimizing Error PDFs in the Hessian Approach

Carl Schmidt, Jon Pumplin, C. -P. Yuan

摘要:

我们讨论了如何应用Hessian方法(i)预测新数据集对部分子分布函数(PDF)及其误差的影响,通过产生更新的最佳拟合PDF和误差PDF集,如CTEQ-TEA PDF;(ii)直接预测新数据集对任何其他可观测数据集的PDF误差的影响,而不需要使用新的误差PDF重新计算;以及(iii)将原始集合转换为误差PDF的缩减集合,该缩减集合针对特定的可观测量集合进行优化,以将PDF引起的不确定性再现到任何指定的精度。我们提出了一个软件包,{ \tt ePump}(错误PDF更新方法包),可以用来更新或优化一组PDF,包括最佳拟合PDF集和PDF集的Hessian特征向量对(即,错误PDF),并更新任何其他可观察数据集。我们展示了潜在的方案,提出了相关的大型强子对撞机的现象学应用。特别注意讨论的假设和限制,这个理论框架相比,治疗的完整的全球分析程序。

英文摘要:

We discuss how to apply the Hessian method (i) to predict the impact of a new data set (or sets) on the parton distribution functions (PDFs) and their errors, by producing an updated best-fit PDF and error PDF sets, such as the CTEQ-TEA PDFs; (ii) to predict directly the effect of a new data set on the PDF errors of any other set of observables, without the need to recalculate using the new error PDFs; and (iii) to transform the original set into a reduced set of error PDFs which is optimized for a specific set of observables to reproduce the PDF-induced uncertainties to any specified precision. We present a software package, {\tt ePump} (error PDF Updating Method Package), that can be used to update or optimize a set of PDFs, including the best-fit PDF set and Hessian eigenvector pairs of PDF sets (i.e., error PDFs), and to update any other set of observables. We demonstrate the potential of the program by presenting selected phenomenological applications relevant to the Large Hadron Collider. Special care is given to discuss the assumptions made and the limitations of this theoretical framework compared to a treatment by the full global analysis program.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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