论文标题
帕顿分布与规模不确定性：蒙特卡洛抽样方法
Parton distributions with scale uncertainties: a MonteCarlo sampling approach
论文作者
论文摘要
我们提出了将比例不确定性纳入Parton分布函数（PDFS）的MCSCALES方法。新方法建立在蒙特卡洛采样的基础上，将实验不确定性传播到了NNPDF方法基础的PDF空间中，但它将其扩展到分解和肾化级数的空间。在用于获得蒙特卡洛集团中每个PDF复制品的理论预测中设置的每个比例组合中，将事先概率分配给了，并通过选择满足适合质量标准的副本来获得后验概率。我们的方法使人们可以将PDF中的比例变化与党横截面的计算中的比例变化完全匹配，从而考虑了两者之间的完整相关性。我们说明了我们的方法论为各种LHC可观察物所提供的现象学探索的机会。提供了一组充满比例信息的PDF，以及一组使用它们的工具。
We present the MCscales approach for incorporating scale uncertainties in parton distribution functions (PDFs). The new methodology builds on the Monte Carlo sampling for propagating experimental uncertainties into the PDF space that underlies the NNPDF approach, but it extends it to the space of factorisation and renomalisation scales. A prior probability is assigned to each scale combinations set in the theoretical predictions used to obtain each PDF replica in the Monte Carlo ensemble and a posterior probability is obtained by selecting replicas that satisfy fit-quality criteria. Our approach allows one to exactly match the scale variations in the PDFs with those in the computation of the partonic cross sections, thus accounting for the full correlations between the two. We illustrate the opportunities for phenomenological exploration made possible by our methodology for a variety of LHC observables. Sets of PDFs enriched with scale information are provided, along with a set of tools to use them.
