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arXiv 1409.3029hep-ph
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基于最大一致数据集的部分子分布

Parton distributions based on a maximally consistent dataset

Juan Rojo

摘要:

进入整体QCD分析的数据的选择可以对所得到的部分子分布及其对对撞机可观测量的预测产生重大影响。其中一个主要原因是可能存在不一致性,无论是实验内部还是不同实验之间的外部。为了评估全局拟合的鲁棒性,引入了保守PDF集(即基于最大一致数据集的PDF集)的不同定义。然而,这些方法通常受到数据集选择中的理论偏差的影响。在这篇文章中,在简要概述了最近NNPDF的发展,我们提出了一个新的,完全客观的,保守的PDF集的定义,基于贝叶斯重新加权方法。使用新的NNPDF3.0框架,我们产生了各种保守的集合,这些集合在各自的PDF不确定性内以及与全局拟合相互一致。我们探讨了它们对LHC现象学的一些影响,发现与全局拟合结果也有很好的一致性。这些结果提供了新的NNPDF3.0拟合方法的非平凡验证测试,并表明拟合数据集中可能的不一致性不会对全局拟合PDF产生实质性影响。

英文摘要:

The choice of data that enters a global QCD analysis can have a substantial impact on the resulting parton distributions and their predictions for collider observables. One of the main reasons for this has to do with the possible presence of inconsistencies, either internal within an experiment or external between different experiments. In order to assess the robustness of the global fit, different definitions of a conservative PDF set, that is, a PDF set based on a maximally consistent dataset, have been introduced. However, these approaches are typically affected by theory biases in the selection of the dataset. In this contribution, after a brief overview of recent NNPDF developments, we propose a new, fully objective, definition of a conservative PDF set, based on the Bayesian reweighting approach. Using the new NNPDF3.0 framework, we produce various conservative sets, which turn out to be mutually in agreement within the respective PDF uncertainties, as well as with the global fit. We explore some of their implications for LHC phenomenology, finding also good consistency with the global fit result. These results provide a non-trivial validation test of the new NNPDF3.0 fitting methodology, and indicate that possible inconsistencies in the fitted dataset do not affect substantially the global fit PDFs.

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