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arXiv 1906.05296hep-phhep-ex
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用贝叶斯重新加权约束SMEFT

Constraining the SMEFT with Bayesian reweighting

Samuel van Beek, Emanuele R. Nocera, Juan Rojo, Emma Slade

摘要:

我们说明了如何贝叶斯重新加权可用于将新的测量提供的约束纳入全球蒙特卡罗分析的标准模型有效场论(SMEFT)。这种方法,广泛应用于研究新的数据对质子的部分子分布函数的影响,在这里验证了我们最近的顶夸克部门的SMEFiT分析。我们展示了如何,在定义良好的条件下,SMEFT运营商直接敏感的新数据,重新加权过程是相当于一个相应的新的适合。我们通过香农熵和Kolmogorov-Smirnov统计量来量化添加到SMEFT参数空间的信息量。我们调查的依赖我们的结果选择的NNPDF或Giele-Keller表达式的权重。

英文摘要:

We illustrate how Bayesian reweighting can be used to incorporate the constraints provided by new measurements into a global Monte Carlo analysis of the Standard Model Effective Field Theory (SMEFT). This method, extensively applied to study the impact of new data on the parton distribution functions of the proton, is here validated by means of our recent SMEFiT analysis of the top quark sector. We show how, under well-defined conditions and for the SMEFT operators directly sensitive to the new data, the reweighting procedure is equivalent to a corresponding new fit. We quantify the amount of information added to the SMEFT parameter space by means of the Shannon entropy and of the Kolmogorov-Smirnov statistic. We investigate the dependence of our results upon the choice of either the NNPDF or the Giele-Keller expressions of the weights.

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