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arXiv 1408.4572hep-phnucl-th
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Hessian PDF重新加权满足贝叶斯方法

Hessian PDF reweighting meets the Bayesian methods

Hannu Paukkunen, Pia Zurita

摘要:

我们讨论了Hessian PDF重新加权-一种旨在估计新测量对一组PDF的影响的技术。该方法直接源于在通常的$χ^2$ -拟合中考虑新数据,并且它自然地也包含公差$Δχ^2>1$的非零值。与当代贝叶斯重新加权技术相比,不需要生成大量的PDF Monte-Carlo副本,并且只需要使用原始PDF的中心和错误集来评估可观测量。尽管显然是相当不同的方法,我们发现,海森和贝叶斯技术实际上是等同的,如果$Δχ^2$标准是适当的贝叶斯似然函数,这是一个简单的指数。

英文摘要:

We discuss the Hessian PDF reweighting - a technique intended to estimate the effects that new measurements have on a set of PDFs. The method stems straightforwardly from considering new data in a usual $χ^2$-fit and it naturally incorporates also non-zero values for the tolerance, $Δχ^2>1$. In comparison to the contemporary Bayesian reweighting techniques, there is no need to generate large ensembles of PDF Monte-Carlo replicas, and the observables need to be evaluated only with the central and the error sets of the original PDFs. In spite of the apparently rather different methodologies, we find that the Hessian and the Bayesian techniques are actually equivalent if the $Δχ^2$ criterion is properly included to the Bayesian likelihood function that is a simple exponential.

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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