ATLAS中风味标记不确定度统计处理的两个新进展

I. Luise, Y. Ke, G. Piacquadio, Q. Buat
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引用次数: 0

摘要

本文介绍了在ATLAS物理分析中实现风味标记不确定度的两种新方法。为了减少风味标签校准的不确定性,物理分析中采用了特征向量分解方法。然而,在不同的风味标签选择中,得到的风味标签特征向量通常是不相同的,因此在组合分析中,不确定性不能直接关联。为了克服这个问题,设计了一种新的方法,称为特征向量重组。本文介绍了该方法,并给出了其在物理分析中的应用实例,重点介绍了其在物理分析中的应用。第二个发展涉及高横向动量射流分析中的风味标记不确定性。使用喷射-p - T光谱范围为140-250 GeV的事件计算风味标签不确定度的原位校准,并将其用于所有的喷射-p - T光谱。因此,在较高的横向动量下,校准需要专门的外推不确定度,以便考虑与中心值的可能偏差。文件的第二部分描述了从Z '模拟事件开始提取这些外推不确定性的方法。
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Two New Developments on the Statistical Treatment of Flavour Tagging Uncertainties in ATLAS
The document introduces two new methods on the implementation of flavour tagging uncertainties in ATLAS physics analyses. In order to reduce the number of flavor-tagging calibration uncertainties, the physics analyses use an eigenvector decomposition approach. However, the resulting flavour tagging eigenvectors are in general not the same across flavour tagging selections, so the uncertainties can not be directly correlated in combination analyses. A new method, called eigenvector recomposition , has been designed to overcome this problem. This proceeding describes the method and gives practical examples about its usage in physics analyses, focusing on the 𝑉𝐻, 𝐻 → 𝑏𝑏 analysis. The second development involves the flavour tagging uncertainties in analyses with high-transverse momentum jets. The in-situ calibration of the flavour tagging uncertainties is computed using events with jet-p T spectra up to 140-250 GeV and used through all the jet-p T spectrum. Therefore, at higher transverse momenta the calibration needs dedicated extrapolation uncertainties in order to account for possible deviations from the central value. The second part of the document describes the method used to extract these extrapolation uncertainties starting from Z’ simulated events.
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