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基于次领头阶矩阵元方法从顶夸克对事例测定顶夸克质量:潜力与展望

Determination of the top-quark mass from top-quark pair events with the matrix element method at next-to-leading order: Potential and prospects

Till Martini, Turan Nuraliyev, Peter Uwer

AI总结:

本研究探究次领头阶(NLO)精度下矩阵元方法测定顶夸克质量的潜力,通过两种模拟设置验证发现该方法可显著降低理论不确定性,对LHC高亮度阶段的相关分析具有重要意义。

摘要:

2004年,Tevatron的D0实验在一项开创性工作中使用矩阵元方法,从少量事例中测定了顶夸克质量。此后,该方法逐步发展为一种强大的分析工具。早期应用仅限于领头阶精度,目前学界也已对其扩展至次领头阶(NLO)精度开展了研究。本文探究了NLO精度下矩阵元方法利用成对产生的顶夸克事例测定顶夸克质量的潜力。我们通过生成具有固定输入质量的非加权事例模拟了一个理想实验,并应用矩阵元方法构建顶夸克质量的估计量。研究考察了两种不同的设置:由NLO精度的固定阶截面得到的非加权事例,以及使用与部分子簇射匹配的POWHEG得到的事例。后者可实现更符合实际的模拟,能够用于研究高阶修正的影响以及该方法的稳健性。我们发现,与领头阶相比,NLO精度的矩阵元方法可显著降低理论不确定性。鉴于大型强子对撞机(LHC)的高亮度阶段即将到来,这一发现对于不再受统计不确定性主导的分析工作具有特别重要的意义。

英文摘要:

In 2004 the matrix element method was used in a pioneering work by the Tevatron experiment D0 to determine the top-quark mass from a handful of events. Since then the method has been matured into a powerful analysis tool. While the first applications were restricted to leading-order accuracy, in the meantime also the extension to next-to-leading order (NLO) accuracy has been studied. In this article we explore the potential of the matrix element method at NLO to determine the top-quark mass using events with pair-produced top quarks. We simulate a toy experiment by generating unweighted events with a fixed input mass and apply the matrix element method to construct an estimator for the top-quark mass. Two different setups are investigated: unweighted events obtained from the fixed-order cross section at NLO accuracy as well as events obtained using POWHEG matched to a parton shower. The latter lead to a more realistic simulation and allow to study the impact of higher-order corrections as well as the robustness of the approach. We find that the matrix element method in NLO accuracy leads to a significant reduction of the theoretical uncertainties compared to leading order. In view of the high luminosity phase of the LHC, this observation is especially relevant in analyses which are no longer dominated by statistical uncertainties.

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