论文标题
与Atlas检测器在13 TEV处的硬光子相关的顶级Quark对生产的横截面测量值
Cross-section measurements of top-quark pair production in association with a hard photon at 13 TeV with the ATLAS detector
论文作者
论文摘要
在夸克（Quark）的发现25年后，CERN的大型强子对撞机在前所未有的能量上产生了前所未有的尺度上的质子 - 普罗顿碰撞数据，并预示了一个最高的精度测量时代。与光子（$ t \ bar {t}γ$）相关的顶级夸克对的生产可访问电磁上顶耦合，这是顶部夸克的基本特性之一。标准模型的各种扩展可以预测耦合强度或结构的修改，并且与$ t \ bar {t}γ$生产横截面的标准模型预测的偏差将表明新物理学。借助大型强子对撞机的足够统计数据，电子通道由于其高信号纯度和精确的可用理论预测而引起了特别的兴趣。 本文提出了结果，结果是在2015年至2018年之间在质子蛋白核能碰撞器中，在2015年至2018年之间在13 TEV质量中心能量中收集了ATLAS检测器的全部2个数据集，与139 fb $^{ - 1} $相对应。为了将结果与包括非谐振图的固定顺序计算进行比较，执行了$ t \ bar {t}γ+TWγ$的合并测量。将重点放在电子通道中基准包容性横截面的测量上。此外，随着几种可观察到的功能，图形数据被展开至Parton水平，并测量差分横截面。将基准的包容性和差异结果与QCD的近代领先顺序的最先进的固定阶计算进行了比较。论文的另一个重点放在研究上，以使用机器学习技术，尤其是深神经网络来识别及时光子。
25 years after the top quark's discovery, the Large Hadron Collider at CERN produces proton-proton collision data on unprecedented scales at unprecedented energies - and has heralded an era of top-quark precision measurements. The production of a top-quark pair in association with a photon ($t\bar{t}γ$) gives access to the electromagnetic top-photon coupling, one of the fundamental properties of the top quark. Various extensions of the Standard Model predict modifications of the coupling strength or structure, and deviations from the Standard Model prediction of the $t\bar{t}γ$ production cross-section would indicate new physics. With enough statistics available from the Large Hadron Collider, the electron-muon channel has gained particular interest due to its high signal purity and precise available theory predictions. This thesis presents results with the full Run 2 dataset collected with the ATLAS detector in proton-proton collisions at the Large Hadron Collider between 2015 and 2018 at 13 TeV centre-of-mass energy, corresponding to an integrated luminosity of 139 fb$^{-1}$. In order to compare the results to fixed-order calculations that include non-doubly-resonant diagrams, a combined measurement of $t\bar{t}γ+ tWγ$ is performed. The focus is placed on a measurement of the fiducial inclusive cross-section in the electron-muon channel. Furthermore, the ATLAS data is unfolded to parton level and measurements of differential cross-sections as functions of several observables are presented. Both fiducial inclusive and differential results are compared to state-of-the-art fixed-order calculations at next-to-leading order in QCD. An additional focus of the thesis is placed on studies to use machine-learning techniques, in particular deep neural networks, for the identification of prompt photons.
