The Higgs boson and the top quark in the ATLAS detector: gateway to new physics

ATLAS 探测器中的希格斯玻色子和顶夸克：通向新物理学的大门

• 批准号: SAPPJ-2020-00034
• 负责人: David, Claire
• 金额: $ 3.64万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Subatomic Physics Envelope - Project
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=718496
• 关键词: Higgs; boson; top; quark; ATLAS

In the quest to understand the universe through its elementary constituents, CERN's Large Hadron Collider (LHC) has delivered important results confirming the current theory of particle physics, the Standard Model (SM). The discovery of the Higgs boson was a remarkable achievement: it explained how elementary particles acquired their masses. Despite being a very accurate description of the fundamental particle physics laws at the quantum scale, the SM fails to explain major cosmological phenomena in our universe. Finding a sign of “new physics” extending beyond the SM would be a ground-breaking discovery, and a guide toward a more complete description of nature. A promising gateway to probe for signatures of new physics is the measurement of the Higgs boson's interaction with the heaviest particle of matter: the top quark. The interaction strength, called Yukawa coupling, is very sensitive to new physics, and any deviation with respect to the theoretical prediction would uncover non-SM phenomena. I led the effort on the background evaluation towards the observation of the Higgs boson production in association with a top quark pair, or ttH, with the multipurpose ATLAS detector at the LHC. The ttH production mode is the physics process that can give direct access to the top quark Yukawa coupling. However, extracting the ttH signal from the LHC data is extremely challenging; the main background processes are very difficult to accurately model. The simulations, traditionally performed using Monte Carlo (MC) techniques, are intrinsically biased due to theoretical limitations. I propose to deploy advanced machine learning tools to measure with better precision the top quark Yukawa coupling in order to exploit the full potential of the incoming LHC Run 3 (2021 - 2023). Generative Adversarial Networks (GANs) are promising deep learning models with relevant applications in high energy physics. I propose a gradual approach to implement GANs for mitigating the large theoretical uncertainties and make the ttH analysis less reliant on MC simulations. This is in preparation for the High-Luminosity LHC program starting 2026, where the needs of MC with high statistics is almost multiplied by ten. GAN-generated collisions would be faster to produce than MC and much less computationally intensive. Preparing for the High-Luminosity LHC also requires detector upgrades and I propose to use my expertise in particle detector characterization to join the effort of the York University/Toronto cluster, which is in charge of producing and testing 500 sensor units (silicon and electronics) of the future ATLAS inner tracker. York University is best suited to be the dedicated site for detailed evaluation and recovery of components failing standard quality assurance tests. I propose to design and construct the evaluation laboratory, and oversee the reevaluation and recovery efforts during production.

为了通过其基本构成理解宇宙，CERN的大型强子对撞机（LHC）取得了重要的结果证实了当前的粒子物理学理论，即标准模型（SM）。希格斯玻色子的发现是一个了不起的成就：它解释了基本粒子如何获得其质量。尽管在量子尺度上对基本粒子物理定律进行了非常准确的描述，但SM仍无法解释我们宇宙中的主要宇宙学现象。发现“新物理学”延伸超出SM的迹象将是一个突破性的发现，也是对自然更完整描述的指南。 探测新物理学签名的有前途的门户是Higgs Boson与物质最重的粒子的相互作用：顶部夸克。相互作用强度（称为Yukawa耦合）对新物理学非常敏感，并且相对于理论预测的任何偏差都将发现非SM现象。我领导了背景评估的努力，以与LHC的多功能地图集探测器相关的一对Quark对（TTH），以观察Higgs玻色子的产生。 TTH生产模式是物理过程，可以直接访问顶级Quark Yukawa耦合。但是，从LHC数据中提取TTH信号非常挑战。主要的背景过程很难准确建模。传统上使用Monte Carlo（MC）技术进行的模拟由于理论上的局限性而在本质上存在偏差。 我建议部署高级机器学习工具，以更好的精确度测量顶级Quark Yukawa耦合，以探索传入的LHC运行3（2021-2023）的全部潜力。生成的对抗网络（GAN）是有望在高能量物理学中使用相关应用的深度学习模型。我提出了一种实施GAN的等级方法，以减轻大型理论不确定性，并使TTH分析与MC模拟的相关性降低。这是为从2026年开始的高亮度LHC计划做准备的，在该计划中，具有高统计数据的MC的需求几乎乘以十。与MC相比，GAN生成的碰撞的生产速度要快，计算密集程度要少得多。 准备高肌性LHC还需要探测器升级，我建议使用我在粒子探测器表征方面的专业知识来加入约克大学/多伦多群集的工作，该群集负责生产和测试未来Atlas Inner Tracker的500个传感器单元（硅和电子）。约克大学最适合成为专门的网站，用于详细评估和恢复标准质量保证测试的组件。我建议设计和构建评估实验室，并监督生产过程中的重新评估和恢复工作。