ATLAS Bridging Application: Di-Higgs Processes as a Window to the Standard Model and Beyond

ATLAS 桥接应用：Di-Higgs 过程作为标准模型及其他模型的窗口

• 批准号: SAPPJ-2020-00032
• 负责人: Swiatlowski, Maximilian
• 金额: $ 7.29万
• 依托单位: TRIUMF
• 依托单位国家: 加拿大
• 项目类别: Subatomic Physics Envelope - Project
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=741712
• 关键词: ATLAS; Bridging; Application; Di; Higgs

The Large Hadron Collider (LHC) collides protons at the highest energy conditions of any facility in the world, recreating conditions a fraction of a second after the Big Bang. We record the outcomes of these collisions with the ATLAS detector, and we use this data to understand the fundamental building blocks of the universe and the forces which bind them together. In 2012 ATLAS (and another experiment, CMS) discovered a new particle, the Higgs boson. This particle is thought to play a critical role in our understanding of the universe by providing other particles their masses. While this discovery of the Higgs Boson resolved one set of questions, a whole host of new ones has emerged. The most pressing is about the nature of the Higgs mechanism, the process which provides the other particles their masses. My research program addresses this question by searching for collisions producing not just one Higgs boson, but two. These events are extremely rare: only roughly one in a trillion collisions produces two Higgs bosons at once. We use advanced data analysis techniques to pick out this delicate needle from the haystack, but the challenge is worthwhile: these events can hold clues to the shape of the Higgs energy potential and the fundamental mechanism that provides particles their masses. Additionally, the conditions just moments after the Big Bang could be imprinted onto this same Higgs energy potential: if we are able to measure this, we could see a relic of the universe's birth. Discovering these double Higgs events could revolutionize our understanding of the universe, allowing us to see not just how the universe works but how it evolved to its current state, explaining the why we are made of only matter and not anti-matter. I intend to place Canadian scientists at the forefront of the global effort to discover these processes and understand their consequences. A second key component of my research program is the full utilization of information that our detectors provide. Since the Higgs boson is not stable, observing pairs of Higgs bosons requires that we accurately measure particles they decay into. The most common decay is into b-quarks, which themselves form complicated sprays of particles called jets which we can measure with ATLAS's inner detector and calorimeter systems. I intend to use deep learning techniques, inspired by developments in image recognition technology, to revolutionize how we measure the energy of the particles that make up jets. In the same way that machine learning has revolutionized photography through the combination of several images at once, we can combine low level information from the detector and algorithms designed and tuned by physicists to significantly sharpen our understanding of the collisions we are observing. By improving the quality of the data we are taking, we can make the most of the significant Canadian investment in ATLAS's upgrades and accelerate our road to discoveries.

大型强子对撞机（LHC）在世界上任何设施的最高能源条件下碰撞质子，重现大爆炸后一秒钟的一小部分。我们记录了这些与Atlas检测器相撞的结果，并使用这些数据来了解宇宙的基本构建块以及将它们绑定在一起的力。 2012年，Atlas（和另一个实验CMS）发现了一个新粒子，即Higgs玻色子。人们认为，通过提供其他粒子的质量，该粒子在我们对宇宙的理解中起着至关重要的作用。尽管希格斯玻色子的发现解决了一组问题，但已经出现了许多新的问题。最紧迫的是关于希格斯机制的性质，该过程提供了其他粒子的质量。我的研究计划通过搜索碰撞而不仅仅是一个希格斯玻色子，而是两个，从而解决了这个问题。这些事件极为罕见：只有一万亿次碰撞中只有一场碰撞会产生两个希格斯玻色子。我们使用先进的数据分析技术从干草堆中挑选出这种细腻的针头，但是挑战是值得的：这些事件可以使HIGGS能量潜力的形状和提供颗粒质量的基本机制保持线索。此外，大爆炸之后的瞬间可能会印在同样的希格斯能源潜力上：如果我们能够衡量这一点，我们可以看到宇宙诞生的遗物。发现这些双重希格斯事件可以彻底改变我们对宇宙的理解，使我们不仅看到宇宙的工作原理，而且可以看到它如何发展到当前状态，从而解释了为什么我们只有物质而不是反物质。我打算将加拿大科学家置于全球努力的最前沿，以发现这些过程并了解它们的后果。我的研究计划的第二个关键组成部分是对检测器提供的信息的全面利用。由于希格斯玻色子不稳定，因此观察成对的希格斯玻色子需要我们准确地测量它们腐烂成的颗粒。最常见的衰减是B Quarks，它们本身形成了复杂的称为喷气机的颗粒喷雾剂，我们可以使用Atlas的内部检测器和热量计系统进行测量。我打算使用深度学习技术，灵感来自图像识别技术的发展，以彻底改变我们如何测量构成喷气机的颗粒的能量。就像机器学习通过同时彻底改变了摄影的方式，我们可以结合从探测器和由物理学家设计和调整的算法中的低级信息，以显着增强我们对所观察到的碰撞的理解。通过提高所采用的数据质量，我们可以充分利用加拿大对Atlas升级的大量投资，并加速我们的发现道路。