NSF-BSF: Searching for Physics Beyond the Standard Model at the LHCb Experiment

20世纪的主要智力成就之一是粒子物理标准模型(SM)的发展。这个模型成功地将当时已知的所有基本粒子归入具有相似量子性质的群组的层次结构中。在欧洲核子研究中心的大型强子对撞机上发现的希格斯玻色子证实了这个模型到目前为止的有效性。然而，目前存在的标准模型留下了许多关于宇宙的问题。这些包括为什么宇宙中物质支配反物质(CP破坏)，基本成分，夸克和轻子的质量值，夸克之间和轻子之间的混合的大小，以及暗物质的性质。大多数解释都要求存在新的粒子、对称性或力，我们称之为超越标准模型物理(BSM)。该项目旨在探索BSM物理学。大型强子对撞机是世界上首屈一指的高能物理粒子加速器，目前在瑞士日内瓦附近的欧洲核子研究中心实验室运行，该实验室是回答这些BSM问题的最重要设施之一。麻省理工学院小组是LHCb的合作成员，LHCb是一项专门设计用于研究大型强子对撞机上含有b或c夸克的强子衰变的实验，并寻找其他新的物质状态。LHCb的目标是通过检查包含这些夸克的强子的性质来识别自然界中的新物理。新的物理，或新的力，可以由尚未发现的粒子表现出来，粒子的存在将改变衰减率和CP破坏包含b和c夸克的强子的不对称性，从而允许间接观察到新的现象。此外，LHCb正在为研究量子色动力学(QCD)的浮现现象学做出贡献，并寻找新的GeV尺度(即“低质量”)BSM粒子，可能是物质暗部分的组成部分。正是在这一研究领域，麻省理工学院的团队正在发挥领导和基础性的作用，不仅在基于机器学习算法的新触发策略的开发中，以识别和选择感兴趣的物理，而且还在对可能包含诸如暗光子或类似轴子的粒子等假设的“暗扇区”粒子的相互作用进行分析。通过美国-以色列双国科学基金会(NSF-BSF)计划与以色列理工学院的合作，该计划加强了与这些暗区研究相关的分析活动。由MIT-LHCb小组开发的机器学习算法可以在开源软件包中获得，并被许多其他研究小组使用。此外，该小组还在麻省理工学院推出了广受认可的国际大师班计划，该计划将当地高中生带到麻省理工学院校园，了解高能物理研究的兴奋。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

One of the major intellectual achievements of the 20th century was the development of the Standard Model (SM) of particle physics. This model succeeded in classifying all of the elementary particles known at the time into a hierarchy of groups having similar quantum properties. The validity of this model to date was confirmed by the discovery of the Higgs boson at the Large Hadron Collider at CERN. However, the Standard Model as it currently exists, leaves open many questions about the universe. These include why matter dominates over anti-matter in the Universe (CP violation), the values of the masses of the fundamental constituents, the quarks and the leptons, the size of the mixings among the quarks, and separately among the leptons, and the properties of dark matter. Most explanations require the presence of new particles, symmetries or forces, which we call Beyond the Standard Model Physics (BSM). This project is designed to pursue searches for BSM physics. The LHC is the premier High Energy Physics particle accelerator in the world and is currently operating at the CERN laboratory near Geneva Switzerland, one of the foremost facilities for answering these BSM questions. The Massachusetts Institute of Technology group is a collaboration member of LHCb, an experiment designed specifically to study the decays of hadrons containing b or c quarks at the LHC and to search for other new states of matter. The goal of LHCb is to identify new physics in nature by examining the properties of hadrons containing these quarks. New physics, or new forces, can be manifest by particles, as yet to be discovered, whose presence would modify decay rates and CP violating asymmetries of hadrons containing the b and c quarks, and thus allow new phenomena to be observed indirectly. Additionally, LHCb is making contributions to the study of the emergent phenomenology of quantum chromodynamics (QCD), and to searches for new GeV-scale (i.e. "low mass") BSM particles, possibly components of the dark sector of matter. And it is in this research domain that the MIT group is playing a leading and fundamental role, both in the development of new trigger strategies based upon machine learning algorithms to identify and select the physics of interest, but also in conducting analyses of interactions that might contain hypothetical "dark sector" particles such as dark photons or axion-like particles. The analytical activities associated with these dark sector studies are enhanced in this program through collaboration with Technion in Israel, through the United States - Israel Binational Science Foundation (NSF-BSF) program. The machine learning algorithms developed by the MIT-LHCb group are available in open-source software packages and are being used by many other research groups. Additionally, the group has introduced at MIT the well-recognized International Masterclasses program, which brings local high school students to the MIT campus to learn about the excitement of high energy physics research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.