CAREER: Probing the High Energy Frontier With the CMS Experiment

完全理解描述最小亚原子长度的相互作用的物理学是难以捉摸的。通过欧洲核子研究中心的大型强子对撞机(LHC)的高能质子-质子碰撞，我们可以瞬间打开一扇通往已知最高能量的窗口，同时探测这些微小的尺寸，提供了在原本无法进入的区域直接研究基础物理的机会。这项工作包括堪萨斯大学(KU)的一项研究计划，该计划利用大型强子对撞机CMS实验的现有和未来数据，在这些高能尺度上面对公开问题。罗根的KU小组是大型强子对撞机上紧凑型Muon螺线管(CMS)实验的成员，该项目的大部分活动都与这一努力有关。该项目有两个主要组成部分：对CMS收集的数据进行分析和解释，以及CMS探测器本身。在这两种情况下，都有一些元素专注于已经收集的数据和实验的操作，另一些元素则期待着分析数据的新方法和探测器的未来升级。这项工作的重要部分是对与新对称和暗物质有关的标准模型以外的物理进行新的全面搜索，其中包括开发一种新的分析范式，将无监督机器学习的元素纳入对新物理的搜索中，并计划用现有的CMS数据集进行概念验证演示。该小组还在为CMS开发新的、精确的计时探测器，这将为事件重建引入一个额外的维度，促进涉及长寿命粒子的新物理的搜索。该小组还在研究现有CMS电磁量热仪的定时重建性能，目的是通过改进的重建算法来缓解分辨率的退化。KU小组还专注于两项针对公众和KU学术界的倡议。与昆士兰大学的本科生一起，该组织正在开发“梦幻物理”推广项目，在该项目中，学生们可以与由精选的粒子物理实验组成的团队以在线梦幻运动为灵感的形式进行竞争。该小组还开发了一个跨部门的“机器学习”论坛，其中包括讲座、教程和研讨会，为有兴趣将当代机器学习纳入他们的研究的KU学术界成员提供服务。该组织还积极通过公开演讲和外展活动传播其研究成果。这一奖项反映了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。

A complete understanding of the physics describing interactions at the smallest, subatomic lengths is elusive. Through the high-energy proton-proton collisions of CERN’s Large Hadron Collider (LHC), we can momentarily open a window to the highest energies known and simultaneously probe these tiny sizes, providing the opportunity to directly study fundamental physics in an otherwise inaccessible regime. This work includes a program of research at the University of Kansas (KU) which confronts open questions at these high-energy scales using existing and future data from the CMS experiment at the LHC. Rogan’s KU group are members of the Compact Muon Solenoid (CMS) experiment at the LHC, with most of the activities included in this project related to this effort. The project has two primary components: the analysis and interpretation of data collected by CMS, and the CMS detector itself. In both cases, there are elements that focus on already collected data and the operation of the experiment, with others looking forward to new approaches to analyzing data and future upgrades to the detector. A significant portion of this work is for a new comprehensive search for physics beyond the Standard Model related to new symmetries and Dark Matter, which includes development of a novel analysis paradigm that incorporates elements of unsupervised machine learning into searches for new physics, with proof-of-concept demonstrations planned with the existing CMS dataset. The group is also developing new, precision timing detectors for CMS, which will introduce an additional dimension to event reconstruction, facilitating searches for new physics involving long-lived particles. The group is also studying the timing reconstruction performance of the existing CMS electromagnetic calorimeter, with the goal of mitigating degradations in resolution through an improved reconstruction algorithm.The KU group is also focused on two initiatives targeting the public and the KU academic community. With KU undergraduates, the group is developing the "Fantasy Physics" outreach project, where students can compete with teams comprised of selected particle physics experiments in an online fantasy-sports-inspired format. The group also developed an inter-departmental "Learning Machine Learning" forum, which includes lectures, tutorials, and seminars serving members of the KU academic community who are interested in incorporating contemporary machine learning in their research. The group is also active in disseminating its research through public talks and outreach events.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.