Experimental Particle Physics

该奖项将为在欧洲核子研究中心(CERN)的大型强子对撞机(LHC)上从事ATLAS实验的一个小组提供支持，CERN是一个位于瑞士日内瓦的粒子物理实验室。大型强子对撞机和大型粒子探测器ATLAS是利用美国国家科学基金会和世界各地其他机构的资金作为基础科学工具建造的。他们的主要目标之一是找到希格斯玻色子，这是历史上成功的“标准模型”(SM)中的最后一个粒子，它解释了宇宙中形成物质的已知粒子的存在和相互间的作用力。这一努力取得了成功。实验的下一步是寻找标准模型(BSM)以外的物理学证据，例如，可以解释神秘的“暗物质”的存在，这种物质构成了宇宙的如此大的质量。大型强子对撞机目前正处于第二次运行中，能量几乎是之前探索的两倍，事件样本也显著增加。在这种更高的能量和更高的事件统计数据下，BSM物理的证据可能会出现。从分析上看，新墨西哥州小组正在使用ATLAS探测器搜索BSM物理。这些研究包括对中性B介子罕见地衰变为两个介子的分支比的确定的ATLAS测量。这种测量很有趣，因为来自大型强子对撞机的早期数据产生了一个与标准模型的预测相一致的张力值，任何显著的偏差都是新的BSM物理学的先兆。在2021年开始的即将到来的数据运行中，该小组正在研究软件基础设施，以探测轻子味道反常的迹象。从技术上讲，新墨西哥州小组领导了一项对ATLAS像素跟踪探测器的研究，该研究表征了该探测器在下一次运行结束时的性能能力，并为这个时代的像素操作提供了指导方针。像素探测器对研究寿命短的粒子至关重要，例如该小组感兴趣的中性BS介子，以及更广泛的ATLAS发现科学计划。新墨西哥州小组研究活动的更广泛影响包括机器学习方面的进展。开发这种分析工具是新墨西哥州数据分析的内在要求，该小组的初级成员正在成为这一领域的权威，并将能够培训其他人。机器学习在虚拟助手、医疗诊断、DNA分类和其他研究领域都有应用，在这些领域，微弱信号必须从广泛的背景中敏感地分离出来。该小组的研究是他们赞助的QuarkNet项目的跳板，包括大型强子对撞机大师班、教师实验室研究和新墨西哥州科学设施的技术参观。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。

This award will provide support to a group working on the ATLAS experiment at the Large Hadron Collider (LHC) at CERN, a particle physics laboratory in Geneva, Switzerland. The LHC machine and ATLAS, a large particle detector facility, were built as basic science tools using funds from NSF and other agencies around the world. One of their primary objectives was to find the Higgs Boson, the last particle in the historically successful "Standard Model" (SM) that accounts for so much of the existence of, and forces between, known particles forming the matter in the universe. This effort has been successful. The next step in the experiments is to look for evidence for physics Beyond the Standard Model (BSM) that might, for instance, account for the presence of the mysterious "Dark Matter" that makes up so much of the mass of the universe. The LHC is currently in the midst of Run 2, at almost twice the energy explored earlier and with significantly increased event samples. It is possible that evidence for BSM physics could emerge at this higher energy and with the higher event statistics. Analytically, the New Mexico group is searching for BSM physics using the ATLAS detector. These studies include a definitive ATLAS measurement of the branching ratio of the rare decay of the neutral Bs meson into two muons. This measurement is interesting because the early data from LHC yielded a value in tension with predictions of the Standard Model, and any significant deviations are a harbinger of new BSM physics. In the upcoming data run which begins in 2021, the group is working on software infrastructure to probe for hints of lepton flavor anomaly. Technically, the New Mexico group leads a study of the ATLAS Pixel tracking detector that characterizes the performance capabilities of this detector through the end of the next run and yields guidelines for Pixel operations in this era. The pixel detector is critical to the studies of particles with short lifetimes such as the neutral Bs mesons of interest to the group, as well as for the broader ATLAS program of discovery science.The broader impacts of the New Mexico group's research activities include advances in machine learning. The development of such analytical tools is intrinsic to the New Mexico data analyses, and the group's junior members are becoming authoritative in this domain and will be able to train others. Machine learning has applications in virtual assistants, medical diagnosis, DNA classification, and other research domains where weak signals must be sensitively separated from extensive background. The group's research serves as a springboard for QuarkNet projects that they sponsor, including LHC masterclasses, laboratory research for teachers, and technical tours of New Mexico scientific facilities.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.