NSF-BSF: Elementary Particle Physics with ATLAS

NSF-BSF：使用 ATLAS 进行基本粒子物理

• 批准号: 2111244
• 负责人: Allen Mincer
• 金额: $ 173万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2111244&HistoricalAwards=false
• 关键词: NSF; BSF; Elementary; Particle; Physics

This award will provide support for the NYU 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 experiments are currently in the midst of analyzing data from 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 from the current run and by means of further upgrades of the LHC and ATLAS to follow. The NYU group will be studying Higgs decays, searching for evidence of supersymmetry and exotic new states of matter through several approaches, including the reaction process known as Vector Boson Fusion, and will be developing novel approaches to the reconstruction and study of high energy Jets. NYU will partner with the Weizmann Institute of Science through support from the US-Israel Binational Science Foundation program to search for the decays of Higgs boson decays to charm quark pairs, through heavy flavor tagging. Here the joint NYU-Weizmann effort will exploit advanced machine learning techniques to identify and select such challenging final states in Higgs decay. Technical projects include improvements and refinements of the ATLAS trigger for missing energy, a key variable in the searches for new physics, and track triggering, an essential technique for dealing with reconstruction of events in very high rate collisions, which are endemic at the LHC. The group also helps to lead a smaller experimental effort called milliQan, whose objective is to search for fractionally charged particles that might be produced at the LHC. The group has a strong Machine Learning effort to further the precision of the Higgs measurements and to clarify BSM discovery in channels such as new Higgs particles in the so-called Hidden Valley suggested by string theory.The NYU group's broader impacts efforts are extensive, including a collaboration with the National Museum of Mathematics and Brookhaven National Laboratory designed to bring to the general public the excitement of particle physics and a better understanding of how a basic understanding of statistics can be used to assess conclusions that might be drawn from experiments or medical tests. The group's use of machine learning and simulation-based inference will continue to impact scientific areas beyond particle physics including neuroscience, epidemiology, and algorithmic fairness, and to foster collaboration between academia and industry. Additionally, the analytical projects of the group, which include statistical applications, machine learning, and analysis preservation tools and techniques, can be extended to fields outside of physics, and young researchers supported under this program will have training in such innovative and cross-cutting techniques.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.

该奖项将为纽约大学在瑞士日内瓦粒子物理实验室 CERN 大型强子对撞机 (LHC) 进行 ATLAS 实验的团队提供支持。 LHC 机器和 ATLAS（大型粒子探测器设施）是利用 NSF 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，该模型解释了形成宇宙物质的已知粒子的存在以及它们之间的作用力。这项努力取得了成功。实验的下一步是寻找标准模型（BSM）之外的物理学证据，例如，这些证据可能解释构成宇宙大部分质量的神秘“暗物质”的存在。 LHC 实验目前正在分析第二轮的数据，其能量几乎是之前探索的两倍，并且事件样本显着增加。 BSM 物理学的证据可能会在这种更高的能量下出现，并通过当前运行的更高事件统计数据以及随后 LHC 和 ATLAS 的进一步升级来出现。纽约大学小组将研究希格斯衰变，通过多种方法寻找超对称性和奇异的新物质态的证据，包括称为矢量玻色子聚变的反应过程，并将开发新的方法来重建和研究高能喷流。纽约大学将与魏茨曼科学研究所合作，在美国-以色列两国科学基金会项目的支持下，寻找希格斯玻色子衰变的衰变，通过重口味标签来吸引夸克对。纽约大学和魏茨曼的联合研究将利用先进的机器学习技术来识别和选择希格斯衰变中此类具有挑战性的最终状态。技术项目包括对 ATLAS 丢失能量触发器的改进和细化，这是寻找新物理学的一个关键变量，以及轨道触发，这是一种处理极高频率碰撞事件重建的基本技术，这种情况在大型强子对撞机中很常见。该小组还帮助领导了一项名为 milliQan 的小型实验项目，其目标是寻找大型强子对撞机可能产生的分数带电粒子。该小组在机器学习方面做出了强有力的努力，以提高希格斯粒子测量的精度，并澄清在弦理论所建议的所谓隐藏谷中的新希格斯粒子等通道中的 BSM 发现。纽约大学小组的更广泛的影响努力是广泛的，包括与国家数学博物馆和布鲁克海文国家实验室合作，旨在让公众了解粒子物理学的乐趣，并更好地了解如何利用对统计学的基本了解来评估可能从实验或医学测试中得出的结论。该小组对机器学习和基于模拟的推理的使用将继续影响粒子物理学以外的科学领域，包括神经科学、流行病学和算法公平性，并促进学术界和工业界之间的合作。此外，该小组的分析项目，包括统计应用、机器学习、分析保存工具和技术，可以扩展到物理学以外的领域，该项目支持的年轻研究人员将接受此类创新和交叉领域的培训。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Combination of searches for invisible decays of the Higgs boson using 139 fb−1 of proton-proton collision data at s=13 TeV collected with the ATLAS experiment

• DOI: 10.1016/j.physletb.2023.137963
• 发表时间: 2023-01
• 期刊: Physics Letters B
• 影响因子: 4.4
• 作者: Atlas Collaboration

Search for dark matter produced in association with a dark Higgs boson decaying into W+W− in the one-lepton final state at $$ \sqrt{s} $$ = 13 TeV using 139 fb−1 of pp collisions recorded with the ATLAS detector

使用 139 fbâ1 记录的 pp 碰撞，在 $$ sqrt{s} $$ = 13 TeV 处搜索与暗希格斯玻色子衰变成 W Wâ 的单轻子最终状态相关的暗物质。

• DOI: 10.1007/jhep07(2023)116
• 发表时间: 2023
• 期刊: Journal of High Energy Physics
• 影响因子: 5.4
• 作者: Aad, G.;Abbott, B.;Abbott, D. C.;Abeling, K.;Abidi, S. H.;Aboulhorma, A.;Abramowicz, H.;Abreu, H.;Abulaiti, Y.;Abusleme Hoffman, A. C.
• 通讯作者: Abusleme Hoffman, A. C.

Observation of electroweak production of two jets in association with an isolated photon and missing transverse momentum, and search for a Higgs boson decaying into invisible particles at 13 $$\text {TeV}$$ with the ATLAS detector

观察与孤立光子和缺失横向动量相关的两个射流的电弱产生，并使用 ATLAS 探测器寻找在 13 $$ ext {TeV}$$ 处衰变成不可见粒子的希格斯玻色子

• DOI: 10.1140/epjc/s10052-021-09878-z
• 发表时间: 2022
• 期刊: The European Physical Journal C
• 作者: Aad G

Search for heavy, long-lived, charged particles with large ionisation energy loss in pp collisions at $$ \sqrt{s} $$ = 13 TeV using the ATLAS experiment and the full Run 2 dataset

使用 ATLAS 实验和完整的 Run 2 数据集，在 $$ sqrt{s} $$ = 13 TeV 的 pp 碰撞中搜索具有大量电离能量损失的重、寿命长的带电粒子

• DOI: 10.1007/jhep06(2023)158
• 发表时间: 2023
• 期刊: Journal of High Energy Physics
• 影响因子: 5.4
• 作者: Aad, G.;Abbott, B.;Abbott, D. C.;Abed Abud, A.;Abeling, K.;Abhayasinghe, D. K.;Abidi, S. H.;Aboulhorma, A.;Abramowicz, H.;Abreu, H.
• 通讯作者: Abreu, H.

The Forward Physics Facility at the High-Luminosity LHC

• DOI: 10.1088/1361-6471/ac865e
• 发表时间: 2022-03
• 期刊: Journal of Physics G: Nuclear and Particle Physics
• 作者: Jonathan L. Feng;F. Kling;M. Reno;J. Rojo;D. Soldin;L. Anchordoqui;J. Boyd;A. Ismail;L. Harland–La