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.

该奖项将为在瑞士日内瓦粒子物理实验室CERN的大型强子对撞机（LHC）上进行ATLAS实验的纽约大学小组提供支持。大型强子对撞机和大型粒子探测器设施ATLAS是利用NSF和世界各地其他机构的资金建造的基础科学工具。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）中的最后一种粒子，该模型解释了宇宙中形成物质的已知粒子的存在及其之间的作用力。这一努力取得了成功。实验的下一步是寻找超越标准模型（BSM）的物理学证据，例如，可以解释构成宇宙质量的神秘“暗物质”的存在。LHC实验目前正在分析运行2的数据，其能量几乎是早期探索的两倍，并且事件样本显著增加。BSM物理学的证据可能会在更高的能量和更高的事件统计数据中出现，并通过LHC和ATLAS的进一步升级来实现。纽约大学小组将研究希格斯衰变，通过几种方法寻找超对称性和奇异的新物质状态的证据，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射流。纽约大学将与魏茨曼科学研究所合作，通过美国-以色列两国科学基金会项目的支持，通过重口味标记来寻找希格斯玻色子衰变的衰变，以吸引夸克对。在这里，纽约大学和魏茨曼的联合努力将利用先进的机器学习技术来识别和选择希格斯衰变中具有挑战性的最终状态。技术项目包括改进和完善ATLAS触发器，用于寻找新物理学的关键变量，以及轨道触发器，这是处理LHC特有的极高速碰撞事件重建的基本技术。该小组还帮助领导了一项名为milliQan的小型实验工作，其目标是寻找可能在LHC中产生的部分带电粒子。该小组有一个强大的机器学习的努力，以进一步希格斯测量的精度，并澄清BSM发现的渠道，如新的希格斯粒子在所谓的隐藏谷建议弦理论。纽约大学小组的更广泛的影响的努力是广泛的，包括与国家数学博物馆和布鲁克海文国家实验室的合作，旨在为公众带来粒子物理学的兴奋以及更好地理解如何利用对统计学的基本理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，机器学习和分析保存工具和技术，可以扩展到物理学以外的领域，该计划支持的年轻研究人员将接受这种创新和交叉的培训，该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值进行评估来支持和更广泛的影响审查标准。

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.

Search for heavy resonances decaying into a Z or W boson and a Higgs boson in final states with leptons and b-jets in 139 fb−1 of pp collisions at $$ \sqrt{s} $$ = 13 TeV with the ATLAS detector

使用 ATLAS 探测器在 $$ sqrt{s} $$ = 13 TeV 处的 139 fbâ1 pp 碰撞中寻找衰变为最终态 Z 或 W 玻色子和希格斯玻色子的重共振

• DOI: 10.1007/jhep06(2023)016
• 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.