CAREER: New Algorithms to Simulate Ultracold Matter Out of Equilibrium and Redefine the Low-Temperature Frontier

职业：模拟失衡超冷物质并重新定义低温前沿的新算法

• 批准号: 1848304
• 负责人: Kaden Hazzard
• 金额: $ 49.98万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1848304&HistoricalAwards=false
• 关键词: CAREER; New; Algorithms; Simulate; Ultracold

Understanding and controlling the dynamics of quantum systems which are out of equilibrium is a fundamental challenge for science in the 21st century. Systems which are not in equilibrium display phenomena that "break the rules" that govern equilibrium phases. Such phenomena are intrinsically interesting and potentially useful for applications. Gases that have been cooled to nano-Kelvin temperatures provide an exciting new platform for the study of non-equilibrium systems. Experiments with ultracold gases flexibly manipulate and image matter using unique and precise tools provided by optics. While such experiments are rapidly advancing, new theoretical techniques are also needed to aid the investigations. This project will develop numerical algorithms to solve a range of previously intractable, experimentally important problems. The new algorithms will be used to design experimental schemes to cool ultracold matter to even lower temperatures (a grand challenge of the field), thereby redefining the low-temperature frontier. This would realize long-sought and previously inaccessible phases of matter, including phases which simulate high-temperature superconductivity. The project will train graduate, undergraduate, and high school students in the use of the new algorithms, facilitating their future use in other areas of non-equilibrium physics. In addition, publicly accessible educational materials will be developed which unify concepts in non-equilibrium dynamics that are used regularly by physicists, but which are taught only inexplicitly, if at all, in typical physics curricula. These lessons will include videos, reading, and exercises that can be used for self-study or in a classroom, and will include multiple versions, each designed for students of different levels of expertise, from non-physicists to practicing researchers.This project will develop two algorithms, a dynamical numerical linked cluster expansion (NLCE) and a cluster truncated Wigner approximation (cl-TWA), which potentially can accurately calculate important ultracold dynamics in minutes on a laptop for cases that are currently inaccessible to even the largest supercomputers. The algorithms achieve their accuracy by recognizing and exploiting special physical structures that underlie many ultracold dynamics experiments. The project will focus on applying these new algorithms to design and optimize new protocols for cooling ultracold matter that fall into three categories: entropy management, adiabatic preparation, and engineered dissipation. It will also partner with experiments to address fundamental questions of nonequilibrium physics, selected to align the strengths of the algorithms with emerging experimental directions.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.

理解和控制处于非平衡状态的量子系统的动力学是21世纪科学面临的根本挑战。不处于平衡状态的系统表现出“打破规则”的现象，这些规则支配着平衡阶段。这种现象本质上很有趣，并有潜在的应用价值。已经冷却到纳米开尔文温度的气体为研究非平衡体系提供了一个令人兴奋的新平台。超冷气体实验使用光学提供的独特而精确的工具灵活地操纵物质并对其成像。虽然这样的实验正在迅速推进，但也需要新的理论技术来帮助研究。这个项目将开发数值算法来解决一系列以前难以解决的实验上重要的问题。新的算法将被用来设计实验方案，将超冷物质冷却到更低的温度(这是该领域的一个重大挑战)，从而重新定义低温前沿。这将实现人们长期寻求的、以前无法获得的物质相，包括模拟高温超导的相。该项目将培训研究生、本科生和高中生使用新的算法，促进它们未来在非平衡物理的其他领域中的使用。此外，还将开发可公开获取的教材，将物理学家经常使用的非平衡动力学中的概念统一起来，但在典型的物理课程中只不明确地教授，如果有的话。这些课程将包括可用于自学或在课堂上使用的视频、阅读和练习，并将包括多个版本，每个版本都是为不同专业水平的学生设计的，从非物理学家到实践研究人员。这个项目将开发两种算法，动态数值链接星系团扩展(NLCE)和星系团截断维格纳近似(CL-TWA)，对于目前即使是最大的超级计算机也无法访问的情况，它可能在笔记本电脑上在几分钟内准确计算重要的超冷动力学。这些算法通过识别和利用作为许多超冷动力学实验基础的特殊物理结构来实现其准确性。该项目将专注于应用这些新算法来设计和优化冷却超冷物质的新协议，这些协议分为三类：熵管理、绝热准备和工程耗散。它还将与实验合作，解决非平衡物理的基本问题，选择这些问题是为了使算法的优势与新兴的实验方向保持一致。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。

项目成果

Topological correlations in three-dimensional classical Ising models: An exact solution with a continuous phase transition

• DOI: 10.1103/physrevresearch.5.013086
• 发表时间: 2022-02
• 期刊: Physical Review Research
• 影响因子: 4.2
• 作者: Zhiyuan Wang;K. Hazzard

Thermodynamics and magnetism in the two-dimensional to three-dimensional crossover of the Hubbard model

• DOI: 10.1103/physreva.102.033340
• 发表时间: 2020-09
• 期刊: Physical Review A
• 影响因子: 2.9
• 作者: E. Ibarra-García-Padilla;R. Mukherjee;R. Hulet;K. Hazzard;T. Paiva;R. Scalettar

Multi-round QAOA and advanced mixers on a trapped-ion quantum computer

• DOI: 10.1088/2058-9565/ac91ef
• 发表时间: 2022-01
• 期刊: Quantum Science & Technology
• 影响因子: 6.7
• 作者: Yingyue Zhu;Zewen Zhang;Bhuvanesh Sundar;Alaina M. Green;C. Huerta Alderete;N. Nguyen;K. Hazzard;N. Linke

Universal thermodynamics of an SU(N) Fermi-Hubbard model

• DOI: 10.1103/physreva.104.043316
• 发表时间: 2021-08
• 期刊: Physical Review A
• 影响因子: 2.9
• 作者: Eduardo Ibarra-Garc'ia-Padilla;S. Dasgupta;Hao-Tian Wei;S. Taie;Y. Takahashi;R. Scalettar;K. Hazzard

Bounding the finite-size error of quantum many-body dynamics simulations

限制量子多体动力学模拟的有限尺寸误差

• DOI: 10.1103/physrevresearch.3.l032047
• 发表时间: 2021
• 期刊: Physical Review Research
• 影响因子: 4.2
• 作者: Wang, Zhiyuan;Foss-Feig, Michael;Hazzard, Kaden R.
• 通讯作者: Hazzard, Kaden R.