CAREER: Probing Quantum Matter using Programmable Quantum Simulators

职业：使用可编程量子模拟器探测量子物质

• 批准号: 2237244
• 负责人: Soonwon Choi
• 金额: $ 50万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-15 至 2028-02-29
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2237244&HistoricalAwards=false
• 关键词: CAREER; Probing; Quantum; Matter; using

NONTECHNICAL SUMMARYRecent advances in the ability to control quantum devices are ushering in new approaches to study the rich and complex physics that emerges from quantum systems of many interacting particles such as quantum materials. One promising approach is quantum simulation, in which a quantum device with several tunable parameters is carefully manipulated to emulate the physics of various other systems of interest. Despite their promise, present-day quantum devices are still far from ideal, as their operations are noisy and the ability to control them is imperfect. The central challenges are (i) to understand how to optimally exploit such devices to explore the largest wealth of physics possible despite the restrictions and (ii) to extract physically meaningful information from potentially noisy and limited data. Here, the principal investigator proposes to address these challenges through novel ideas from theory leveraging recent advances in quantum information science and machine learning. The principal investigator will pursue this research goal in parallel with a diverse set of outreach activities fostering high-school and undergraduate student research, attracting talented students, and preparing them as the next generation scientists.TECHNICAL SUMMARYUnderstanding, controlling, and harnessing the quantum dynamics of increasingly complex many-body systems are among the most important goals of quantum science research. The first half of the research component aims to develop practical methods to achieve these goals, focusing on existing experimental capabilities. In particular, the PI and his team will develop methods to robustly engineer effective Hamiltonians of a given quantum hardware by means of optimized pulsed controls and to perform advanced measurements of arbitrary observables or nonlocal properties by utilizing information scrambling. These capabilities are otherwise difficult owing to limitations in quantum control of current devices, calling for novel theory ideas. Leveraging improved capabilities, the research team will pursue probing exotic emergent phenomena such as deconfined quantum criticality using existing quantum simulators. Deconfined quantum criticality may plan an important role in understanding high temperature superconductors and other quantum materials. Successful observations of exotic emergent phenomena using quantum simulators will allow the experimental investigations of them in greater detail, deepening our understanding of quantum phases and phase transitions. The second half of the research activities introduces a new perspective to study quantum matter using the language of quantum information theory. Specifically, the research team will develop quantum and classical algorithms to efficiently extract important information such as the phase of quantum matter from experimental data and investigate the fundamental limitations in computational power of these new algorithms. This will provide new ways to characterize the properties of quantum matter such as the computational hardness of distinguishing two different phases. Successful outcomes will establish a rigorous connection between different disciplines of physical sciences such as renormalization group in theoretical physics and error corrections information theory.This award is jointly supported through funds contributed by the Division of Materials Research and the Physics Division within the Mathematical and Physical Sciences Directorate.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.

非技术性总结控制量子设备能力的最新进展正在引入新的方法来研究从许多相互作用粒子（如量子材料）的量子系统中出现的丰富而复杂的物理学。一种很有前途的方法是量子模拟，其中具有几个可调参数的量子设备被仔细操纵，以模拟各种其他感兴趣系统的物理特性。尽管它们有希望，但目前的量子设备仍然远未达到理想状态，因为它们的操作是嘈杂的，并且控制它们的能力是不完美的。核心挑战是：（i）了解如何最佳地利用这些设备，以探索尽可能丰富的物理学，尽管有限制;（ii）从潜在的噪声和有限的数据中提取有物理意义的信息。在这里，首席研究员建议通过利用量子信息科学和机器学习的最新进展的理论中的新想法来解决这些挑战。首席研究员将追求这一研究目标的同时，还将开展各种推广活动，促进高中和本科生的研究，吸引有才华的学生，并为他们成为下一代科学家做好准备。技术概述理解、控制和利用日益复杂的多体系统的量子动力学是量子科学研究的最重要目标之一。研究部分的前半部分旨在开发实现这些目标的实用方法，重点是现有的实验能力。特别是，PI和他的团队将开发方法，通过优化的脉冲控制来鲁棒地设计给定量子硬件的有效哈密顿量，并通过利用信息加扰来执行任意可观测量或非局部属性的高级测量。由于当前设备的量子控制的限制，这些能力是困难的，需要新的理论思想。利用改进的能力，研究团队将继续探索奇异的涌现现象，例如使用现有的量子模拟器去限制量子临界性。量子临界性的非限制化对于理解高温超导体和其他量子材料有着重要的意义。利用量子模拟器成功地观测奇异的涌现现象，将允许对它们进行更详细的实验研究，加深我们对量子相位和相变的理解。研究活动的后半部分引入了一个新的视角，使用量子信息理论的语言来研究量子物质。具体而言，研究团队将开发量子和经典算法，以有效地从实验数据中提取量子物质的相位等重要信息，并研究这些新算法计算能力的基本限制。这将提供新的方法来表征量子物质的性质，例如区分两个不同相位的计算难度。成功的成果将在物理科学的不同学科之间建立严格的联系，如理论物理学中的重整化群和误差校正信息理论。该奖项由数学和物理科学理事会的材料研究部和物理部共同资助。该奖项反映了NSF的法定使命，并通过评估被认为值得支持使用基金会的知识价值和更广泛的影响审查标准。

项目成果

Complete Hilbert-Space Ergodicity in Quantum Dynamics of Generalized Fibonacci Drives

广义斐波那契驱动量子动力学中的完整希尔伯特空间遍历性

• DOI: 10.1103/physrevlett.131.250401
• 发表时间: 2023
• 期刊: Physical Review Letters
• 影响因子: 8.6
• 作者: Pilatowsky-Cameo, Saúl;Dag, Ceren B.;Ho, Wen Wei;Choi, Soonwon
• 通讯作者: Choi, Soonwon