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.

非技术总结最近在控制量子设备能力方面的进展为研究由许多相互作用的粒子(如量子材料)组成的量子系统而产生的丰富而复杂的物理现象带来了新的方法。一种有希望的方法是量子模拟，在这种方法中，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的系统的物理。尽管有希望，但目前的量子设备仍然远非理想，因为它们的操作噪音很大，控制它们的能力也不完美。核心挑战是(I)了解如何以最佳方式利用这些设备，以探索尽可能多的物理学财富，尽管存在这些限制；以及(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，首席研究人员建议通过理论上的新想法来解决这些挑战，利用量子信息科学和机器学习的最新进展。首席研究人员将在追求这一研究目标的同时，开展一系列不同的外联活动，促进高中和本科生的研究，吸引有才华的学生，并将他们培养成下一代科学家。技术总结了解、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稳健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对任意可观测或非局部性质的高级测量。由于当前设备的量子控制的局限性，这些能力在其他方面是困难的，需要新的理论想法。利用改进的能力，研究团队将利用现有的量子模拟器来探索奇异的新兴现象，例如去受限的量子临界。非受限量子临界性可能在理解高温超导体和其他量子材料方面发挥重要作用。使用量子模拟器成功地观测到奇异的紧急现象将使我们能够对它们进行更详细的实验研究，加深我们对量子相和相变的理解。研究活动的后半部分介绍了使用量子信息论的语言来研究量子物质的新视角。具体地说，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，并调查这些新算法在计算能力方面的根本限制。这将为表征量子物质的性质提供新的方法，例如区分两个不同相的计算难度。成功的结果将在不同的物理科学学科之间建立严格的联系，如理论物理中的重整化组和误差修正信息论。该奖项由材料研究部和数学和物理科学局内的物理部共同提供资金支持。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

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