RAISE-QAC-QSA: Open Quantum Systems on Noisy Intermediate-Scale Quantum Devices

RAISE-QAC-QSA：噪声中等规模量子设备上的开放量子系统

基本信息

批准号：
2037783
负责人：
Prineha Narang
金额：
$ 40万
依托单位：
Harvard University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-01 至 2023-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2037783&HistoricalAwards=false
关键词：
RAISE QAC QSA Open Quantum

项目摘要

Non-technical Summary: Open quantum systems are ubiquitous in chemistry, physics, and materials science, from photosynthetic light-harvesting chromophores and catalytic centers to quantum defects in solid-state materials. More generally, open quantum systems provide a framework to consider the structure and dynamics of a system that has significant interactions with its environment. Despite the fundamental and technological importance of open systems, classical approaches remain computationally limited. Catalyzed by recent discoveries in quantum computation, the team proposes to use quantum resources (noisy intermediate-scale quantum, or NISQ, devices) to describe open quantum systems. A new quantum algorithm for such open systems, one that scales favorably on quantum devices, would be transformative beyond the quantum-information community. In the larger context of quantum simulation, accurate and efficient computation of molecules and materials is one of the most important outstanding problems in science and engineering. The advent of quantum computing raises new possibilities for eliminating the exponential complexity that has stymied simulation of strongly correlated and open quantum systems on high-performance classical computers. The proposed quantum algorithm will leverage the power of quantum computing to solve a class of physically-relevant problems and overcome inherent limitations of the exponential scaling of many-electron quantum theory in classical approaches. To advance quantum information science and technology, this program will pursue parallel approaches to broader impact: (i) Education, with a Quantum Computing for Open Quantum Systems course and online-module across Harvard and University of Chicago. This course would leverage access to small-scale quantum devices. PI Narang has already incorporated such ideas into an undergraduate course with devices at IBM; (ii) Outreach Programs emphasizing recruitment and inclusion of underrepresented groups in STEM to the field of Quantum Algorithms via connections with Boston's Museum of Science; and (iii) a close engagement with industry partners and startups in the area of quantum information for chemistry and physics.Technical Summary: The PIs propose a dedicated and multidisciplinary RAISE program between quantum chemistry, theoretical computer science, and computational condensed matter physics in the context of NSF's Quantum Algorithm Challenge. A new quantum algorithm for such open systems, one that scales favorably on quantum devices, would be transformative beyond the quantum-computing community. The team notes the timeliness of the proposed approach: as recently as 2019, researchers at Google and NASA presented heuristic benchmarking showing that their 54-qubit superconducting circuit quantum computer performs certain sampling algorithms much faster than classical computers, even though these algorithms have no known practical application. This advance sparked the research for practical quantum algorithms that solve relevant problems in chemistry and physics on near-term devices. The proposed quantum algorithm will leverage the power of quantum computation to solve a class of physically-relevant problems and overcome inherent limitations of the exponential scaling of many-electron quantum theory in classical approaches. The proposed effort will be organized in the following closely connected, interdisciplinary Thrusts: 1) Accelerated quantum algorithms for Non-Markovian dynamics with the ensemble-of-Lindbladian-trajectories (ELT) method on NISQ devices, and 2) Demonstration of the quantum ELT algorithm to capture non-trivial electron and nuclear dynamics in strongly correlated condensed-phase systems with non-exponential scaling. For weakly coupled Markovian systems, the Lindblad formalism gives an efficient and accurate depiction of the dynamics, though it places severe constraints on the size of the system. This program will build on the ELT method with the quantum algorithm retaining significant advantages of its classical counterpart, including an exact treatment of non-Markovian dynamics and complete positivity of the density matrices. Multidisciplinary discoveries and methods from the PIs spanning computational and condensed matter physics, theoretical chemistry, and theoretical quantum information are essential to the vision and goals of this program, well-suited for the NSF RAISE program mandate.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.

非技术摘要：开放量子系统在化学、物理和材料科学中无处不在，从光合作用光捕获发色团和催化中心到固态材料中的量子缺陷。更一般地说，开放量子系统提供了一个框架来考虑与其环境有显着相互作用的系统的结构和动力学。尽管开放系统具有基础和技术重要性，但经典方法在计算上仍然有限。在量子计算最新发现的推动下，该团队建议使用量子资源（嘈杂的中尺度量子或 NISQ 设备）来描述开放量子系统。针对此类开放系统的一种新量子算法，可以在量子设备上顺利扩展，将给量子信息界带来变革。在更大的量子模拟背景下，分子和材料的精确高效计算是科学和工程中最重要的突出问题之一。量子计算的出现为消除指数复杂性提供了新的可能性，这种复杂性阻碍了在高性能经典计算机上模拟强相关和开放的量子系统。所提出的量子算法将利用量子计算的力量来解决一类与物理相关的问题，并克服经典方法中多电子量子理论指数缩放的固有局限性。为了推进量子信息科学和技术，该计划将寻求并行方法以产生更广泛的影响：（i）教育，包括哈佛大学和芝加哥大学的开放量子系统量子计算课程和在线模块。本课程将利用小型量子设备。 PI Narang 已经将这些想法融入到 IBM 的设备本科生课程中； (ii) 外展计划，强调通过与波士顿科学博物馆的联系，招募和纳入 STEM 中代表性不足的群体进入量子算法领域； (iii) 与化学和物理量子信息领域的行业合作伙伴和初创公司密切合作。技术摘要：PI 提议在量子化学、理论计算机科学和计算凝聚态物理之间建立一个专门的多学科 RAISE 项目。 NSF 量子算法挑战赛的背景。针对此类开放系统的一种新量子算法，可以在量子设备上顺利扩展，将给量子计算界带来变革。该团队注意到所提出方法的及时性：就在 2019 年，谷歌和 NASA 的研究人员提出了启发式基准测试，表明他们的 54 量子位超导电路量子计算机执行某些采样算法的速度比传统计算机快得多，尽管这些算法没有已知的数据实际应用。这一进展引发了对实用量子算法的研究，这些算法可以解决近期设备上的化学和物理相关问题。所提出的量子算法将利用量子计算的力量来解决一类与物理相关的问题，并克服经典方法中多电子量子理论指数缩放的固有局限性。拟议的工作将按照以下紧密相连的跨学科主旨进行组织：1）在 NISQ 设备上使用林布拉迪轨迹集合（ELT）方法加速非马尔可夫动力学量子算法，以及 2）量子 ELT 的演示算法来捕获具有非指数缩放的强相关凝聚相系统中的非平凡电子和核动力学。对于弱耦合马尔可夫系统，林德布拉德形式主义给出了动态的有效和准确的描述，尽管它对系统的大小提出了严格的限制。该程序将建立在 ELT 方法的基础上，量子算法保留了其经典算法的显着优点，包括对非马尔可夫动力学的精确处理和密度矩阵的完全正性。 PI 的跨学科发现和方法涵盖计算和凝聚态物理、理论化学和理论量子信息，对于该计划的愿景和目标至关重要，非常适合 NSF RAISE 计划的任务。该奖项反映了 NSF 的法定使命，并具有通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。