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

非技术总结：开放量子系统在化学、物理和材料科学中无处不在，从光合作用的光收集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环境有重要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上的重要性，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（嘈杂的中等规模量子或NISQ设备）来描述开放量子系统。对于这样的开放系统，一种新的量子算法，一种在量子设备上有利扩展的算法，将会超越量子信息社区。在更大的量子模拟背景下，分子和材料的精确和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物理相关问题，并克服经典方法中多电子量子理论的指数缩放的固有局限性。为了推进量子信息科学和技术，该项目将采用并行方法来产生更广泛的影响：(i)教育，在哈佛大学和芝加哥大学开设开放量子系统的量子计算课程和在线模块。本课程将利用小规模量子设备。皮·纳朗（PI Narang）已经将这些想法融入了IBM的一门本科生课程中；（ii）外展计划，强调通过与波士顿科学博物馆的联系，在量子算法领域招募和包容STEM中代表性不足的群体；（三）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。技术总结：在NSF量子算法挑战的背景下，pi提出了一个专门的多学科RAISE计划，涉及量子化学、理论计算机科学和计算凝聚态物理。一种适用于这种开放系统的新量子算法，一种在量子设备上可以很好地扩展的算法，将带来超越量子计算社区的变革。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经典计算机快得多，尽管这些算法没有已知的实际应用。这一进展引发了对实用量子算法的研究，这些算法可以在近期设备上解决化学和物理中的相关问题。所提出的量子算法将利用量子计算的能力来解决一类物理相关问题，并克服经典方法中多电子量子理论的指数缩放的固有局限性。本研究将在以下密切相关的跨学科方向上进行：1)在NISQ设备上使用林德布拉迪轨迹集成（ELT）方法加速非马尔可夫动力学的量子算法；2)演示量子ELT算法在非指数标度的强相关凝聚相系统中捕获非无足轻重的电子和核动力学。对于弱耦合的马尔可夫系统，Lindblad形式给出了一个有效和准确的动力学描述，尽管它对系统的大小有严格的限制。该程序将建立在ELT方法的基础上，量子算法保留了经典算法的显著优点，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。来自pi的多学科发现和方法跨越计算和凝聚态物理，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。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.