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

非技术综述：开放量子系统在化学、物理和材料科学中无处不在，从光合作用捕光的生色团和催化中心到固态材料中的量子缺陷。更广泛地说，开放量子系统提供了一个框架来考虑与环境有重大交互作用的系统的结构和动力学。尽管开放系统在根本上和技术上都很重要，但经典方法在计算上仍然有限。在量子计算最新发现的催化下，该团队提议使用量子资源(噪声中等规模的量子设备，或NISQ设备)来描述开放量子系统。一种适用于这种开放系统的新量子算法，在量子设备上具有良好的可伸缩性，将在量子信息界之外产生变革。在更大的量子模拟背景下，准确、高效地计算分子和材料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带来了新的可能性，指数复杂性阻碍了在高性能经典计算机上模拟强关联和开放的量子系统。所提出的量子算法将利用量子计算的能力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标度的固有局限性。为了推动量子信息科学和技术的发展，该计划将采取并行的方法，以产生更广泛的影响：(I)教育，包括开放量子系统的量子计算课程和哈佛大学和芝加哥大学的在线模块。本课程将利用对小型量子设备的访问。PiNarang已经将这些想法融入到IBM的本科课程中；(Ii)通过与波士顿科学博物馆的联系，强调招募和纳入STEM中未被充分代表的群体进入量子算法领域；以及(Iii)在化学和物理的量子信息领域与行业合作伙伴和初创公司密切接触。技术总结：PI在NSF量子算法挑战的背景下，提出了一个专门的、多学科的提升计划，介于量子化学、理论计算机科学和计算凝聚态物理之间。一种适用于这种开放系统的新量子算法，在量子设备上具有良好的可扩展性，将在量子计算社区之外产生革命性的影响。该团队注意到了拟议方法的及时性：就在2019年，谷歌和NASA的研究人员还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标度的固有局限性。拟议的工作将组织在以下紧密联系的跨学科推进中：1)在NISQ设备上使用Lindbladian轨迹系综(ELT)方法加速非马尔可夫动力学的量子算法，以及2)演示量子ELT算法以捕获具有非指数尺度的强关联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，Lindblad形式给出了有效和准确的动力学描述，尽管它对系统的大小施加了严格的限制。这个程序将建立在ELT方法的基础上，量子算法保留了经典算法的显著优势，包括对非马尔科夫动力学的精确处理和密度矩阵的完全正性。PIS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，对本计划的愿景和目标至关重要，非常适合NSF RAISE计划的要求。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。

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.