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.
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.
