Surrogate optimization of variational quantum circuits

• 成果类型: Article
• 署名作者: Gustafson, Erik J.; Tiihonen, Juha; Chamaki, Diana; Sorourifar, Farshud; Mullinax, J. Wayne; Li, Andy C. Y.; Maciejewski, Filip B.; Sawaya, Nicolas P. D.; Krogel, Jaron T.; Neira, David E. Bernal; Tubman, Norm M.
• 署名单位: National Aeronautics & Space Administration (NASA); NASA Ames Research Center; Universities Space Research Association (USRA); University of Jyvaskyla; Columbia University; University System of Ohio; Ohio State University; National Aeronautics & Space Administration (NASA); NASA Ames Research Center; United States Department of Energy (DOE); University of Chicago; Fermi National Accelerator Laboratory; United States Department of Energy (DOE); Oak Ridge National Laboratory; Purdue University System; Purdue University; National Aeronautics & Space Administration (NASA); NASA Ames Research Center
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-10076
• DOI: 10.1073/pnas.2408530122
• 发表日期: 2025-09-09
• 关键词: eigensolver

摘要

Variational quantum eigensolvers are touted as a near-term algorithm capable of impacting many applications. However, the potential has not yet been realized, with few claims of quantum advantage and high resource estimates, especially due to the need for optimization in the presence of noise. Finding algorithms and methods to improve convergence is important to accelerate the capabilities of near-term hardware for variational quantum eigensolver or more broad applications of hybrid methods in which optimization is required. To this goal, we look to use modern approaches developed in circuit simulations and stochastic classical optimization, which can be combined to form a surrogate optimization approach to quantum circuits. Using an approximate (classical central processing unit/graphical processing unit) state vector simulator as a surrogate model, we efficiently calculate an approximate Hessian, which is passed as input for a quantum processing unit or exact circuit simulator. This method will lend itself well to parallelization across quantum processing units. We demonstrate the capabilities of such an approach with and without sampling noise and a proof-of-principle demonstration on a quantum processing unit utilizing 40 qubits.