Scaling adaptive quantum simulation algorithms via operator pool tiling

Journal Article · 15 February 2024 · Physical Review Research

DOI: https://doi.org/10.1103/PhysRevResearch.6.L012030 · OSTI ID:2305785

Van Dyke, John S. ; Shirali, Karunya ; Barron, George S. ; Mayhall, Nicholas J. ; Barnes, Edwin; Economou, Sophia E.

Adaptive variational quantum simulation algorithms use information from a quantum computer to dynamically create optimal trial wave functions for a given problem Hamiltonian. A key ingredient in these algorithms is a predefined operator pool from which trial wave functions are constructed. Finding suitable pools is critical for the efficiency of the algorithm as the problem size increases. Here, we present a technique called operator pool tiling that facilitates the construction of problem-tailored pools for arbitrarily large problem instances. By first performing an Adaptive Derivative-Assembled Problem-Tailored Ansatz Variational Quantum Eigensolver (ADAPT-VQE) calculation on a smaller instance of the problem using a large, but computationally inefficient, operator pool, we extract the most relevant operators and use them to design more efficient pools for larger instances. We demonstrate the method here on strongly correlated quantum spin models in one and two dimensions, finding that ADAPT automatically finds a highly effective ansatz for these systems. Given that many problems, such as those arising in condensed matter physics, have a naturally repeating lattice structure, we expect the pool tiling method to be a widely applicable technique apt for such systems. Published by the American Physical Society 2024

• Sponsoring Organization: USDOE
• Grant/Contract Number: SC0019199; SC0012704
• OSTI ID: 2305785
• Journal Information: Physical Review Research, Journal Name: Physical Review Research Journal Issue: 1 Vol. 6; ISSN 2643-1564; ISSN PPRHAI
• Publisher: American Physical SocietyCopyright Statement
• Country of Publication: United States
• Language: English