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  • Letter
  • Open Access

Scaling adaptive quantum simulation algorithms via operator pool tiling

John S. Van Dyke1,2,*,†, Karunya Shirali1,2,*, George S. Barron1,2, Nicholas J. Mayhall2,3, Edwin Barnes1,2, and Sophia E. Economou1,2

  • 1Department of Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
  • 2Virginia Tech Center for Quantum Information Science and Engineering, Blacksburg, Virginia 24061, USA
  • 3Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, USA

  • *These authors contributed equally to this work.
  • †Present address: Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, Maryland 20723, USA.
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Phys. Rev. Research 6, L012030 – Published 16 February, 2024

DOI: https://doi.org/10.1103/PhysRevResearch.6.L012030

Abstract

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.

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Phys. Rev. Research 6, L012030– Published 16 February, 2024
  • Received 27 June 2022
  • Revised 27 October 2023
  • Accepted 14 December 2023
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