XY mixers: Analytical and numerical results for the quantum alternating operator ansatz

Zhihui Wang, Nicholas C. Rubin, Jason M. Dominy, and Eleanor G. Rieffel
Phys. Rev. A 101, 012320 – Published 14 January 2020

Abstract

The quantum alternating operator ansatz (QAOA) is a promising gate-model metaheuristic for combinatorial optimization. Applying the algorithm to problems with constraints presents an implementation challenge for near-term quantum resources. This paper explores strategies for enforcing hard constraints by using XY Hamiltonians as mixing operators (mixers). Despite the complexity of simulating the XY model, we demonstrate that, for an integer variable admitting κ discrete values represented through one-hot encoding, certain classes of the mixer Hamiltonian can be implemented without Trotter error in depth O(κ). We also specify general strategies for implementing QAOA circuits on all-to-all connected hardware graphs and linearly connected hardware graphs inspired by fermionic simulation techniques. Performance is validated on graph-coloring problems that are known to be challenging for a given classical algorithm. The general strategy of using XY mixers is borne out numerically, demonstrating a significant improvement over the general X mixer, and moreover the generalized W state yields better performance than easier-to-generate classical initial states when XY mixers are used.

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  • Received 1 August 2019

DOI:https://doi.org/10.1103/PhysRevA.101.012320

©2020 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & Technology

Authors & Affiliations

Zhihui Wang*

  • Quantum Artificial Intelligence Laboratory, NASA Ames Research Center, Moffett Field, California 94035, USA and Universities Space Research Association, 615 National Avenue, Mountain View, California 94043, USA

Nicholas C. Rubin

  • Google, Inc., 340 Main Street, Venice, California 90291, USA and Rigetti Quantum Computing, 775 Heinz Avenue, Berkeley, California 94710, USA

Jason M. Dominy

  • Department of Applied Mathematics, University of California, Santa Cruz, Santa Cruz, California 95064, USA

Eleanor G. Rieffel

  • Quantum Artificial Intelligence Laboratory, NASA Ames Research Center, Moffett Field, California 94035, USA

  • *zhihui.wang@nasa.gov
  • nickrubin@google.com

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Vol. 101, Iss. 1 — January 2020

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