Digitized-counterdiabatic quantum approximate optimization algorithm

2021/07/31 by P. Chandarana, Pranav Chandarana, N. N. Hegade +8
Computer Science · Mathematics · Physics and Astronomy · #Algorithm #Ansatz #Computer science #Hamiltonian (control theory) #Ising model #Mathematical optimization #Mathematical physics #Mathematics #Optimization problem #Physics #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum computer #Quantum many-body systems #Quantum mechanics #Statistical physics #quant-ph

paper · pdf · doi:10.1103/physrevresearch.4.013141

published as Phys. Rev. Research 4, 013141 (2022) · 9 pages, 4 figures

openalex publication_date 2022/02/22 · arxiv created 2022/03/04 · arxiv updated 2022/03/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

The quantum approximate optimization algorithm (QAOA) has proved to be an effective classical-quantum algorithm serving multiple purposes, from solving combinatorial optimization problems to finding the ground state of many-body quantum systems. Since the QAOA is an Ansatz-dependent algorithm, there is always a need to design Ans"atze for better optimization. To this end, we propose a digitized version of the QAOA enhanced via the use of shortcuts to adiabaticity. Specifically, we use a counterdiabatic (CD) driving term to design a better Ansatz, along with the Hamiltonian and mixing terms, enhancing the global performance. We apply our digitized-CD QAOA to Ising models, classical optimization problems, and the P-spin model, demonstrating that it outperforms the standard QAOA in all cases we study.

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