Digitized-counterdiabatic quantum approximate optimization algorithm

• URL: http://arxiv.org/abs/2107.02789v3
• Date: Fri, 4 Mar 2022 12:24:02 GMT
• Title: Digitized-counterdiabatic quantum approximate optimization algorithm
• Authors: P. Chandarana, N. N. Hegade, K. Paul, F. Albarr\'an-Arriagada, E. Solano, A. del Campo, Xi Chen
• Abstract summary: We propose a digitized version of QAOA enhanced via the use of shortcuts to adiabaticity. We apply our digitized-counterdiabatic QAOA to Ising models, classical optimization problems, and the P-spin model, demonstrating that it outperforms standard QAOA in all cases.
• Score: 3.0638256603183054
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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 QAOA is an ansatz-dependent algorithm, there is always a need to design ansatz for better optimization. To this end, we propose a digitized version of 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-counterdiabatic QAOA to Ising models, classical optimization problems, and the P-spin model, demonstrating that it outperforms standard QAOA in all cases we study.

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