Digitized-counterdiabatic quantum approximate optimization algorithm

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