We introduce a family of variational quantum algorithms called quantum iterative power algorithms (QIPA) that outperform existing hybrid near-term quantum algorithms of the same kind. We demonstrate the capabilities of QIPA as applied to three different global-optimization numerical experiments: the ground-state optimization of the H2 molecular dissociation, search of the transmon qubit ground-state, and biprime factorization. Since our algorithm is hybrid, quantum/classical technologies such as error mitigation and adaptive variational ansatzes can easily be incorporated into the algorithm. Due to the shallow quantum circuit requirements, we anticipate large-scale implementation and adoption of the proposed algorithm across current major quantum hardware.
@article{arxiv.2208.10470,
title = {Variational quantum iterative power algorithms for global optimization},
author = {Thi Ha Kyaw and Micheline B. Soley and Brandon Allen and Paul Bergold and Chong Sun and Victor S. Batista and Alán Aspuru-Guzik},
journal= {arXiv preprint arXiv:2208.10470},
year = {2023}
}