Variational quantum iterative power algorithms for global optimization

Abstract

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 $H_2$ 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.

17 pages, 7 figures

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• Simulating electronic structure on bosonic quantum computers
• Expanding Hardware-Efficiently Manipulable Hilbert Space via Hamiltonian Embedding
• The Quantum Ensemble Variational Optimization Algorithm: Applications to Molecular Inverse Design
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• Molecular resonance identification in complex absorbing potentials via integrated quantum computing and high-throughput computing
• Exponential Separation Criteria for Quantum Iterative Power Algorithms