Photonic counterdiabatic quantum optimization algorithm

• URL: http://arxiv.org/abs/2307.14853v1
• Date: Thu, 27 Jul 2023 13:33:33 GMT
• Title: Photonic counterdiabatic quantum optimization algorithm
• Authors: Pranav Chandarana, Koushik Paul, Mikel Garcia-de-Andoin, Yue Ban, Mikel Sanz, Xi Chen
• Abstract summary: We propose a hybrid quantum- approximate optimization algorithm for quantum computing that is tailored for continuous-variable problems. We conduct proof-of-principle experiments on an-photo quantum chip.
• Score: 3.2174634059872154
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a hybrid quantum-classical approximate optimization algorithm for photonic quantum computing, specifically tailored for addressing continuous-variable optimization problems. Inspired by counterdiabatic protocols, our algorithm significantly reduces the required quantum operations for optimization as compared to adiabatic protocols. This reduction enables us to tackle non-convex continuous optimization and countably infinite integer programming within the near-term era of quantum computing. Through comprehensive benchmarking, we demonstrate that our approach outperforms existing state-of-the-art hybrid adiabatic quantum algorithms in terms of convergence and implementability. Remarkably, our algorithm offers a practical and accessible experimental realization, bypassing the need for high-order operations and overcoming experimental constraints. We conduct proof-of-principle experiments on an eight-mode nanophotonic quantum chip, successfully showcasing the feasibility and potential impact of the algorithm.

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