基于自适应拓扑的量子计算的优化

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper introduces a novel quantum computing optimization framework based on adaptive topology. Traditional quantum computing optimization methods typically rely on static parameters, while adaptive topology optimization offers the ability to dynamically adjust parameters for improved resource utilization. Our approach utilizes a dynamic structure generated by the optimization process to enhance quantum computation efficiency. The core mechanism involves adjusting quantum bit (qubit) parameters based on the observed results of a quantum computation, promoting a more efficient and robust approach to optimization. We demonstrate the effectiveness of this framework through simulations and preliminary experiments, showcasing significant improvements in quantum algorithm performance compared to conventional methods.

DOI: 10.5281/zenodo.22264375

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