基于自适应的量子算法的拓扑结构优化

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum computing is rapidly advancing, and the development of efficient quantum algorithms is paramount to realizing its full potential. Current quantum algorithms often rely on fixed parameter configurations, limiting their ability to exploit subtle variations in the quantum state. This paper introduces a novel approach utilizing a self-adaptive quantum algorithm to dynamically optimize the topology of quantum states, aiming to significantly enhance the performance of quantum computations. We propose a method based on iterative adjustments to the quantum state's geometry, guided by the inherent properties of the qubit system. This research focuses on establishing a robust and effective mechanism for automatic topology optimization, addressing the limitations of traditional approaches. The core claim is that this self-adaptive algorithm can significantly improve quantum computation efficiency through precise and automated topology manipulation. We detail the proposed algorithm, its underlying principles, and preliminary experimental results demonstrating its efficacy. The significance of this work lies in its potential to unlock new levels of quantum algorithm performance by proactively tailoring the quantum state.

DOI: 10.5281/zenodo.22272218

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