基于动态拓扑结构的量子计算验证

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum computing offers the potential for revolutionary computational capabilities, but its practical realization faces significant challenges, particularly in algorithm validation. Traditional verification methods often rely on classical algorithms and proofs, which struggle to capture the inherent complexities of quantum systems. This paper introduces a novel quantum algorithm verification technique based on dynamic topology, leveraging self-adaptive learning to dynamically adjust the quantum system's topology to ensure correctness and stability. We propose a mechanism that utilizes a continuous evolution of the system's geometry, allowing for a more precise and flexible validation process. This approach directly addresses the limitations of current methods, offering a promising pathway towards robust quantum algorithms. The paper details the theoretical framework, implementation of the self-adaptive learning algorithm, and preliminary experimental results demonstrating the efficacy of the proposed technique.

DOI: 10.5281/zenodo.22184935

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