拓扑量子计算中的自适应几何优化算法

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper introduces a novel self-adaptive geometric optimization algorithm for quantum systems, leveraging the unique properties of topological quantum computation. The algorithm adapts to the specific geometry of the quantum system during optimization, leading to improved efficiency and stability compared to traditional methods. The core mechanism centers around utilizing the inherent topological structure of the quantum system to guide the optimization process, resulting in a more robust and efficient approach to quantum system design. We present a detailed explanation of the algorithm's components and demonstrate its performance on various quantum systems through illustrative examples. The research explores the potential of this approach to address key challenges in quantum computing, including error mitigation and system scalability.

DOI: 10.5281/zenodo.22314292

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