基于自适应的量子纠缠网络拓扑优化

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum entanglement offers unparalleled security and information processing capabilities, but realizing this potential requires sophisticated quantum communication protocols. Current quantum communication networks often rely on pre-defined topologies, which can limit scalability and efficiency. This paper introduces a novel algorithm, "Adaptive Quantum Topology Optimization," designed to dynamically optimize the quantum entanglement network topology, thereby enhancing the efficiency and security of quantum communication. We propose a self-learning process that adjusts quantum entanglement parameters based on observed network performance, leading to more robust and adaptable quantum communication systems. This work addresses the limitations of traditional network design by providing a flexible and adaptive approach to topology optimization. We demonstrate the effectiveness of this algorithm through simulations, showcasing significant improvements in entanglement fidelity and communication rate compared to static topology configurations.

DOI: 10.5281/zenodo.22200250

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