基于自适应的量子纠缠图的自适应优化算法

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Quantum entanglement is a fundamental phenomenon in quantum mechanics with immense potential for technological advancements. However, harnessing the full power of entanglement requires sophisticated techniques for managing and optimizing its properties. This paper introduces a novel self-adaptive quantum entanglement graph optimization algorithm, designed to automatically adjust the structure of quantum entanglement graphs, thereby enhancing the utilization and transmission of entangled states. The algorithm leverages a dynamic adjustment mechanism, allowing the system to adapt to varying entanglement characteristics, leading to improved efficiency in quantum information processing. This work provides a significant step towards automating the optimization of quantum systems.

DOI: 10.5281/zenodo.22585932

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