##拓扑量子纠缠的自适应优化算法

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum entanglement offers unprecedented opportunities for quantum computation and communication, but its practical implementation often faces limitations due to the difficulty of controlling quantum states. This paper explores the potential of leveraging quantum entanglement to develop a novel self-adaptive optimization algorithm for quantum systems. We propose a "quantum state graph" concept, where quantum bits are represented as nodes and entanglement properties are used to dynamically adjust qubit arrangements. This approach aims to overcome the inherent challenges of controlling quantum systems through classical optimization methods, potentially unlocking new capabilities in quantum information processing. The core mechanism involves utilizing pulse-based control to manipulate entanglement and achieve precise results. This research introduces a framework for dynamically adapting quantum states, offering a pathway toward more efficient and robust quantum algorithms.

DOI: 10.5281/zenodo.22192572

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