基于自适应拓扑网络的量子态预测算法

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper presents a novel quantum state prediction algorithm based on an adaptive topology network. Traditional quantum state prediction methods often rely on static models, limiting their ability to accurately predict quantum state evolution. This algorithm leverages the dynamic nature of topology to achieve more efficient and adaptive state optimization. The core mechanism involves adjusting the topology structure dynamically, enabling a more nuanced and precise prediction of quantum states. We demonstrate the algorithm's effectiveness through theoretical analysis and simulation, showcasing improvements in prediction accuracy and state optimization compared to existing approaches. The resulting system offers a significant step towards enhanced quantum control and manipulation.

DOI: 10.5281/zenodo.22185801

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