基于拓扑结构的动态量子态学习

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel dynamic quantum state learning algorithm based on topological structure. Traditional quantum state learning methods often lack adaptability to complex environments, necessitating a dynamic approach. This work proposes a method that leverages topological structure to dynamically adjust quantum states, ultimately optimizing quantum computing performance. The core mechanism involves learning and adapting the topological structure to influence the evolution of the quantum state, enabling efficient and responsive quantum computation. The algorithm's effectiveness is demonstrated through a series of simulations, showcasing improved performance compared to existing techniques.

DOI: 10.5281/zenodo.22185019

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