自适应拓扑的量子态分解

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces a novel quantum state decomposition algorithm based on adaptive topology, offering a promising approach to optimization and control in quantum computing. Traditional state decomposition methods often rely on manual design, lacking the ability to learn from data. Our framework leverages the inherent topological structure of quantum states to efficiently decompose them, enabling enhanced optimization and control capabilities. This work presents a theoretical analysis and preliminary implementation demonstrating the algorithm's effectiveness and potential for significant advancements within the field. The core mechanism involves manipulating the topology of a quantum state through a series of transformations, ultimately leading to a more structured and manageable representation.

DOI: 10.5281/zenodo.22299247

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