自适应拓扑结构与高维量子计算的协同建模

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper investigates the potential of self-adaptive topological structures as a framework for optimizing high-dimensional quantum computations. Traditional quantum computation relies heavily on manual parameter design, presenting limitations in scalability and efficiency. We propose a novel approach that leverages the inherent properties of topological structures to simplify the computational space and facilitate synergistic modeling between quantum processors. This system aims to improve quantum computing performance through enhanced parameter optimization and improved protocol design. The core mechanism involves utilizing topological structures as simplified models for high-dimensional quantum systems, enabling efficient exploration of the parameter space and ultimately leading to increased computational speed. This work presents a new methodology for quantum computing that harnesses the power of topology to address key challenges in this field.

DOI: 10.5281/zenodo.22320802

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