基于量子纠缠的拓扑几何的自适应计算框架

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

Quantum entanglement, a cornerstone of quantum mechanics, presents a unique opportunity for computation beyond classical paradigms. This paper explores the application of quantum entanglement to develop a novel self-adaptive computing framework, leveraging the inherent properties of entangled states to dynamically adjust computational parameters within complex systems. We propose a method for establishing a dynamic mapping between the computational process and the entangled state parameters, enabling efficient optimization of systems exhibiting high complexity and non-linearity. The core claim centers on the ability of this framework to overcome the limitations of traditional computational methods through the utilization of quantum entanglement's self-adaptive nature. This research investigates the potential of such a framework to facilitate the design and execution of algorithms capable of achieving performance gains in challenging scenarios.

DOI: 10.5281/zenodo.22246205

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