基于量子纠缠的动态拓扑的自适应优化

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper investigates the application of quantum entanglement to dynamic topology optimization, presenting a novel framework leveraging the unique properties of entangled states to dynamically adjust the topology of a system. Traditional topological optimization methods often rely on manual design, limiting their adaptability to complex, evolving systems. We introduce a quantum-enhanced approach utilizing entanglement to identify and refine topology, resulting in enhanced computational efficiency and stability. The core mechanism involves establishing entangled states to represent the system's potential, allowing for iterative adjustments to the topology based on quantum feedback. This represents a significant departure from conventional methods, offering a potentially transformative approach to optimization across diverse domains.

DOI: 10.5281/zenodo.22266375

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