Quantum Entanglement-Based Adaptive Topology Optimization

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the application of quantum entanglement to adaptive topology optimization, a novel approach that leverages quantum mechanics to dynamically adjust geometric structures. Traditional topology optimization methods rely on handcrafted parameters, limiting their versatility and adaptability to complex geometries. This research proposes a quantum-enhanced algorithm that utilizes entangled states to explore a vast search space, enabling rapid optimization and the creation of structures exhibiting adaptive behavior. The core mechanism involves manipulating quantum states to iteratively refine a topological structure, driven by entanglement and feedback loops. We present a theoretical framework outlining the algorithm's design and potential for real-world applications, demonstrating its ability to generate novel topological configurations with unprecedented adaptability.

DOI: 10.5281/zenodo.22194346

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