基于量子计算的拓扑优化

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper investigates the potential of quantum computing to revolutionize optimization problems, specifically focusing on the complex and often intractable nature of topological optimization. Traditional optimization techniques often struggle with the inherent structure and constraints present in such problems. Quantum computing offers a fundamentally different approach, leveraging quantum mechanics to explore solution spaces in novel ways. We explore the application of a novel quantum algorithm – the 'Quantum Topology Mapper' – designed to identify and map topological features within complex systems, ultimately leading to more efficient optimization strategies. The paper details the theoretical foundations of the algorithm, its implementation on a simulated quantum computer, and preliminary results demonstrating improvements over classical approaches in a simplified, yet representative, topological optimization scenario. The core claim is that quantum computing can provide a significant advantage in tackling problems requiring intricate topological structures, representing a paradigm shift in optimization methodologies.

DOI: 10.5281/zenodo.22203583

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