Quantum Simulation of Dynamic Topological Optimization Algorithm

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper presents a novel dynamic topological optimization algorithm based on quantum simulation. Traditional optimization algorithms often rely on intuitive design, while this approach leverages the unique properties of quantum mechanics to dissect the algorithm's underlying mechanisms and accelerate optimization. The core focus is to employ quantum simulation to model the dynamic evolution of topological structures during optimization, providing a deeper understanding of the algorithm's behavior. We propose a framework that utilizes quantum states to represent the topological landscape, allowing for a more nuanced simulation of the optimization process. The research explores the potential of this approach to identify key stages of the algorithm and to develop novel optimization strategies. The results demonstrate the effectiveness of quantum simulation in illuminating crucial aspects of the algorithm's operation, ultimately leading to improved optimization efficiency.

DOI: 10.5281/zenodo.22315395

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