基于动态自组织的粒子的量子拓扑优化

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper investigates the application of dynamic self-organization algorithms to quantum topology optimization problems. We propose a novel approach that utilizes a particle-based search strategy, guided by self-organization principles, to identify more efficient paths within the optimization landscape. The core mechanism involves iteratively constructing and refining a particle swarm, leveraging the inherent properties of self-organization to explore the solution space and mitigate the pitfalls of traditional optimization methods. The effectiveness of this approach is demonstrated through the application of a specific quantum topology optimization task, showcasing improved convergence speed and robustness compared to existing techniques. The study highlights the potential of dynamic self-organization to unlock new solutions in complex quantum optimization problems.

DOI: 10.5281/zenodo.22266371

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