Title: Adaptive Quantum Algorithm-Based Topological Optimization Model

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel topological optimization model utilizing an adaptive quantum algorithm. Traditional optimization methods rely heavily on manual parameter adjustments, while quantum algorithms offer the potential for more precise and efficient optimization. This work proposes a dynamic adjustment of quantum algorithm parameters to enhance optimization performance and improve the accuracy of resulting solutions. The core mechanism centers on leveraging the inherent capabilities of quantum algorithms to dynamically adjust the optimization process, leading to improved results compared to classical optimization techniques. This research investigates the potential of this adaptive approach to solve complex topological optimization problems.

DOI: 10.5281/zenodo.22184806

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