Title: Quantum-Enhanced Topological Optimization Algorithms

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper introduces a novel quantum-enhanced topological optimization algorithm designed to address complex optimization problems with inherent topological properties. Traditional optimization techniques often struggle with highly non-convex and sparse landscapes, limiting their effectiveness in diverse scenarios. We propose a quantum algorithm leveraging quantum entanglement to explore the solution space more efficiently and discover potentially globally optimal solutions. The core mechanism hinges on utilizing quantum entanglement to establish correlations between data points, enabling a probabilistic exploration of the solution space that surpasses the capabilities of classical methods. The proposed algorithm demonstrates promising results on benchmark topological optimization problems, showcasing the potential of quantum computation to revolutionize this field. This work contributes to the exploration of quantum algorithms for optimization, specifically focusing on topological optimization, and introduces a novel approach leveraging quantum entanglement for enhanced efficiency.

DOI: 10.5281/zenodo.22314710

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