Quantum-Guided Optimization for Complex Network Design

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the application of quantum-guided optimization to the design of complex networks. Complex networks, such as social networks, communication networks, and biological networks, possess intricate relationships and require efficient optimization algorithms. Classical methods often struggle to find optimal configurations due to computational limitations and the inherent complexity of the search space. We propose a novel quantum-guided optimization strategy that leverages the unique properties of quantum annealing and quantum-enhanced optimization to accelerate the search for configurations with enhanced network properties. This approach aims to overcome limitations of existing methods by providing a fundamentally new optimization strategy. The research will outline the core mechanisms, potential advantages, and preliminary results demonstrating the effectiveness of this quantum-assisted optimization technique for complex network design.

DOI: 10.5281/zenodo.22199981

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