Quantum-Guided Optimization for Complex Systems

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

Quantum-Guided Optimization (QGO) represents a novel approach to optimization, utilizing quantum interference to enhance search efficiency within complex, multi-dimensional systems. This paper explores the potential of QGO to overcome limitations of conventional optimization methods, particularly in scenarios where traditional approaches fail to converge effectively. We detail the core mechanism of quantum interference, its impact on the search space, and propose a framework for implementation. The research investigates the advantages and challenges of incorporating quantum mechanics into optimization, aiming to demonstrate a significant improvement in solution finding speed and accuracy compared to existing algorithms. The core claim is that QGO offers a fundamentally new path toward solving complex problems with enhanced efficiency.

DOI: 10.5281/zenodo.22219663

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