Title: Quantum Constraint Propagation with Adaptive Resonance

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum Constraint Propagation with Adaptive Resonance presents a novel quantum algorithm for solving complex systems by dynamically adjusting constraint strength. Traditional approaches often struggle with the inherent complexity of these problems, leading to slow convergence and limited solution quality. This work introduces a 'resonance' mechanism, which intelligently strengthens constraints in regions of high uncertainty and weakens them in areas of high certainty, significantly enhancing the algorithm's performance. We demonstrate the effectiveness of this approach through extensive simulations and analysis, showcasing substantial improvements in solution speed and accuracy compared to existing quantum constraint propagation techniques. The proposed algorithm leverages quantum entanglement and superposition to achieve a unique approach to constraint management, offering a significant advancement in the field.

DOI: 10.5281/zenodo.22468529

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