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Quantum-Enhanced Constraint Propagation for Optimization

Jincheng Zhang

Published Sep 7, 2026• 0 citations
Publisher

Abstract

This paper explores the potential of quantum computing to revolutionize constraint propagation in optimization problems. Traditional constraint propagation methods often suffer from limitations in computational efficiency, particularly when dealing with complex, high-dimensional problems. We propose a novel approach leveraging quantum entanglement to enhance constraint propagation, aiming to dramatically improve the speed and accuracy of solving constrained optimization problems. The core mechanism involves establishing entanglement between constraint variables, enabling a more efficient and synchronized exploration of the search space. We detail the theoretical foundation, implementation details, and preliminary experimental results demonstrating the effectiveness of this technique. The research focuses on addressing the computational bottleneck inherent in current optimization algorithms and presents a pathway towards significant advancements in the field.

DOI
10.5281/zenodo.22635311

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