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Quantum-Accelerated Constraint Propagation for Large-Scale Constraint Satisfaction

Jincheng Zhang

Published Aug 31, 2026• 0 citations
Publisher

Abstract

This paper investigates the potential of quantum computing to revolutionize constraint satisfaction problems (CSPs), specifically focusing on the development of a quantum-accelerated constraint propagation algorithm. We address the significant computational bottleneck associated with CSPs, particularly at scale, and propose a novel approach that utilizes quantum algorithms to represent and manipulate constraint sets with a drastically reduced computational cost. The core mechanism involves leveraging quantum superposition and entanglement to efficiently explore the vast solution space, leading to significant speedups compared to classical methods. We present a theoretical framework and preliminary implementation demonstrating the efficacy of this approach in tackling large-scale CSPs. The paper concludes with a discussion of the challenges and future research directions in this rapidly evolving field.

DOI
10.5281/zenodo.22187116

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