Quantum-Enhanced Constraint Satisfaction with Probabilistic Reasoning

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the potential of quantum computing to revolutionize constraint satisfaction problems (CSPs) by integrating quantum annealing or variational quantum eigensolver (VQE) to enhance the probabilistic reasoning component. We address the limitations of traditional CSP solvers, particularly in complex scenarios, and propose a novel approach that leverages quantum phenomena to accelerate solution finding and improve accuracy. The core mechanism involves strategically utilizing quantum algorithms to explore the solution space more efficiently, leading to improved performance compared to classical methods. We present a preliminary analysis, demonstrating the potential benefits of this approach through simulations and theoretical considerations.

DOI: 10.5281/zenodo.22198766

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