Quantum-Enhanced Constraint Satisfaction

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper investigates the application of quantum annealing to the constraint satisfaction problem (CSP) to enhance the speed and effectiveness of solving complex CSPs. The core claim is that incorporating a quantum annealing algorithm allows for more efficient exploration of the solution space, leading to faster and more accurate solutions compared to classical methods, particularly in scenarios with large and intricate constraint sets. We analyze the potential benefits of quantum annealing in this domain, focusing on its ability to mitigate the difficulties inherent in exploring vast solution spaces. The paper presents a detailed theoretical framework for integrating quantum annealing, explores its suitability for specific CSP variations, and discusses the challenges and limitations associated with this approach. The goal is to demonstrate a tangible improvement in solution speed and quality through the utilization of quantum annealing.

DOI: 10.5281/zenodo.22188292

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