Quantum-Enhanced Optimization for Constraint Satisfaction

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum annealing techniques are being explored as a potential advancement in optimization for constraint satisfaction problems (CSPs). This paper investigates the application of quantum annealing to accelerate the search for optimal solutions for CSPs, focusing on its ability to overcome the computational limitations of traditional methods, especially for large and complex problems. The core claim is that the introduction of quantum annealing can significantly enhance the efficiency of optimization, offering a pathway to more scalable solutions. This work will detail the theoretical framework, implementation details, and preliminary results demonstrating the efficacy of this approach.

DOI: 10.5281/zenodo.22280202

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