Title: Quantum-Enhanced Constraint Satisfaction Problem (Q-CSP)

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum-enhanced Constraint Satisfaction Problem (Q-CSP) addresses the limitations of traditional CSP solvers, particularly in the context of complex, large-scale problems. This research proposes a novel approach leveraging quantum annealing to accelerate the solution process. The core claim is to design a CSP solver that utilizes quantum annealing to efficiently explore solutions, achieving near-optimal performance compared to classical methods. The investigation focuses on the design and implementation of a quantum annealing algorithm tailored for this specific problem. The paper details the algorithm's architecture, the rationale behind its selection, and the experimental evaluation of its performance. The primary objective is to demonstrate a significant reduction in computational time while maintaining or improving solution quality. This work presents a practical exploration of a quantum annealing solution for the Q-CSP, highlighting its potential for tackling complex constraint satisfaction problems.

DOI: 10.5281/zenodo.22198303

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