Quantum-Driven Constraint Programming

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

This paper introduces a novel quantum-driven constraint programming framework, leveraging quantum entanglement and superposition to optimize constraint conditions and enhance the efficiency of constraint solving. Traditional constraint programming methods often struggle with computationally intensive optimization problems. Quantum computing offers the potential for significant speedups through quantum algorithms. We propose a new approach that utilizes quantum entanglement to accelerate the search process, ultimately leading to more efficient constraint solving. This work demonstrates the feasibility of quantum-enhanced constraint programming and explores its potential impact on various constraint satisfaction problems.

DOI: 10.5281/zenodo.22219603

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