Quantum-Enhanced Constraint Satisfaction with Wave Function Optimization

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum-enhanced constraint satisfaction problems (CSPs) offer a potential paradigm shift in solving complex optimization challenges, particularly in areas requiring sophisticated search and efficient solution paths. This paper investigates the application of quantum algorithms to constraint satisfaction, aiming to accelerate the search process and enhance solution quality. Specifically, we explore the integration of quantum wave function optimization techniques to represent and manipulate constraint satisfaction spaces. The core mechanism focuses on leveraging quantum computation to efficiently explore the solution space, optimizing the wave function for a given constraint satisfaction. We present a theoretical framework and preliminary experimental results demonstrating the potential benefits of this approach, emphasizing its ability to overcome limitations associated with traditional CSP solvers. The paper concludes with a discussion of future research directions and the challenges associated with scaling this quantum-enhanced approach to larger, more complex problems.

DOI: 10.5281/zenodo.22265062

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