Solving Quantum-Inspired Perfect Matching Problems via Tutte-Theorem-Based Hybrid Boolean Constraints

Solving Quantum-Inspired Perfect Matching Problems via Tutte-Theorem-Based Hybrid Boolean Constraints

Moshe Y. Vardi, Zhiwei Zhang

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
Main Track. Pages 2039-2048. https://doi.org/10.24963/ijcai.2023/227

Determining the satisfiability of Boolean constraint-satisfaction problems with different types of constraints, that is hybrid constraints, is a well-studied problem with important applications. We study a new application of hybrid Boolean constraints, which arises in quantum computing. The problem relates to constrained perfect matching in edge-colored graphs. While general-purpose hybrid constraint solvers can be powerful, we show that direct encodings of the constrained-matching problem as hybrid constraints scale poorly and special techniques are still needed. We propose a novel encoding based on Tutte's Theorem in graph theory as well as optimization techniques. Empirical results demonstrate that our encoding, in suitable languages with advanced SAT solvers, scales significantly better than a number of competing approaches on constrained-matching benchmarks. Our study identifies the necessity of designing problem-specific encodings when applying powerful general-purpose constraint solvers.
Keywords:
Constraint Satisfaction and Optimization: CSO: Constraint satisfaction
Constraint Satisfaction and Optimization: CSO: Applications
Constraint Satisfaction and Optimization: CSO: Modeling