Domain-Driven Modeling of Combinatorial Constraint Satisfaction Problems for Quantum Solvers

Marc Uphues, Sebastian Thöne, Herbert Kuchen

Published Jan 1, 2026• 0 citations

Abstract

Over the last years, quantum computing has reached a level of technological maturity that enables the exploration of potential applications. One use case is solving combinatorial Constraint Satisfaction Problems. Yet, it seems challenging to utilize quantum computing for such problems in practice, as software developers must translate these problems to specialized models required by quantum solvers. A common candidate is the model of Quadratic Unconstrained Binary Optimization. It serves as an input format for both quantum annealing and gate-based quantum algorithms. With this paper, we present a software-based and domain-driven modeling approach that is compatible with such quantum solvers. It facilitates the inline-declaration of problems within domain model code through an annotation-based syntax. Our novel approach is driven by a framework-like engine that encapsulates and automates the process of problem instantiation, translation, solver invocation, and solution mapping. It ena bles software developers and domain experts to solely focus on the problem domain, rather than highly specialized models prescribed by quantum solvers. By incorporating principles of Domain-Driven Design, our approach employs a well-known modeling technique.

DOI: 10.25974/fhms-20395

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