This article summarizes a software framework combining classical and quantum computing for optimization, enhancing usability for non-experts.
This article gives an overview of the ProvideQ Toolbox, a software framework that utilizes so-called Meta-Solver Strategies to solve combinatorial optimization problems with hybrid quantum-classical computing methods. We reuse existing state-of-the-art methods from classical and quantum computing, with the goal of combining the best of both worlds. We hide the implementations of algorithms, parsers, circuit-optimization techniques, and other complex tasks behind accessible and easy-to-understand user interfaces, which drastically improves the usability for non-experts. This article is a short summary of an already published paper. An extended description of this contribution can be found in our full-paper [Ei25] or by visiting us on GitHub [Pr25].
No takes yet. Share an insight, caveat, or question.
Eichhorn et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: