Quantum computers alone cannot solve industrial problems. Only software that translates use cases into suitable algorithms and combines classical and quantum-assisted methods can turn the technology into a practical tool. With the QuaST Decision Tree, Fraunhofer IKS is now providing an open-source framework that helps bridging the gap: it helps users systematically prepare complex optimization problems and identify suitable hybrid solution approaches.
August 28, 2026
© iStock/Bartlomiej Wroblewski
Quantum computing sounds like science fiction: professors covering blackboards with long equations and researchers in darkened laboratories using complex apparatus to control the tiniest particles. Yet research into this cutting-edge technology also has a much more practical side: how can quantum computers actually be put to use?
After all, the revolutionary quantum algorithm developed by the professor in her office must first be executed. This requires not only quantum computers, but also software that enables users to solve practical problems with their aid – for example: Which routes should my delivery vans take to deliver parcels as efficiently as possible? How can I achieve the best utilization of the machines on my production floor?
This "bridge to application" is the focus of the Quantum Computing department at the Fraunhofer Institute for Cognitive Systems IKS, led by PD Dr. habil. Jeanette Lorenz. Its latest publication is not a scientific paper, but a piece of software: the QuaST (Quantum-enabling Services and Tools for Industrial Applications) Decision Tree (https://www.quast-decisiontree.com/). This modular framework makes it possible to address application problems systematically using algorithms that employ both classical and quantum computers. After all, developing a quantum-assisted solution involves questions that end users cannot reasonably be expected to answer: What is the best way to formulate my problem? How should I decompose it to obtain the best solution? Which quantum algorithm can help?
To automate such decisions, the QuaST Decision Tree uses a clever approach. Instead of providing specific decision aids – which could become obsolete with the next research result – it supplies a modular framework. Individual components can therefore be replaced and improved easily, while the many tools already available from the community can be integrated. Tools like these make scientific results usable in practice.
One example is a quantitative analysis method developed at Fraunhofer IKS to examine the interaction between quantum and classical optimization algorithms (https://safe-intelligence.fraunhofer.de/artikel/auszeichnung-hybride-quantenalgorithmen). It determines the circumstances under which a specific class of quantum-classical algorithms may offer an advantage. When translated into a software tool, the method can automatically determine whether such algorithms should be used and, if so, in which variant. This avoids the need to launch costly trial runs for every new use case, even though most of them could not deliver an advantage.
In the QuaST Decision Tree, such automation modules can be connected flexibly. It can support a variety of application scenarios. Fraunhofer IKS is, for example, testing its integration into an industrial platform for optimization solutions, with the aim of extending the platform’s capabilities to include quantum-assisted solutions.
The QuaST Decision Tree is presented here (https://www.quast-decisiontree.com/) and is available to developers as open-source software at https://gitlab.cc-asp.fraunhofer.de/iks-quantum-computing-public/quast-decisiontree.
Furthermore, European and national initiatives are also currently driving the development of a comprehensive software stack for quantum-assisted solutions. The QuaST Decision Tree is an important component of this stack and can form its topmost layer: the transition from an application to the definition of a hybrid algorithm comprising both quantum and classical components. Its modularity makes it possible to incorporate the many tools developed through applied research that simplify the configuration and execution of such algorithms.
This is how Fraunhofer IKS is helping to build a European infrastructure that connects and integrates quantum-assisted solutions with established technologies, bringing quantum computing one step closer to industrial practice.
