Quantum leaps for the economy: three projects demonstrate the potential of quantum computing
Quantum computing offers enormous potential - also for SMEs. Three projects from the BMWK technology programme "Quantum Computing - Applications for the Economy" have successfully completed their work. Their results show how companies can benefit from this future technology.
Germany should play a leading role in the economic application of quantum technologies - this is the goal of the German government. By funding quantum computing software in the "Quantum Computing - Applications for the Economy" technology programme, the BMWK has made an important contribution to making this future technology accessible since 2022, especially for small and medium-sized enterprises (SMEs). The first three projects in the programme successfully completed their work at the end of 2024. The DLR Project Management Agency's programme support team has summarised the key results and their benefits for the economy in compact results profiles.
Chemical simulations for the energy transition: AQUAS
The AQUAS project has developed methods to efficiently simulate chemical reactions using a combination of quantum computers and classical computers. The catalysis of hydrogen - a key factor for the energy transition - served as an example. The results profile shows how the methods developed can be made easily accessible via the cloud in the future.
Solving optimisation problems: QuaST
The QuaST project focused on optimisation problems. Using examples from logistics, software development and finance, the partners involved developed procedures and tools to best break down industrial challenges into smaller steps and solve them on quantum computers. You can find out how a decision tree developed in the project helps with this in the results profile.
Machine learning with quantum computers: AutoQML
The AutoQML project focussed on methods of machine learning on quantum computers. The focus was on use cases such as predicting the price of used vehicles. With the sQUlearn library and the AutoQML framework, important building blocks were created to make it easier for users to get started with this technology. Project manager Christian Tutschku explains the practical significance of these tools in the results profile.