Partners:
TUM, IQM, Infineon, ParityQC, Datev, LRZ, Fraunhofer AISEC, Fraunhofer IIS, Fraunhofer IISB, Fraunhofer IKS
Project duration:
January 2022 – Dezember 2024
Funding:
Federal Ministry of Economic Affairs and Climate Action (BMWK)
In the QuaST research consortium, the project partners worked to facilitate access to quantum computing for small and large companies. This is because solutions based on quantum computing (QC) can make a significant contribution to the advancement of industrial optimization problems, thereby saving time and money.
However, QC-based solutions are not yet available for mainstream industrial users. This is not only due to the limits of quantum computing hardware, but also because in-depth knowledge of physics and computer science is required in order to program today's quantum computers. There has been a lack of low-threshold access to QC-supported solutions for end users.
The QuaST project conducted research and developed tools to provide low-threshold access to quantum computers for companies of all sizes. From 2022 to 2024, it gathered partners from science and industry to tackle this problem within the problem domain of combinatorial optimization. Industrial end users should be able to obtain easily accessible and reliable QC-supported solutions for their application problems with minimal knowledge of QC hardware and QC software.
Throughout the three project years, several cornerstone application cases have been investigated with numerous methods from the literature and within the consortium. The QuaST Best Practice Guide gathers the enormous expertise gained within QuaST and contains the key results of the project.
Restricted Global Optimization for QAOA
by P. Gleißner et al., APL Quantum (2024)
Fraunhofer Institute for Integrated Systems and Device Technology IISB