The “QuaST” (quantum-enabling services and tools for industrial applications) project, led by Fraunhofer IKS, is now underway. Jeanette Lorenz, Senior Scientist at the Quantum Computing Department of Fraunhofer IKS, heads the project. In this interview, she explains what QuaST is all about.
February 3, 2022
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Quantum computing at Fraunhofer IKS
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H. T. Hengl:
Jeanette, what is the core aim of the QuaST project?
Jeanette Lorenz:
We want to provide companies of all sizes with easy access to quantum computing (QC). More specifically, industrial end users will only need to have minimal knowledge of QC hardware and software to automatically receive easily accessible and reliable QC-supported solutions for their application problems. Not only that, but they will be able to use the hardware more efficiently. In the QuaST project, these application problems refer to optimization problems in various industries and processes. In other words, companies should be able to benefit from the advantages of QC right from the start.
H. T. Hengl:
This doesn’t sound very ambitious...
Jeanette Lorenz:
No, it all seems very simple at first glance, but there’s a lot more to it than meets the eye. QC is a completely new technology and there is still a lot of work to be done on each part of the software stack. For instance, the question remains as to how to combine QC with traditional computers and systems. In QuaST, we are faced with the challenge of developing a solution that automatically deconstructs individual optimization problems into parts requiring either classical, high performance or quantum computing. As well as this, because of the small size of current quantum computations, all of the algorithms used are hybrid algorithms, which continuously split the computational tasks between classical and QC systems. Even linking the systems presents a major challenge. Another aspect to consider is how to optimize mapping the QC part onto the hardware. Lastly, it’s also necessary to evaluate and verify the final implementation on the QC system in terms of the applications. When you consider the bigger picture, it is clear to see that all project partners are facing a real challenge.
H. T. Hengl:
You briefly mentioned optimization problems — can you explain in concrete terms what these are?
Jeanette Lorenz:
In this context, optimization problems refer to our partners’ application problems. The project’s goal is to find more efficient solutions to these. For example, Infineon is addressing scheduling problems in semiconductor production. The issue here is knowing when to schedule and implement the respective steps in the highly sensitive production process to achieve maximum efficiency.
DATEV is interested in optimizing business forecasting. Fraunhofer IISB is working on network optimization, while Roche — an associated partner of Fraunhofer IKS — is researching the use of QC in drug development.
A total of seven partners are involved in the QuaST project. The Fraunhofer-Gesellschaft is represented by the following institutes: Fraunhofer IKS, AISEC, IIS and IISB. The project partners also include the Leibniz Supercomputing Center and the Technical University of Munich (TUM) as well as DATEV eG, Infineon, IQM and ParityQC. The German Aerospace Center (DLR) is the project sponsor.
H. T. Hengl:
Which research topics is Fraunhofer IKS focusing on?
Jeanette Lorenz:
Fraunhofer IKS is involved in deconstructing optimization problems into “sub-problems,” which I mentioned earlier. Our work in the project is largely characterized by the evaluation and verification of the final application. From a mathematics’ perspective, this means checking the probabilistic properties of the quantum computer.
We are also collaborating with our industrial partners, for example, in the form of training programs and best practice guides.
H. T. Hengl:
Quantum computing is seen as one of the key technological topics of the future. Can you briefly explain what makes quantum computing so special? What can a quantum computer do that conventional computers have failed to do so far?
Jeanette Lorenz:
In the long term, error-corrected quantum computers are expected to provide significantly faster solutions for several classes of problem, for example, search algorithms, which is also relevant for the optimization problems mentioned, or for simulation problems. Classical computers are poorly suited to these tasks. Quantum computers, on the other hand, automatically facilitate parallel processing because they require fewer qubits to store information. They may even allow for a greater information capacity in certain algorithms. Despite their capabilities, though, quantum computers will not replace classical computers, but rather quantum processing units will be used alongside classical systems.
