Quantum Computing Research at DLR

Langer, Stefan

Quantum computing has the potential to become one of the key technologies of the 21st century. In order to achieve this, on the one hand, it is necessary to tackle the challenges that exist in the area of hardware in the construction of industrial-grade quantum computers, but on the other hand, questions about how exactly the possibilities of a quantum computer can be used to reach the expected acceleration also play a major role. In order to answer both questions together, DLR has founded the Quantum Computing Initiative to research the possibilities of this new technology in a network of external partners and internal projects. In addition to the presentation of the DLR quantum computing initiative, another focus of the talk will be to present methods for accelerating computationally expensive simulations, e.g. in the field of flow simulation, with the help of quantum computers.

Bertrand Georgeot

Lobe, Elisabeth

We present on the QC activities at DLR within the Quantum Computing Initiative.

Vijay Kumar Vishwakarma, Soumya Ranjan Jena

Vijay Kumar Vishwakarma, Soumya Ranjan Jena

Christoph Räth, Joel Steinegger, Fabian Fischbach

The application of AI-based forecasting methods has led to great progress in the prediction of complex systems. Among the AI-methods being used reservoir computing (RC) turns out to be so far the most promising approach as it combines superior prediction results with little CPU-needs for training. In Quantum Reservoir Computing (QRC) the reservoir that is commonly a random network, is replaced by a system of entangled qubits. Using a spin-network as ad hoc quantum reservoir it was demonstrated that a NARMA process can be well predicted using as few as 10 qubits [1]. Our recent first results suggest that even a 4-6 qubit system may be sufficient to predict the Lorenz-system as well as with “conventional” RC [2]. In the forthcoming research project “Neuromorphic Quantum Computing (NeMoQC)” within the framework of the DLR Quantum Computing Initiative (QCI) we will now investigate systematically which quantum reservoirs are best suited for prediction and optimization tasks. In a software/hardware codesign we will seek for hardware realizations of QRC. Further, these newly developed QC-based forecasting and optimization methods are to be utilized in real world applications. Industrial partners for both the hardware design and the applications in real world use cases are welcome to join our project. [1] R. Martinez-Pena et al., PRL, 127, 100502 (2021) [2] J. Steinegger, Masterthesis LMU (ongoing)