Application areas of quantum computing

Method-driven research in quantum computing is always directed at specific application areas. In manufacturing, we examine applications from many different industries, such as the automotive industry and precision manufacturing. Many problems encountered in manufacturing can be solved with the help of machine learning (ML). Quantum machine learning holds potential for many applications where conventional ML is used. This includes areas such as quality control, predictive maintenance, and simulations. Our analyses focus on identifying potential benefits of quantum computing, comparing them to conventional methods, and further developing quantum algorithms.

Hydrogen technology can play a major role in our efforts to achieve climate neutrality. At Fraunhofer IPA, we are investigating how hydrogen can be produced on an industrial scale. To this end, we implement QML and optimization methods. Quantum computers also offer an inherent advantage when it comes to simulating quantum mechanical systems. The projects use this in the search for suitable catalyst materials and also for analyzing the lifetime of electrolyzers at molecular level.