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Solving Inverse Problems with Quantum Physics-Informed Machine Learning
The project aims at developing new quantum-accelerated computational methods for solving inverse problems in real-time, building upon recent developments in classical computational engineering. By implementing these methods on emerging real-world quantum computers, we can, e.g., potentially improve the efficiency and safety of future cars, including meeting the requirements for Level 5 autonomous driving.
Field of action:
Quantum Computing
- Faculty 1 – Mathematics, Computer Science and Natural Sciences
Address:
Chair for Computational Analysis of Technical Systems, Rogowski Building, Room 222, Schinkelstraße 2, 52062 Aachen
Contact:
Dr.-Ing. Norbert Hosters
hosters@cats.rwth-aachen.de
Homepage:
https://www.cats.rwth-aachen.de/cms/cats/Der-Lehrstuhl/~odqz/Ueber-uns/lidx/1/
Status:
in preparation