Learned feedback control mechanisms for a quantum system

The talk presents an example based introduction on how machine learning can be applied to a quantum system. It starts with illustrating the main concepts of quantum information science and points out essential differences between classical and quantum systems, which are important in designing AI systems. The main part of the talk is dedicated to the possible application of gravitational wave detection. It is illustrated how machine learning could potentially be used to control a quantum system, which is in our case, an interferometer for gravitational wave detection. It will be shown that in this context, the learning problem is related to learning a decision tree and how evolutionary algorithms could be applied in this particular case.