The detection of gravitational waves (GWs) has opened a new window on the universe, through which we can study the physics of black-hole and neutron-star mergers. By analyzing GWs we can infer properties of the corresponding astrophysical systems. Current analysis methods are however too computationally expensive to deal with the growing amount of data. My research is thus concerned with the development of more efficient methods for the GW analysis using powerful machine learning methods.

The central paradigm of quantum optics is the absorption and emission of radiation by quantum emitters. When the coupling between an emitter and its environment becomes strong, intriguing radiative properties can be engineered, such as directional emission patterns or strongly modified emission rates. This project aims at accessing such effects in a system of ultracold atoms in optical lattices where artificial emitters decay by emitting matter waves rather than optical radiation.