Research

In my research, I aim to understand strongly-interacting quantum many-body systems with novel analysis tools. To this end, I combine state-of-the art numerical methods established in condensed matter research, intuitive physical pictures, close collaboration with quantum simulation experiments, and machine learning techniques, such as for example neural networks.

Quantum simulation experiments offer a new perspective on strongly-correlated many-body systems: through a high degree of control and tunability, microscopic models can be directly realized. In many experiments, readout with single-site resolution is possible, enabling a direct real-space view on condensed matter problems. For the most difficult questions, it can even be challenging to find the right questions to ask, and the right observables to measure. For example from Fock space snapshots of a quantum many-body system, correlations up to arbitrary order can now be studied. Quantum simulation experiments also provide a bridge between theoretical models and real materials. Similar probes as in condensed matter experiments, such as spectroscopy, can be implemented, but in a system which realizes a clean microscopic model, without unknown coupling constants, disorder, or contributions from phonons.