Prof. Dr. Annabelle Bohrdt
Bohrdt Group
Machine learning meets quantum many-body physics
We develop and apply novel analysis tools to understand strongly interacting quantum many-body systems. Our work sits at the intersection of condensed matter theory, quantum simulation experiments, and machine learning.
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Quantum simulation
Close collaboration with cold-atom experiments, enabling real-space views of condensed matter phenomena with single-site resolution.
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Machine learning
Neural networks and other ML techniques for analyzing quantum data, state tomography, and representing quantum many-body states.
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Strongly correlated systems
Numerical and analytical study of Fermi-Hubbard type models, pairing mechanisms, and spectroscopic probes in doped quantum magnets.
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For more details, see our Research page. If you are interested in joining the group, visit Join us.