Optimal readout of quantum simulators

• Applicants: Professorin Dr. Monika Aidelsburger; Professor Dr. Martin Gärttner; Professor Dr. Christof Weitenberg
• Subject Area: Optics, Quantum Optics and Physics of Atoms, Molecules and Plasmas ; Theoretical Condensed Matter Physics
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 550495627

The project develops machine-learning enhanced technique for improving the processing of data from ultracold atom experiments. We optimize the analysis of fluorescence and absorption images in optical lattice experiments where site-resolved atom numbers and phases are to be reconstructed. Furthermore, we develop methods for the reconstruction of (sub)system states that optimally exploit prior knowledge in the form of physical constraints or machine-learning inspired variational ansatz functions. Finally, we develop adaptive measurement strategies for choosing the optimal measurement settings based on previous observations on the system. Here machine-learning methods allow us to overcome the prohibitive numerical complexity of traditional methods. In alignment with the common goals of the RU this research will open up new possibilities for using quantum simulation experiments to explore the physics of complex quantum many-body systems.

• DFG Programme: Research Units
• Subproject of: FOR 5919: Machine learning for complex quantum states
• Co-Investigators: Professorin Dr. Annabelle Bohrdt; Professor Dr. Florian Kai Marquardt