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quant-ph2025
Statistical learning on randomized data to verify quantum state approximate k-designs
Kaustav Mukherjee, Sarah Chehade, Lorenzo Versini +3
Random ensembles of pure states have proven to be extremely important in various aspects of quantum physics such as benchmarking the performance of quantum circuits, testing for qu…
quant-ph2024
Quantum network tomography of Rydberg arrays by machine learning
Kaustav Mukherjee, Johannes Schachenmayer, Shannon Whitlock +1
Configurable arrays of optically trapped Rydberg atoms are a versatile platform for quantum computation and quantum simulation, also allowing controllable decoherence. We demonstra…
quant-ph2024
Automated quantum system modeling with machine learning
Kaustav Mukherjee, Johannes Schachenmayer, Shannon Whitlock +1
Despite the complexity of quantum systems in the real world, models with just a few effective many-body states often suffice to describe their quantum dynamics, provided decoherenc…