Variational autoencoders combined with symbolic regression extract physically meaningful representations and order parameters from raw quantum measurement data, revealing new phenomena such as corner-ordering in Rydberg arrays.
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Competition between intra-species repulsion and inter-species attraction in dual-species Rydberg chains induces real-space dynamical fragmentation with coexisting frozen and oscillatory sectors.
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Discovering quantum phenomena with Interpretable Machine Learning
Variational autoencoders combined with symbolic regression extract physically meaningful representations and order parameters from raw quantum measurement data, revealing new phenomena such as corner-ordering in Rydberg arrays.
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Long-lived revivals and real-space fragmentation in chains of multispecies Rydberg atoms
Competition between intra-species repulsion and inter-species attraction in dual-species Rydberg chains induces real-space dynamical fragmentation with coexisting frozen and oscillatory sectors.