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Found 2 papers, 1 papers with code
Fluctuation based interpretable analysis scheme for quantum many-body snapshots
Microscopically understanding and classifying phases of matter is at the heart of strongly-correlated quantum physics.
Correlator Convolutional Neural Networks: An Interpretable Architecture for Image-like Quantum Matter Data
Machine learning models are a powerful theoretical tool for analyzing data from quantum simulators, in which results of experiments are sets of snapshots of many-body states.
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