Correlator convolutional neural networks as an interpretable architecture for image-like quantum matter data
Physical principles underlying machine learning analysis of quantum gas microscopy data are not well understood. Here the authors develop a neural network based approach to classify image data in terms of multi-site correlation functions and reveal the role of fourth-order correlations in the Fermi-...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-06-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-23952-w |