Kernel ridge regression predicts the self-energy of 1D Hubbard models from static and dynamic mean-field features, enabling Green's functions via Dyson's equation for U/t from weak to strong coupling.
While this is certainly the case for weakly interacting systems such as molecules, we show in fig
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Machine Learning Green's Functions of Strongly Correlated Hubbard Models
Kernel ridge regression predicts the self-energy of 1D Hubbard models from static and dynamic mean-field features, enabling Green's functions via Dyson's equation for U/t from weak to strong coupling.