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.
A.8, we show that the ML predictions of the DOS for (a)U≈4and (b)U≈8align well with the exact solution close to the Fermi edge, while the main deviations occur far away from it
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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.