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.
Nnqs-transformer: an efficient and scalable neural network quantum states approach for ab initio quantum chemistry
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cond-mat.str-el 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.