This review explains the relationship between density functional theory and strongly
correlated models using the simplest possible example, the two-site Hubbard model. The …

Recently, metal-free graphitic carbon nitride (gC 3 N 4) has been recognized as a potential
candidate for high-performance photocatalytic hydrogen production while challenges still …

Including prior knowledge is important for effective machine learning models in physics and
is usually achieved by explicitly adding loss terms or constraints on model architectures …

Two-dimensional graphitic carbon nitride (2D gC 3 N 4) nanostructures have been the focus
of substantial research interest recently owing to their promising photoactive properties for …

Density-corrected density functional theory (DC-DFT) is enjoying substantial success in
improving semilocal DFT calculations in a wide variety of chemical problems. This paper …

We argue that any general mathematical measure of density error, no matter how
reasonable, is too arbitrary to be of universal use. However, the energy functional itself …

We use the density-matrix renormalization group, applied to a one-dimensional model of
continuum Hamiltonians, to accurately solve chains of hydrogen atoms of various …

We incorporate in the Kohn-Sham self-consistent equation a trained neural-network
projection from the charge density distribution to the Hartree-exchange-correlation potential …

Standard density functional approximations often give questionable results for odd-electron
radical complexes, with the error typically attributed to self-interaction. In density corrected …

We explore a variety of unsolved problems in density functional theory, where
mathematicians might prove useful. We give the background and context of the different …