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Machine learning for many-body physics: efficient solution of dynamical mean-field theory
Louis-François Arsenault, O. Anatole von Lilienfeld, Andrew J. Millis
Machine learning methods for solving the equations of dynamical mean-field theory are developed. The method is demonstrated on the three dimensional Hubbard model. The key technica…
Metal-insulator transitions in GdTiO3/SrTiO3 superlattices
Se Young Park, Andrew J. Millis
The density functional plus U method is used to obtain the electronic structure, lattice relaxation and metal-insulator phase diagram of superlattices consisting of layers of G…
Density functional versus spin-density functional and the choice of correlated subspace in multi-variable effective action theories of electronic structure
Hyowon Park, Andrew J. Millis, Chris A. Marianetti
Modern extensions of density functional theory such as the density functional theory plus U and the density functional theory plus dynamical mean-field theory require choices, incl…
Strain Control of Electronic Phase in Rare Earth Nickelates
Zhuoran He, Andrew J. Millis
We use density functional plus methods to study the effects of a tensile or compressive substrate strain on the charge-ordered insulating phase of LuNiO. The numerical resu…