A semiclassical coherent-state approximation for the Hubbard model qualitatively reproduces exact results for particle number, double occupancy, hopping, and spin correlations in one- and two-site systems.
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Generalized ML force fields reproduce non-collinear magnetic orders on lattices and predict voltage-driven domain-wall motion in itinerant magnets using extensions to nonequilibrium torques.
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Semiclassical representation of the Hubbard model
A semiclassical coherent-state approximation for the Hubbard model qualitatively reproduces exact results for particle number, double occupancy, hopping, and spin correlations in one- and two-site systems.
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Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems
Generalized ML force fields reproduce non-collinear magnetic orders on lattices and predict voltage-driven domain-wall motion in itinerant magnets using extensions to nonequilibrium torques.