A two-body machine learning model based on Gaussian Approximation Potentials is trained to reproduce noncollinear DFT energies and fields for bcc Fe within 1 meV per spin under an adiabatic spin approximation.
Kikuchi, A theory of cooperative phenomena, Phys
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Smooth Overlap of Spin Orientations: Machine Learning Exchange Fields for Ab-initio Spin Dynamics
A two-body machine learning model based on Gaussian Approximation Potentials is trained to reproduce noncollinear DFT energies and fields for bcc Fe within 1 meV per spin under an adiabatic spin approximation.