Machine Learning Approach for Data Analysis of Magnetic Orbital Moments and Magnetocrystalline Anisotropy in Transition-Metal Thin Films on MgO(001)
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Using the Least Absolute Shrinkage and Selection Operator (LASSO) technique, we analyze a long-standing issue in the field of magnetism: the relationship between orbital magnetic moments and magnetocrystalline anisotropy (MCA) energy in transition-metal thin films. Our LASSO regression utilizes the data obtained from first principles calculations for single slabs with six atomic-layers of binary Au-Fe, Au-Co, and Fe-Co films on MgO(001). In the case of Fe-Co thin films, we have successfully regressed the MCA energy against the anisotropy of orbital moments along the in-plane and the perpendicular plane directions, giving a linear behavior. For the Au-Fe and Au-Co thin films, however, our data-driven analysis shows no relation between the MCA energy and the anisotropy of orbital moments.
KeywordsFirst principles calculation magnetocrystalline anisotropy orbital magnetic moment single slab model
Work was supported by JSPS KAKENHI Grant Numbers 15H05702, 16K05415, and 17H06154, and the Cooperative Research Program of Network Joint Research Center for Materials and Devices, and Center for Spintronics Research Network (CSRN), Osaka University. Computations were performed at the Research Institute for Information Technology, Kyushu University.