  Machine learning interatomic potentials (MLIPs) based on a large dataset
obtained by density functional theory (DFT) calculation have been developed
recently. This study gives both conceptual and practical bases for the high
accuracy of MLIPs, although MLIPs have been considered to be simply an accurate
black-box description of atomic energy. We also construct the most accurate
MLIP of the elemental Ti ever reported using a linearized MLIP framework and
many angular-dependent descriptors, which also corresponds to a generalization
of the modified embedded atom method (MEAM) potential.
