Fig. 2: On-the-fly machine learning of parametrization for BaTiO3.
From: Active learning of effective Hamiltonian for super-large-scale atomic structures
a–c—(a) Bayesian error, (b) potential energy per formal unit (f.u.), and (c) local dipolar mode u in the learning/fitting process as functions of MD steps. The dash line in panel (a) denotes the threshold to perform FP calculations. The blue and orange lines in panel (b) represent the energy computed by effective Hamiltonian model during the fitting process and with the the final parameter after the learning process, respectively. Phase diagram by effective Hamiltonian simulations with the parameters from (d) direct FP calculations using the method in ref. 7 and (e) on-the-fly learning. Absolute values of local mode u of BaTiO3 as functions of temperature are shown in panel (d), (e). Here, R, O, T, and C denote the rhombohedral, orthogonal, tetrahedral, and cubic phases, respectively.
