New theoretical physics research introduces a simulation method of machine-learning-based effective Hamiltonian for super-large-scale atomic structures. This effective Hamiltonian method could simulate much larger structures than the methods based on quantum mechanisms and classical mechanics.
The findings are published in npj Computational Materials under the title, “Active learning of effective Hamiltonian for super-large-scale atomic structures.” The paper was authored by an international team of physicists, including the University of Arkansas, Nanjing University, and the University of Luxembourg.
In ferroelectrics and dielectrics, there is one kind of structure—mesoscopic structure, which usually has atoms more than millions.
