Studying magnetic superstructures
In this issue, we highlight two studies on moiré magnets. Li et al. developed a rotational and time-reversal equivariant neural network that can accurately model the dependence of the density functional theory Hamiltonian on atomic and magnetic superstructures. In another study, Yang et al. proposed a microscopic moiré spin model that enables the description of moiré magnetic exchange interactions via a sliding-mapping method. These methodological developments open opportunities for predicting emerging phenomena of magnetic superstructures, such as magnetic skyrmions. The cover image depicts — from top to bottom — magnetic field lines, magnetic configurations, a moiré lattice, Hamiltonian matrices, and neural networks.
See Editorial , Li et al. and Yang et al.