An FFT-Based Direct Splitting Method for Efficient Micromagnetic Simulations

Abstract

The Landau--Lifshitz--Gilbert equation poses significant challenges for numerical simulation due to its nonlinearity, nonconvex unit-length constraint, and nonlocal field contributions. Existing implicit or semi-implicit schemes exhibit unconditional stability but require repeated solution of nonlinear or linearized systems, resulting in high computational costs. In this work, we revisit the tangent plane formulation and show that the resulting discrete problem at each time step can be written as a generalized saddle-point system. Exploiting this structure, we develop a matrix-free preconditioner for the implicit Euler scheme by combining FFT-based techniques with a splitting iteration method. We show that each component in the splitting method can be efficiently implemented in a direct fashion via fast Poisson solvers, enabling the design of an efficient preconditioner for iterative solvers. To enhance geometric consistency of the tangent vector and reduce projection steps, a Crank--Nicolson scheme is further investigated, retaining the same algorithmic structure as the Euler scheme, thus allowing direct reuse of preconditioners and solvers. Extensive 2D and 3D numerical experiments are conducted to validate the framework, demonstrating accurate constraint preservation, improved computational efficiency, and robust solver performance. The proposed approach is shown to scale effectively for large-scale micromagnetic simulations, making it suitable for practical applications in complex magnetic systems.