Investigation of the dynamics of magnetic vortices and antivortices using micromagnetic simulations

Abstract

This thesis is focused on investigating the dynamic properties of spin textures in patterned magnetic structures by using micromagnetic simulations. These textures become particularly relevant at sub-micron length scales where the interplay between magnetostatic and exchange energy leads to unique properties that are of great interest both from a fundamental perspective and for the development of new technologies. Two different systems, a magnetic antivortex (AV) stabilized in the intersection of perpendicular microwires, and three interacting vortices in an equilateral arrangement, were considered for this study. For the first system, the AV, the formation process and the excitation spectra were investigated. Since the AV is a metastable state, the design of a host structure capable of stabilizing it requires careful consideration and it is desirable to have general guidelines that could help to optimize the AV formation rate. The role of the shape anisotropy and the field dependence of the AV formation process is discussed in detail. Micromagnetic simulations along with magneto-optical Kerr effect and magnetic force microscopy measurements demonstrated that the asymmetry in the structure can be used to promote the formation of such AV's and that regions with lower shape anisotropy lead the reversal process, while simulations of the dynamic response show that when the system is excited with in-plane and out-of-plane external magnetic fields, normal modes with azimuthal and radial characteristics are found, respectively, in addition to the low frequency gyrotropic mode. The modes are influenced by the spin texture in the intersection, which offers additional possibilities for manipulating spin waves (SW). For the second system, three interacting vortices are simulated and compared with a simple analytical model that considers only dipolar interactions. It was found that when a fitting parameter is introduced to the model, the main features of the simulations are captured better than more complex models, which suggest that this simple framework can be used to accurately model more complex vortex networks.