Micromagnetic Simulation of Nanoscale Films with Perpendicular Anisotropy

A model is studied for the theoretical description of nanoscale magnetic films with high perpendicular anisotropy. In the model the magnetic film is described in terms of single domain magnetic grains with Ising-like behavior, interacting via exchange as well as via dipolar forces. Additionally, the model contains an energy barrier and a coupling to an external magnetic field. Disorder is taken into account in order to describe realistic domain and domain wall structures. The influence of a finite temperature as well as the dynamics can be modeled by a Monte Carlo simulation. Many of the experimental findings can be investigated and at least partly understood by the model introduced above. For thin films the magnetisation reversal is driven by domain wall motion. The results for the field and temperature dependence of the domain wall velocity suggest that for thin films hysteresis can be described as a depinning transition of the domain walls rounded by thermal activation for finite temperatures.Comment: Revtex, Postscript Figures, to be published in J. Appl.Phy

Domain State Model for Exchange Bias

Monte Carlo simulations of a system consisting of a ferromagnetic layer exchange coupled to a diluted antiferromagnetic layer described by a classical spin model show a strong dependence of the exchange bias on the degree of dilution in agreement with recent experimental observations on Co/CoO bilayers. These simulations reveal that diluting the antiferromagnet leads to the formation of domains in the volume of the antiferromagnet carrying a remanent surplus magnetization which causes and controls exchange bias. To further support this domain state model for exchange bias we study in the present paper the dependence of the bias field on the thickness of the antiferromagnetic layer. It is shown that the bias field strongly increases with increasing film thickness and eventually goes over a maximum before it levels out for large thicknesses. These findings are in full agreement with experiments.Comment: 8 pages latex, 3 postscript figure

From synaptic interactions to collective dynamics in random neuronal networks models: critical role of eigenvectors and transient behavior

The study of neuronal interactions is currently at the center of several neuroscience big collaborative projects (including the Human Connectome, the Blue Brain, the Brainome, etc.) which attempt to obtain a detailed map of the entire brain matrix. Under certain constraints, mathematical theory can advance predictions of the expected neural dynamics based solely on the statistical properties of such synaptic interaction matrix. This work explores the application of free random variables (FRV) to the study of large synaptic interaction matrices. Besides recovering in a straightforward way known results on eigenspectra of neural networks, we extend them to heavy-tailed distributions of interactions. More importantly, we derive analytically the behavior of eigenvector overlaps, which determine stability of the spectra. We observe that upon imposing the neuronal excitation/inhibition balance, although the eigenvalues remain unchanged, their stability dramatically decreases due to strong non-orthogonality of associated eigenvectors. It leads us to the conclusion that the understanding of the temporal evolution of asymmetric neural networks requires considering the entangled dynamics of both eigenvectors and eigenvalues, which might bear consequences for learning and memory processes in these models. Considering the success of FRV analysis in a wide variety of branches disciplines, we hope that the results presented here foster additional application of these ideas in the area of brain sciences.Comment: 24 pages + 4 pages of refs, 8 figure

Modeling exchange bias microscopically

Exchange bias is a horizontal shift of the hysteresis loop observed for a ferromagnetic layer in contact with an antiferromagnetic layer. Since exchange bias is related to the spin structure of the antiferromagnet, for its fundamental understanding a detailed knowledge of the physics of the antiferromagnetic layer is inevitable. A model is investigated where domains are formed in the volume of the AFM stabilized by dilution. These domains become frozen during the initial cooling procedure carrying a remanent net magnetization which causes and controls exchange bias. Varying the anisotropy of the antiferromagnet we find a nontrivial dependence of the exchange bias on the anisotropy of the antiferromagnet.Comment: 7 pages, 5 figure