16,417 research outputs found
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
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