A self-consistent treatment of non-equilibrium spin torques in magnetic multilayers

It is known that the transfer of spin angular momenta between current carriers and local moments occurs near the interface of magnetic layers when their moments are non-collinear. However, to determine the magnitude of the transfer, one should calculate the spin transport properties far beyond the interface regions. Based on the spin diffusion equation, we present a self-consistent approach to evaluate the spin torque for a number of layered structures. One of the salient features is that the longitudinal and transverse components of spin accumulations are inter-twined from one layer to the next, and thus, the spin torque could be significantly amplified with respect to treatments which concentrate solely on the transport at the interface due to the presence of the much longer longitudinal spin diffusion length. We conclude that bare spin currents do not properly estimate the spin angular momentum transferred between to the magnetic background; the spin transfer that occurs at interfaces should be self-consistently determined by embedding it in our globally diffuse transport calculations.Comment: 21 pages, 6 figure

Layer thickness dependence of the current induced effective field vector in Ta|CoFeB|MgO

The role of current induced effective magnetic field in ultrathin magnetic heterostructures is increasingly gaining interest since it can provide efficient ways of manipulating magnetization electrically. Two effects, known as the Rashba spin orbit field and the spin Hall spin torque, have been reported to be responsible for the generation of the effective field. However, quantitative understanding of the effective field, including its direction with respect to the current flow, is lacking. Here we show vector measurements of the current induced effective field in Ta|CoFeB|MgO heterostructrures. The effective field shows significant dependence on the Ta and CoFeB layers' thickness. In particular, 1 nm thickness variation of the Ta layer can result in nearly two orders of magnitude difference in the effective field. Moreover, its sign changes when the Ta layer thickness is reduced, indicating that there are two competing effects that contribute to the effective field. The relative size of the effective field vector components, directed transverse and parallel to the current flow, varies as the Ta thickness is changed. Our results illustrate the profound characteristics of just a few atomic layer thick metals and their influence on magnetization dynamics

Current-Driven Magnetization Dynamics in Magnetic Multilayers

We develop a quantum analog of the classical spin-torque model for current-driven magnetic dynamics. The current-driven magnetic excitation at finite field becomes significantly incoherent. This excitation is described by an effective magnetic temperature rather than a coherent precession as in the spin-torque model. However, both the spin-torque and effective temperature approximations give qualitatively similar switching diagrams in the current-field coordinates, showing the need for detailed experiments to establish the proper physical model for current-driven dynamics.Comment: 5 pages, 2 figure

Influence of a Uniform Current on Collective Magnetization Dynamics in a Ferromagnetic Metal

We discuss the influence of a uniform current, $\vec{j}$, on the magnetization dynamics of a ferromagnetic metal. We find that the magnon energy $\epsilon(\vec{q})$ has a current-induced contribution proportional to $\vec{q}\cdot \vec{\cal J}$, where $\vec{\cal J}$ is the spin-current, and predict that collective dynamics will be more strongly damped at finite ${\vec j}$. We obtain similar results for models with and without local moment participation in the magnetic order. For transition metal ferromagnets, we estimate that the uniform magnetic state will be destabilized for $j \gtrsim 10^{9} {\rm A} {\rm cm}^{-2}$. We discuss the relationship of this effect to the spin-torque effects that alter magnetization dynamics in inhomogeneous magnetic systems.Comment: 12 pages, 2 figure

Spin injection into a ballistic semiconductor microstructure

A theory of spin injection across a ballistic ferromagnet-semiconductor-ferromagnet junction is developed for the Boltzmann regime. Spin injection coefficient $\gamma$ is suppressed by the Sharvin resistance of the semiconductor $r_N^*=(h/e^2)(\pi^2/S_N)$, where $S_N$ is the Fermi-surface cross-section. It competes with the diffusion resistances of the ferromagnets $r_F$, and $\gamma\sim r_F/r_N^*\ll 1$ in the absence of contact barriers. Efficient spin injection can be ensured by contact barriers. Explicit formulae for the junction resistance and the spin-valve effect are presented.Comment: 5 pages, 2 column REVTeX. Explicit prescription relating the results of the ballistic and diffusive theories of spin injection is added. To this end, some notations are changed. Three references added, typos correcte

Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration.

Perceptual multistability is a phenomenon in which alternate interpretations of a fixed stimulus are perceived intermittently. Although correlates between activity in specific cortical areas and perception have been found, the complex patterns of activity and the underlying mechanisms that gate multistable perception are little understood. Here, we present a neural field competition model in which competing states are represented in a continuous feature space. Bifurcation analysis is used to describe the different types of complex spatio-temporal dynamics produced by the model in terms of several parameters and for different inputs. The dynamics of the model was then compared to human perception investigated psychophysically during long presentations of an ambiguous, multistable motion pattern known as the barberpole illusion. In order to do this, the model is operated in a parameter range where known physiological response properties are reproduced whilst also working close to bifurcation. The model accounts for characteristic behaviour from the psychophysical experiments in terms of the type of switching observed and changes in the rate of switching with respect to contrast. In this way, the modelling study sheds light on the underlying mechanisms that drive perceptual switching in different contrast regimes. The general approach presented is applicable to a broad range of perceptual competition problems in which spatial interactions play a role

Unified treatment of spin torques using a coupled magnetisation dynamics and three-dimensional spin current solver

A three-dimensional spin current solver based on a generalised spin drift-diffusion description, including the bulk and interfacial spin Hall effects, is integrated with a magnetisation dynamics solver. The resulting model is shown to simultaneously reproduce the spin-orbit torques generated using the spin Hall effect, spin pumping torques generated by magnetisation dynamics in multilayers, as well as the spin transfer torques acting on magnetisation regions with spatial gradients, whilst field-like and spin-like torques are reproduced in a spin valve geometry. Two approaches to modelling interfaces are analysed, one based on the spin mixing conductance and the other based on continuity of spin currents where the spin dephasing length governs the absorption of transverse spin components. In both cases analytical formulas are derived for the spin-orbit torques in a heavy metal / ferromagnet bilayer geometry, showing in general both field-like and damping-like torques are generated. The limitations of the analytical approach are discussed, showing that even in a simple bilayer geometry, due to the non-uniformity of the spin currents, a full three-dimensional treatment is required. The model is further applied to the analysis of the spin Hall angle in Pt by reproducing published experimental ferromagnetic resonance data in the bilayer geometry

Dynamics of temporally interleaved percept-choice sequences: interaction via adaptation in shared neural populations

At the onset of visually ambiguous or conflicting stimuli, our visual system quickly ‘chooses’ one of the possible percepts. Interrupted presentation of the same stimuli has revealed that each percept-choice depends strongly on the history of previous choices and the duration of the interruptions. Recent psychophysics and modeling has discovered increasingly rich dynamical structure in such percept-choice sequences, and explained or predicted these patterns in terms of simple neural mechanisms: fast cross-inhibition and slow shunting adaptation that also causes a near-threshold facilitatory effect. However, we still lack a clear understanding of the dynamical interactions between two distinct, temporally interleaved, percept-choice sequences—a type of experiment that probes which feature-level neural network connectivity and dynamics allow the visual system to resolve the vast ambiguity of everyday vision. Here, we fill this gap. We first show that a simple column-structured neural network captures the known phenomenology, and then identify and analyze the crucial underlying mechanism via two stages of model-reduction: A 6-population reduction shows how temporally well-separated sequences become coupled via adaptation in neurons that are shared between the populations driven by either of the two sequences. The essential dynamics can then be reduced further, to a set of iterated adaptation-maps. This enables detailed analysis, resulting in the prediction of phase-diagrams of possible sequence-pair patterns and their response to perturbations. These predictions invite a variety of future experiments