Thermally-Assisted Spin-Transfer Torque Magnetization Reversal of Uniaxial Nanomagnets in Energy Space

The asymptotic behavior of switching time as a function of current for a uniaxial macrospin under the effects of both spin-torque and thermal noise is explored analytically by focusing on its diffusive energy space dynamics. The scaling dependence ($I\rightarrow 0$, $<\tau\propto\exp(-\xi(1-I)^2)$) is shown to confirm recent literature results. The analysis shows the mean switching time to be functionally independent of the angle between the spin current and magnet's uniaxial axes. These results have important implications for modeling the energetics of thermally assisted magnetization reversal of spin transfer magnetic random access memory bit cells.Comment: arXiv admin note: substantial text overlap with arXiv:1205.650

Thermally-Assisted Spin-Transfer Torque Magnetization Reversal in Uniaxial Nanomagnets

We simulate the stochastic Landau-Lifshitz-Gilbert (LLG) dynamics of a uniaxial nanomagnet out to sub-millisecond timescales using a graphical processing unit based micromagnetic code and determine the effect of geometrical tilts between the spin-current and uniaxial anisotropy axes on the thermally assisted reversal dynamics. The asymptotic behavior of the switching time ($I\rightarrow 0$, $\propto\exp(-\xi(1-I)^2)$) is approached gradually, indicating a broad crossover regime between ballistic and thermally assisted spin transfer reversal. Interestingly, the mean switching time is shown to be nearly independent of the angle between the spin current and magnet's uniaxial axes. These results have important implications for modeling the energetics of thermally assisted magnetization reversal of spin transfer magnetic random access memory bit cells.Comment: 4 pages, 2 figure

Thermally-Assisted Spin-Transfer Torque Dynamics in Energy Space

We consider the general Landau-Lifshitz-Gilbert theory underlying the magnetization dynamics of a macrospin magnet subject to spin-torque effects and thermal fluctuations. Thermally activated dynamical properties are analyzed by averaging the full magnetization equations over constant- energy orbits. After averaging, all the relevant dynamical scenarios are a function of the ratio between hard and easy axis anisotropies. We derive analytically the range of currents for which limit cycles exist and discuss the regimes in which the constant energy orbit averaging technique is applicable

Leave-one-out prediction error of systolic arterial pressure time series under paced breathing

In this paper we show that different physiological states and pathological conditions may be characterized in terms of predictability of time series signals from the underlying biological system. In particular we consider systolic arterial pressure time series from healthy subjects and Chronic Heart Failure patients, undergoing paced respiration. We model time series by the regularized least squares approach and quantify predictability by the leave-one-out error. We find that the entrainment mechanism connected to paced breath, that renders the arterial blood pressure signal more regular, thus more predictable, is less effective in patients, and this effect correlates with the seriousness of the heart failure. The leave-one-out error separates controls from patients and, when all orders of nonlinearity are taken into account, alive patients from patients for which cardiac death occurred