2,713 research outputs found
Ab initio studies of the spin-transfer torque in tunnel junctions
We calculate the spin-transfer torque in Fe/MgO/Fe tunnel junctions and
compare the results to those for all-metallic junctions. We show that the
spin-transfer torque is interfacial in the ferromagnetic layer to a greater
degree than in all-metallic junctions. This result originates in the half
metallic behavior of Fe for the states at the Brillouin zone center;
in contrast to all-metallic structures, dephasing does not play an important
role. We further show that it is possible to get a component of the torque that
is out of the plane of the magnetizations and that is linear in the bias.
However, observation of such a torque requires highly ideal samples. In samples
with typical interfacial roughness, the torque is similar to that in
all-metallic multilayers, although for different reasons.Comment: 5 pages, 4 figure
Identification of the dominant precession damping mechanism in Fe, Co, and Ni by first-principles calculations
The Landau-Lifshitz equation reliably describes magnetization dynamics using
a phenomenological treatment of damping. This paper presents first-principles
calculations of the damping parameters for Fe, Co, and Ni that quantitatively
agree with existing ferromagnetic resonance measurements. This agreement
establishes the dominant damping mechanism for these systems and takes a
significant step toward predicting and tailoring the damping constants of new
materials.Comment: 4 pages, 1 figur
Macrospin Models of Spin Transfer Dynamics
The current-induced magnetization dynamics of a spin valve are studied using
a macrospin (single domain) approximation and numerical solutions of a
generalized Landau-Lifshitz-Gilbert equation. For the purpose of quantitative
comparison with experiment [Kiselev {\it et al.} Nature {\bf 425}, 380 (2003)],
we calculate the resistance and microwave power as a function of current and
external field including the effects of anisotropies, damping, spin-transfer
torque, thermal fluctuations, spin-pumping, and incomplete absorption of
transverse spin current. While many features of experiment appear in the
simulations, there are two significant discrepancies: the current dependence of
the precession frequency and the presence/absence of a microwave quiet magnetic
phase with a distinct magnetoresistance signature. Comparison is made with
micromagnetic simulations designed to model the same experiment.Comment: 14 pages, 14 figures. Email [email protected] for a
pdf with higher quality figure
Overcoming device unreliability with continuous learning in a population coding based computing system
The brain, which uses redundancy and continuous learning to overcome the
unreliability of its components, provides a promising path to building
computing systems that are robust to the unreliability of their constituent
nanodevices. In this work, we illustrate this path by a computing system based
on population coding with magnetic tunnel junctions that implement both neurons
and synaptic weights. We show that equipping such a system with continuous
learning enables it to recover from the loss of neurons and makes it possible
to use unreliable synaptic weights (i.e. low energy barrier magnetic memories).
There is a tradeoff between power consumption and precision because low energy
barrier memories consume less energy than high barrier ones. For a given
precision, there is an optimal number of neurons and an optimal energy barrier
for the weights that leads to minimum power consumption
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