206,739 research outputs found
Universal behavior of giant electroresistance in epitaxial La0.67Ca0.33MnO3 thin films
We report a giant resistance drop induced by dc electrical currents in
La0.67Ca0.33MnO3 epitaxial thin films. Resistance of the patterned thin films
decreases exponentially with increasing current and a maximum drop shows at the
temperature of resistance peak Tp. Variation of resistance with current
densities can be scaled below and above Tp, respectively. This work can be
useful for the future applications of electroresistance.Comment: 13 pages, 4 figure
Laser-catalyzed spin-exchange process in a Bose-Einstein condensate
We show theoretically that it is possible to optically control collective
spin-exchange processes in spinor Bose condensates through virtual
photoassociation. The interplay between optically induced spin exchange and
spin-dependent collisions provides a flexible tool for the control of atomic
spin dynamics, including enhanced or inhibited quantum spin oscillations, the
optically-induced ferromagnetic-to-antiferromagnetic transition, and coherent
matter-wave spin conversion.Comment: 4 pages, 4 figure
The mean velocity of two-state models of molecular motor
The motion of molecular motor is essential to the biophysical functioning of
living cells. In principle, this motion can be regraded as a multiple chemical
states process. In which, the molecular motor can jump between different
chemical states, and in each chemical state, the motor moves forward or
backward in a corresponding potential. So, mathematically, the motion of
molecular motor can be described by several coupled one-dimensional hopping
models or by several coupled Fokker-Planck equations. To know the basic
properties of molecular motor, in this paper, we will give detailed analysis
about the simplest cases: in which there are only two chemical states.
Actually, many of the existing models, such as the flashing ratchet model, can
be regarded as a two-state model. From the explicit expression of the mean
velocity, we find that the mean velocity of molecular motor might be nonzero
even if the potential in each state is periodic, which means that there is no
energy input to the molecular motor in each of the two states. At the same
time, the mean velocity might be zero even if there is energy input to the
molecular motor. Generally, the velocity of molecular motor depends not only on
the potentials (or corresponding forward and backward transition rates) in the
two states, but also on the transition rates between the two chemical states
Is perpendicular magnetic anisotropy essential to all-optical ultrafast spin reversal in ferromagnets?
All-optical spin reversal presents a new opportunity for spin manipulations,
free of a magnetic field. Most of all-optical-spin-reversal ferromagnets are
found to have a perpendicular magnetic anisotropy (PMA), but it has been
unknown whether PMA is necessary for the spin reversal. Here we theoretically
investigate magnetic thin films with either PMA or in-plane magnetic anisotropy
(IMA). Our results show that the spin reversal in IMA systems is possible, but
only with a longer laser pulse and within a narrow laser parameter region. The
spin reversal does not show a strong helicity dependence where the left- and
right-circularly polarized light lead to the identical results. By contrast,
the spin reversal in PMA systems is robust, provided both the spin angular
momentum and laser field are strong enough while the magnetic anisotropy itself
is not too strong. This explains why experimentally the majority of all-optical
spin-reversal samples are found to have strong PMA and why spins in Fe
nanoparticles only cant out of plane. It is the laser-induced spin-orbit torque
that plays a key role in the spin reversal. Surprisingly, the same spin-orbit
torque results in laser-induced spin rectification in spin-mixed configuration,
a prediction that can be tested experimentally. Our results clearly point out
that PMA is essential to the spin reversal, though there is an opportunity for
in-plane spin reversal.Comment: 20 pages, 4 figures and one tabl
Switching ferromagnetic spins by an ultrafast laser pulse: Emergence of giant optical spin-orbit torque
Faster magnetic recording technology is indispensable to massive data storage
and big data sciences. {All-optical spin switching offers a possible solution},
but at present it is limited to a handful of expensive and complex rare-earth
ferrimagnets. The spin switching in more abundant ferromagnets may
significantly expand the scope of all-optical spin switching. Here by studying
40,000 ferromagnetic spins, we show that it is the optical spin-orbit torque
that determines the course of spin switching in both ferromagnets and
ferrimagnets. Spin switching occurs only if the effective spin angular momentum
of each constituent in an alloy exceeds a critical value. Because of the strong
exchange coupling, the spin switches much faster in ferromagnets than
weakly-coupled ferrimagnets. This establishes a paradigm for all-optical spin
switching. The resultant magnetic field (65 T) is so big that it will
significantly reduce high current in spintronics, thus representing the
beginning of photospintronics.Comment: 12 page2, 6 figures. Accepted to Europhysics Letters (2016). Extended
version with the supplementary information. Contribution from Indiana State
University,Europhysics Letters (2016
Effect of disorder with long-range correlation on transport in graphene nanoribbon
Transport in disordered armchair graphene nanoribbons (AGR) with long-range
correlation between quantum wire contact is investigated by transfer matrix
combined with Landauer's formula. Metal-insulator transition is induced by
disorder in neutral AGR. Thereinto, the conductance is one conductance quantum
for metallic phase and exponentially decays otherwise when the length of AGR is
infinity and far longer than its width. Similar to the case of long-range
disorder, the conductance of neutral AGR first increases and then decreases
while the conductance of doped AGR monotonically decreases, as the disorder
strength increases. In the presence of strong disorder, the conductivity
depends monotonically and non-monotonically on the aspect ratio for heavily
doped and slightly doped AGR respectively.Comment: 6 pages, 8 figures; J. Phys: Condensed Matter (May 2012
Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction
Longitudinal analysis is important in many disciplines, such as the study of
behavioral transitions in social science. Only very recently, feature selection
has drawn adequate attention in the context of longitudinal modeling. Standard
techniques, such as generalized estimating equations, have been modified to
select features by imposing sparsity-inducing regularizers. However, they do
not explicitly model how a dependent variable relies on features measured at
proximal time points. Recent graphical Granger modeling can select features in
lagged time points but ignores the temporal correlations within an individual's
repeated measurements. We propose an approach to automatically and
simultaneously determine both the relevant features and the relevant temporal
points that impact the current outcome of the dependent variable. Meanwhile,
the proposed model takes into account the non-{\em i.i.d} nature of the data by
estimating the within-individual correlations. This approach decomposes model
parameters into a summation of two components and imposes separate block-wise
LASSO penalties to each component when building a linear model in terms of the
past measurements of features. One component is used to select features
whereas the other is used to select temporal contingent points. An accelerated
gradient descent algorithm is developed to efficiently solve the related
optimization problem with detailed convergence analysis and asymptotic
analysis. Computational results on both synthetic and real world problems
demonstrate the superior performance of the proposed approach over existing
techniques.Comment: Proceedings of the 21th ACM SIGKDD International Conference on
Knowledge Discovery and Data Mining. ACM, 201
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