178 research outputs found
Spin relaxation in Rashba rings
Spin relaxation dynamics in rings with Rashba spin-orbit coupling is
investigated using spin kinetic equation. We find that the spin relaxation in
rings occurs toward a persistent spin configuration whose final shape depends
on the initial spin polarization profile. As an example, it is shown that a
homogeneous parallel to the ring axis spin polarization transforms into a
persistent crown-like spin structure. It is demonstrated that the ring geometry
introduces a geometrical contribution to the spin relaxation rate speeding up
the transient dynamics. Moreover, we identify several persistent spin
configurations as well as calculate the Green function of spin kinetic
equation
On the validity of memristor modeling in the neural network literature
An analysis of the literature shows that there are two types of
non-memristive models that have been widely used in the modeling of so-called
"memristive" neural networks. Here, we demonstrate that such models have
nothing in common with the concept of memristive elements: they describe either
non-linear resistors or certain bi-state systems, which all are devices without
memory. Therefore, the results presented in a significant number of
publications are at least questionable, if not completely irrelevant to the
actual field of memristive neural networks
SPICE model of memristive devices with threshold
Although memristive devices with threshold voltages are the norm rather than
the exception in experimentally realizable systems, their SPICE programming is
not yet common. Here, we show how to implement such systems in the SPICE
environment. Specifically, we present SPICE models of a popular
voltage-controlled memristive system specified by five different parameters for
PSPICE and NGSPICE circuit simulators. We expect this implementation to find
widespread use in circuits design and testing
On the physical properties of memristive, memcapacitive, and meminductive systems
We discuss the physical properties of realistic memristive, memcapacitive and
meminductive systems. In particular, by employing the well-known theory of
response functions and microscopic derivations, we show that resistors,
capacitors and inductors with memory emerge naturally in the response of
systems - especially those of nanoscale dimensions - subjected to external
perturbations. As a consequence, since memristances, memcapacitances, and
meminductances are simply response functions, they are not necessarily finite.
This means that, unlike what has always been argued in some literature,
diverging and non-crossing input-output curves of all these memory elements are
physically possible in both quantum and classical regimes. For similar reasons,
it is not surprising to find memcapacitances and meminductances that acquire
negative values at certain times during dynamics, while the passivity criterion
of memristive systems imposes always a non-negative value on the resistance at
any given time. We finally show that ideal memristors, namely those whose state
depends only on the charge that flows through them (or on the history of the
voltage) are subject to very strict physical conditions and are unable to
protect their memory state against the unavoidable fluctuations, and therefore
are susceptible to a stochastic catastrophe. Similar considerations apply to
ideal memcapacitors and meminductors
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