arXiv subjects

Y. V. Pershin

Publications and source records attributed to Y. V. Pershin.

At least 37 records · Page 2Linked to original sources

arXiv2019

Transient dynamics of pulse-driven memristors in the presence of a stable fixed point

Some memristors are quite interesting from the point of view of dynamical systems. When driven by narrow pulses of alternating polarities, their dynamics has a stable fixed point, which may be useful for future applications. We study the transient dynamics of two types of memristors characterized by a stable fixed point using a time-averaged evolution equation. Time-averaged trajectories of the Biolek window function memristor and resistor-threshold type memristor circuit (an effective memristor) are determined analytically, and the times of relaxation to the stable fixed point are found. Our analytical results are in perfect agreement with the results of numerical simulations.

cs.ET↗

arXiv2019

Importance of the window function choice for the predictive modelling of memristors

Window functions are widely employed in memristor models to restrict the changes of the internal state variables to specified intervals. Here we show that the actual choice of window function is of significant importance for the predictive modelling of memristors. Using a recently formulated theory of memristor attractors, we demonstrate that whether stable fixed points exist depends on the type of window function used in the model. Our main findings are formulated in terms of two memristor attractor theorems, which apply to broad classes of memristor models. As an example of our findings, we predict the existence of stable fixed points in Biolek window function memristors and their absence in memristors described by the Joglekar window function, when such memristors are driven by periodic alternating polarity pulses. It is anticipated that the results of this study will contribute toward the development of more sophisticated models of memristive devices and systems.

cs.ET↗

arXiv2019

Dynamical attractors of memristors and their networks

It is shown that the time-averaged dynamics of memristors and their networks periodically driven by alternating-polarity pulses may converge to fixed-point attractors. Starting with a general memristive system model, we derive basic equations describing the fixed-point attractors and investigate attractors in the dynamics of ideal, threshold-type and second-order memristors, and memristive networks. A memristor potential function is introduced, and it is shown that in some cases the attractor identification problem can be mapped to the problem of potential function minimization. Importantly, the fixed-point attractors may only exist if the function describing the internal state dynamics depends on an internal state variable. Our findings may be used to tune the states of analog memristors, and also be relevant to memristive synapses subjected to forward- and back-propagating spikes.

nlin.CD↗

arXiv2018

A simple test for ideal memristors

An ideal memristor is defined as a resistor with memory that, when subject to a time-dependent current, $I(t)$, its resistance $R_M(q)$ depends {\it only} on the charge $q$ that has flowed through it, so that its voltage response is $V(t)=R_M(q)I(t)$. It has been argued that a clear fingerprint of these ideal memristors is a pinched hysteresis loop in their I-V curves. However, a pinched I-V hysteresis loop is not a definitive test of whether a resistor with memory is truly an ideal memristor because such a property is shared also by other resistors whose memory depends on additional internal state variables, other than the charge. Here, we introduce a very simple and {\it unambiguous} test that can be utilized to check experimentally if a resistor with memory is indeed an ideal memristor. Our test is based on the duality property of a capacitor-memristor circuit whereby, for any initial resistance states of the memristor and any form of the applied voltage, the final state of an ideal memristor must be identical to its initial state, if the capacitor charge finally returns to its initial value. In actual experiments, a sufficiently wide range of voltage amplitudes and initial states are enough to perform the test. The proposed test can help resolve some long-standing controversies still existing in the literature about whether an ideal memristor does actually exist or it is a purely mathematical concept.

cond-mat.mes-hall↗

arXiv2018

Manipulating graphene kinks through positive and negative radiation pressure effects

We introduce an idea of experimental verification of the counterintuitive negative radiation pressure effect in some classical field theories by means of buckled graphene. In this effect, a monochromatic plane wave interacting with topological solutions pulls these solutions towards the source of radiation. Using extensive molecular dynamics simulations, we investigate the traveling wave-induced motion of kinks in buckled graphene nanoribbons. It is shown that depending on the driving source frequency, amplitude and direction, the kink behavior varies from attraction to repulsion (the negative and positive radiation pressure effects, respectively). Some preliminary explanations are proposed based on the analogy to certain field theory models. Our findings open the way to a new approach to motion control on the nanoscale.

cond-mat.mes-hall↗

arXiv2017

Snap-through transition of graphene membranes for memcapacitor applications: A combined study using MD, DFT and elasticity theory

Using computational and theoretical approaches, we investigate the snap-through transition of buckled graphene membranes. Our main interest is related to the possibility of using the buckled membrane as a plate of capacitor with memory (memcapacitor). For this purpose, we performed molecular-dynamics (MD) simulations and elasticity theory calculations of the up-to-down and down-to-up snap-through transitions for membranes of several sizes. We have obtained expressions for the threshold switching forces for both up-to-down and down-to-up transitions. Moreover, the up-to-down threshold switching force was calculated using the density functional theory (DFT). Our DFT results are in general agreement with MD and analytical theory findings. Our systematic approach can be used for the description of other structures, including nanomechanical and biological ones, experiencing the snap-through transition.

cond-mat.mes-hall↗

arXiv2017

Switching synchronization in 1-D memristive networks: An exact solution

We study a switching synchronization phenomenon taking place in one-dimensional memristive networks when the memristors switch from the high to low resistance state. It is assumed that the distributions of threshold voltages and switching rates of memristors are arbitrary. Using the Laplace transform, a set of non-linear equations describing the memristors dynamics is solved exactly, without any approximations. The time dependencies of memristances are found and it is shown that the voltage falls across memristors are proportional to their threshold voltages. A compact expression for the network switching time is derived.

nlin.AO↗

arXiv2017

Kinks and antikinks of buckled graphene: A testing ground for phi^4 field model

Kinks and antikinks of the classical phi^4 field model are topological solutions connecting its two distinct ground states. Here we establish an analogy between the excitations of a long graphene nanoribbon buckled in the transverse direction and phi^4 model results. Using molecular dynamics simulations, we investigated the dynamics of a buckled graphene nanoribbon with a single kink and with a kink-antikink pair. Several features of phi^4 model have been observed including the kink-antikink capture at low energies, kink-antikink reflection at high energies, and a bounce resonance. Our results pave the way towards the experimental observation of a rich variety of phi^4 model predictions based on graphene.

cond-mat.mes-hall↗

arXiv2016

Computing with volatile memristors: An application of non-pinched hysteresis

The possibility of in-memory computing with volatile memristive devices, namely, memristors requiring a power source to sustain their memory, is demonstrated. We have adopted a hysteretic graphene-based field emission structure as a prototype of volatile memristor, which is characterized by a non-pinched hysteresis loop. Memristive model of the structure is developed and used to simulate a polymorphic circuit implementing in-memory computing gates such as the material implication. Specific regions of parameter space realizing useful logic functions are identified. Our results are applicable to other realizations of volatile memory devices.

cond-mat.mes-hall↗

arXiv2016

Metastable Memristive Lines for Signal Transmission and Information Processing Applications

Traditional studies of memristive devices have mainly focused on their applications in non-volatile information storage and information processing. Here, we demonstrate that the third fundamental component of information technologies { the transfer of information { can also be employed with memristive devices. For this purpose, we introduce a metastable memristive circuit. Combining metastable memristive circuits into a line, one obtains an architecture capable of transferring a signal edge from one space location to another. We emphasize that the suggested transmission lines employ only resistive components. Moreover, their networks (for example, Y-connected lines) have an information processing capability.

cs.ET↗

arXiv2016

The Theory of Spin Noise Spectroscopy: A Review

Direct measurements of spin fluctuations are becoming the mainstream approach for studies of complex condensed matter, molecular, nuclear, and atomic systems. This review covers recent progress in the field of optical Spin Noise Spectroscopy (SNS) with an additional goal to establish an introduction into its theoretical foundations. Various theoretical techniques that have been recently used to interpret results of SNS measurements are explained alongside with examples of their applications.

cond-mat.mes-hall↗

arXiv2016

Memristive model of hysteretic field emission from carbon nanotube arrays

Some instances of electron field emitters are characterized by frequency-dependent hysteresis in their current-voltage characteristics. We argue that such emitters can be classified as memristive systems and introduce a general framework to describe their response. As a specific example of our approach, we consider field emission from a carbon nanotube array. Our experimental results demonstrate a low-field hysteresis, which is likely caused by an electrostatic alignment of some of the nanotubes in the applied field. We formulate a memristive model of such phenomenon whose results are in agreement with the experimental results.

cond-mat.mes-hall↗

arXiv2015

Reconfigurable Transmission Lines with Memcapacitive Materials

We study transmission lines made of memory capacitive (memcapacitive) materials. The transmission properties of these lines can be adjusted on demand using an appropriate sequence of pulses. In particular, we demonstrate a pulse combination that creates a periodic modulation of dielectric properties along the line. Such a structure resembles a distributed Bragg reflector having important optical applications. We present simulation results demonstrating all major steps of such a reconfigurable device operation including reset, programming and transmission of small amplitude signals. The proposed reconfigurable transmission lines employ only passive memory materials and can be realized using available memcapacitive devices.

cond-mat.mes-hall↗

arXiv2015

Switching Synchronization in One-Dimensional Memristive Networks

We report on an astonishing switching synchronization phenomenon in one-dimensional memristive networks, which occurs when several memristive systems with different switching constants are switched from the high to low resistance state. Our numerical simulations show that such a collective behavior is especially pronounced when the applied voltage slightly exceeds the combined threshold voltage of memristive systems. Moreover, a finite increase in the network switching time is found compared to the average switching time of individual systems. An analytical model is presented to explain our observations. Using this model, we have derived asymptotic expressions for memory resistances at short and long times, which are in excellent agreement with our numerical calculations.

cond-mat.mes-hall↗

arXiv2015

A Memcomputing Pascaline

The original Pascaline was a mechanical calculator able to sum and subtract integers. It encodes information in the angles of mechanical wheels and through a set of gears, and aided by gravity, could perform the calculations. Here, we show that such a concept can be realized in electronics using memory elements such as memristive systems. By using memristive emulators we have demonstrated experimentally the memcomputing version of the mechanical Pascaline, capable of processing and storing the numerical results in the multiple levels of each memristive element. Our result is the first experimental demonstration of multidigit arithmetics with multi-level memory devices that further emphasizes the versatility and potential of memristive systems for future massively-parallel high-density computing architectures.

cs.ET↗

arXiv2014

Memcomputing and Swarm Intelligence

We explore the relation between memcomputing, namely computing with and in memory, and swarm intelligence algorithms. In particular, we show that one can design memristive networks to solve short-path optimization problems that can also be solved by ant-colony algorithms. By employing appropriate memristive elements one can demonstrate an almost one-to-one correspondence between memcomputing and ant colony optimization approaches. However, the memristive network has the capability of finding the solution in one deterministic step, compared to the stochastic multi-step ant colony optimization. This result paves the way for nanoscale hardware implementations of several swarm intelligence algorithms that are presently explored, from scheduling problems to robotics.

cs.NE↗

arXiv2013

Hybrid Spin Noise Spectroscopy and the Spin Hall Effect

Here we suggest a novel hybrid spin noise spectroscopy technique, which is sensitive to the spin Hall effect. It is shown that, while the standard spin-spin correlation function is not sensitive to the spin Hall effect, spin-transverse voltage and transverse voltage-voltage correlation functions provide the missing sensitivity being linear and quadratic in the spin Hall coefficient, respectively. The correlation between transverse voltage and spin fluctuations appears as a result of spin-charge coupling fundamental for the spin Hall effect. We anticipate that the proposed method could find applications in the studies of spin-charge coupling in semiconductors.

cond-mat.mes-hall↗

arXiv2013

Memcapacitive neural networks

We show that memcapacitive (memory capacitive) systems can be used as synapses in artificial neural networks. As an example of our approach, we discuss the architecture of an integrate-and-fire neural network based on memcapacitive synapses. Moreover, we demonstrate that the spike-timing-dependent plasticity can be simply realized with some of these devices. Memcapacitive synapses are a low-energy alternative to memristive synapses for neuromorphic computation.

cond-mat.dis-nn↗