Random Initial Distribution Research Articles

A numerical analysis of progressive and abrupt reset in conductive bridging RRAM

The authors investigate the conduction filament (CF) properties of a Cu---$$\textit{HfO}_{2}$$HfO2 based conductive bridging resistive memory device by implementing a numerical simulation of the low and high resistive states, starting from a random initial distribution of oxygen vacancies (OV) defects states in the resistive switching layer (RSL) to a formed CF and ending in a ruptured state. A calculation approach which accounts for both the statistical nature of the system and the synergetic effect of OV and Cu species on the overall conductance is presented. By defining a disorder parameter, the correlation between the OV initial distribution and the CF reset behavior is analyzed. A dependence of the reset transition, being either abrupt or progressive, on the physical shape of the CF which in turn is affected by this disorder is shown to exist based on the simulation results.

A comprehensive study of bipolar operation in resistive switching memory devices

The authors present a new numerical analysis method to investigate the conduction filament dynamics of a resistive switching nonvolatile metal---insulator---metal structured memory device. This comprehensive method, utilizing the Gibbs free energy criteria as a leading indicator and allowing simulation of all resistive memory operational phases (forming, set and reset), is presented for the first time. The formation and rupture of an oxygen vacancies based conduction filament are simulated to demonstrate a cycle of operation in a hafnium oxide based resistive forming layer. Starting from a random initial distribution of defect states, on to a formed conduction filament and ending in a ruptured state. Detailed plots of the physical parameters within the resistive layer are provided to gain deeper understanding of the conduction filament kinetics and introduce the concept of "hot spots", referring to random localized initial agglomeration of oxygen vacancies in which temperature surges is favored and contribute to initiate the conductive filament formation. By basing the method on well known thermodynamic properties and the Metropolis algorithm, simulation reliability and efficiency are obtained. The presented results confirm previously published data demonstrating the switching characteristics of hafnium based resistive random access memory.

Theoretical study of the dynamics of atomic hydrogen adsorbed on graphene multilayers

We present a theoretical study of the dynamics of H atoms adsorbed on graphene bilayers with Bernal stacking. First, through extensive density functional theory calculations, including van der Waals interactions, we obtain the activation barriers involved in the desorption and migration processes of a single H atom. These barriers, along with attempt rates and the energetics of H pairs, are used as input parameters in kinetic Monte Carlo simulations to study the time evolution of an initial random distribution of adsorbed H atoms. The simulations reveal that, at room temperature, H atoms occupy only one sublattice before they completely desorb or form clusters. This sublattice selectivity in the distribution of H atoms may last for sufficiently long periods of time upon lowering the temperature down to 0 C. The final fate of the H atoms, namely, desorption or cluster formation, depends on the actual relative values of the activation barriers which can be tuned by doping. In some cases a sublattice selectivity can be obtained for periods of time experimentally relevant even at room temperature. This result shows the possibility for observation and applications of the ferromagnetic state associated with such distribution.

Stochastic simulation of fluctuation-induced reaction-diffusion kinetics governed by Smoluchowski equations

Abstract A stochastic algorithm for simulation of fluctuation-induced reaction-diffusion kinetics is presented and further developed following our previous study [J. Math. Chem. (2015), DOI 10.1007/s10910-014-0446-6] where this method was used to describe the annihilation of spatially separate electrons and holes in a disordered semiconductor. This model is based on the spatially inhomogeneous, nonlinear Smoluchowski equations with random initial distribution density. Here we focus on the spatial distribution of the reactants, and study the segregation effect which we have found under certain reaction conditions. In addition, to extend simulations on large samples we implemented the method in the cellular-automata framework interpreted as a stochastic interacting particles system in discrete but randomly progressed time instances. We have suggested a first passage time technique to characterize the clustering of electrons and holes, which seems to be quite convenient and informative instrument also in more general processes when there is a need to analyze the segregation phenomena.

Effects of random initial conditions on the dynamical scaling behaviors of a fixed-energy Manna sandpile model in one dimension

For a fixed-energy (FE) Manna sandpile model in one dimension, we investigate the effects of random initial conditions on the dynamical scaling behavior of an order parameter. In the FE Manna model, the density ρ of total particles is conserved, and an absorbing phase transition occurs at ρ(c) as ρ varies. In this work, we show that, for a given ρ, random initial distributions of particles lead to the domain structure in which domains with particle densities higher and lower than ρ(c) alternate with each other. In the domain structure, the dominant length scale is the average domain length, which increases via the coalescence of adjacent domains. At ρ(c), the domain structure slows down the decay of an order parameter and also causes anomalous finite-size effects, i.e., power-law decay followed by an exponential one before the quasisteady state. As a result, the interplay of particle conservation and random initial conditions causes the domain structure, which is the origin of the anomalous dynamical scaling behaviors for random initial conditions.

Stochastic model for the fluctuation-limited reaction–diffusion kinetics in inhomogeneous media based on the nonlinear Smoluchowski equations

To describe the annihilation of spatially separate electrons and holes in a disordered semiconductor, we suggest the use of a model based on the spatially inhomogeneous, nonlinear Smoluchowski equations with random initial distribution density. Furthermore, we present a Monte Carlo algorithm for solving this equation. Our approach provides a general method for the computation of the electron-hole kinetics in inhomogeneous media, taking into account both their radiative and nonradiative recombination by tunneling as well as their diffusion. To validate the simulation algorithm, we compare our model with a more general approach based on a statistical description and the Kirkwood closure of the Bogoliubov–Born–Green–Kirkwood–Yvon hierarchy equations. A comparison with recent experimental results is also discussed.

A Brownian Agent Model for Analyzing Changes in a Nation's Product Space Structure

This paper proposes a Brownian agent model for simulating and analyzing changes in a nation's product space structure. A measurement of proximity has been employed to quantify a relationship between two products and proved to be useful in product space analysis. This study employs such proximity measurement, and estimates a continued structure transformation of a nation's product space through feedback between agent movements and network evolutions. Labor resources of an enterprise or a firm are regarded as Brownian agents; they move through different product spaces for higher economic rewards. The simulation results show that trade areas were self-organized through Brownian agent migration and cooperative production with a random initial distribution. Furthermore, we have verified the applicability and efficiency of the model in analyzing changes in Chinese product space structure with empirical data. Main contributions of this paper are: 1) it provides a bottom-up model for analyzing changes of a nation's product space structure; and 2) it also provides both qualitative and quantitative analysis methods for a nation's product space structure.

Classifying Users of a Topic Recommendation System with a Restricted Boltzmann Machine with Nearest Neighbor Interactions

In this work, we discover groups of similar users of a topic recommendation system. The data sets used are from Tipster Newsgroups, which are used in the annual TREC (Text Retrieval Conference) competition. The users are simulated, represented by tag/rating pairs. The documents in the Tipster data sets are clustered with a topic clustering algorithm that is a subset of the topic recommendation system being proposed in this paper. The users query the clusters derived from the topic clustering algorithm with tags, then rate the degree of relevance the content returned by the system has to their tag. It is shown in this work that, starting from a random sampling of the clusters by the users, and a random initial distribution of ratings per user, that a topic recommendation engine powered by a Boltzmann machine with nearest neighbor interactions results in two distinct clusters of users: those that converge quickly to a particular single topic, and those who explore a few different topics in a way that is periodic in time. This allows new users entering the system to be clustered and hence given a more relevant experience earlier in the process.

Locally Inertial Approximations of Balance Laws Arising in (1+1)-Dimensional General Relativity

An elementary model of (1+1)-dimensional general relativity, known as “${\cal R}={\cal T}$” and mainly developed by Mann and coworkers in the early 1990s, is set up in various contexts. Its formulation, mostly in isothermal coordinates, is derived and a relativistic Euler system of self-gravitating gas coupled to a Liouville equation for the metric's conformal factor is deduced. First, external field approximations are carried out: both a Klein--Gordon equation is studied along with its corresponding density, and a Dirac one inside a hydrostatic gravitational field induced by a static, piecewise constant mass repartition. Finally, the coupled Euler--Liouville system is simulated, by means of a locally inertial Godunov scheme: the gravitational collapse of a static random initial distribution of density is displayed. Well-balanced discretizations rely on the treatment of source terms at each interface of the computational grid, hence the metric remains flat in every computational cell.

An investigation of the efficient implementation of cellular automata on multi-core CPU and GPU hardware

Cellular automata (CA) have proven to be excellent tools for the simulation of a wide variety of phenomena in the natural world. They are ideal candidates for acceleration with modern general purpose-graphical processing units (GPU/GPGPU) hardware that consists of large numbers of small, tightly-coupled processors. In this study the potential for speeding up CA execution using multi-core CPUs and GPUs is investigated and the scalability of doing so with respect to standard CA parameters such as lattice and neighbourhood sizes, number of states and generations is determined. Additionally the impact of ‘Activity’ (the number of ‘alive’ cells) within a given CA simulation is investigated in terms of both varying the random initial distribution levels of ‘alive’ cells, and via the use of novel state transition rules; where a change in the dynamics of these rules (i.e. the number of states) allows for the investigation of the variable complexity within.

Failure and overall stability analysis on high arch dam based on DFPA code

A code of practice for three dimensional cracking and a failure process analysis of high arch dams, based on the finite element method, dam failure process analysis (DFPA) has been developed. In this code, by changing mesh density, consideration of heterogeneity when calculating the elements is achieved. Random strength and elastic modulus are assigned to the elements in accordance with a Weibull distribution. A stress analysis is carried out based on consideration of the deformation of an elastic material containing an initial random distribution of microcracks, which simulates the progressive failure of solids. The dam cracking and failure process associated seismicity accumulation can be analyzed using acoustic emissions. The proposed method was applied in investigating the failure mechanism, and overall stability of the Xiluodu high arch dam. The numerical mesh model was fine, and the total number of hexahedral elements was 300million. The DFPA analysis results, when compared with those derived by the Tfine code, and the 3D geomechanical model test show that the DFPA code is effective in fully simulating the failure processes of the dam and foundation. The analysis results were used to successfully guide the design of the Xiluodu high arch dam. The proposed DFPA method may also be of value to the reinforcement design and construction of high arch dams, associated with similar hydropower projects worldwide which are also located in complicated rock foundation areas.

Molecular dynamics simulation of the initial stages of He bubbles formation in silicon

The initial stages of the formation of bubbles due to helium implantation in silicon remain largely unknown, for they occur at time and space scales hardly accessible to experiments. To improve the current knowledge, we have developed an interatomic potential to describe the He : Si system, which can model helium for the pressure conditions expected in bubbles, and reproduce the behaviour of a single helium atom in silicon. Then molecular dynamics calculations were performed. Starting from an initial random distribution of helium interstitials and silicon vacancies, simulations revealed a two-step formation of small HenVm clusters. First, available vacancies quickly formed vacancy clusters Vm, due to their high mobility. In a second step, all clusters included a slowly increasing number of helium atoms, which were captured by diffusion or by cluster migration. Migration coalescence coarsening mechanisms were also identified during the simulation.

Energy Optimization in Mobile Wireless Sensor Networks with Mobile Targets Achieving Efficient Coverage for Critical Applications

The Mobile Wireless Sensor Networks (MWSN), classified within MANETS, have multiple applications for critical situations management such as target monitoring and tracking in conflict zones, supporting urban security, critical infrastructure monitoring, remote locations exploration (i.e. aerospace exploration), and patients monitoring and care in health facilities, among others. All of these applications have requirements of certain intelligence in the network that can be used for network’s self-configuration in order to find targets, guarantee connectivity and information availability until its reception. This paper proposes a MWSN architecture with an initial random distribution in a specific work area, and a centralized management to perform autonomous decision making about the movement and connectivity of the sensors. The work area presents mobile targets with interesting events which must be covered by the mobile sensors, and thus, send the collected information through the network to any base station available. Our work shows a dynamic mathematical model used to maximize targets’ coverage and send its sensed information to the base stations available, while minimizing system’s power consumption and maximizing operation time. The heuristic algorithm we used to construct and find a feasible solution is also shown.

Merkel cells and the individuality of friction ridge skin

There is no definite theory yet for the mechanism by which the pattern of epidermal ridges on fingers, palms and soles forming friction ridge skin (FRS) patterns is created. For a long time growth forces in the embryonal epidermis have been believed to be involved in FRS formation. More recent evidence suggests that Merkel cells play an important part in this process as well. Here we suggest a model for the formation of FRS patterns that links Merkel cells to the epidermal stress distribution. The Merkel cells are modeled as agents in an agent based model that move anisotropically where the anisotropy is created by the epidermal stress tensor. As a result ridge patterns are created with pattern defects as they occur in real FRS patterns. As a consequence we suggest why the topology of FRS patterns is indeed unique as the arrangement of pattern defects is sensitive to the initial configuration of Merkel cells.

Fiber interaction with a forming fabric

During sheet forming, the structure of the forming fabric leaves wire marks on the pulp mat. Paper nonuniformity caused by the wire mark can lead to ink nonuniformity in printing. We investigated wire mark numerically through simulations of the interaction of individual fibers with a forming fabric. In the simulations, the flow field through the forming fabric was taken to be that of single-phase water flow without disturbance of fibers. A particle level simulation method was applied to simulate the motion of fibers in the flow through a single layer sine-wave fabric. A hundred fibers of random initial distribution were placed into the flow above the fabric. Those fibers were advected onto the fabric, forming a fiber mat. The surface roughness of the resulting fiber mat was then calculated. The results show that during the initial formation, topographic wire mark is caused partially by fiber bending and partially by the geometry of the fabric. For the specific fibers and sinusoidal forming fabric considered, more than 50% of topographic wire mark is the result of geometry, with the remainder attributed to fiber bending. Fabrics with different geometries (e.g., different filament pitches or a nonsinusoidal geometry) will have different relative influences from geometry and fiber bending.

Single-file diffusion in a box: Effect of the initial configuration

This paper studies the single-file diffusion process on a linear chain of identical pointlike particles with multiple-site occupation confined in a one-dimensional box. The particles are noninteracting, except that double occupancy is forbidden. When particles are confined in a finite box, the final stage is saturation. By means of combinatorial analysis, an exact numerical evaluation of the saturation values for both the mean-square displacement (MSD) of a tracer particle and the center of mass of the system are obtained. Different initial distributions of particles are introduced. The time dependence of the MSD is obtained by means of Monte Carlo simulations. The values of the MSD for the tracer particles as well as the center of mass of the system depend on the size of the particle, the size of the box, and the initial distribution. Moreover, the transient regime depends on the initial distribution. In fact, the crossover from normal to subdiffusive regime is observed for random and alternate initial distributions, while superdiffusive diffusion appears for any stacked initial distributions. In all cases, it is shown that the collisions between particles do not determine the time exponent of the MSD. A simple expression for the transient regime is also obtained for the especial case of random initial distribution.

Persistent fluctuations in synchronization rate in globally coupled oscillators with periodic external forcing

A system of phase oscillators with repulsive global coupling and periodic external forcing undergoing asynchronous rotation is considered. The synchronization rate of the system can exhibit persistent fluctuations depending on parameters and initial phase distributions, and the amplitude of the fluctuations scales with the system size for uniformly random initial phase distributions. Using the Watanabe-Strogatz transformation that reduces the original system to low-dimensional macroscopic equations, we show that the fluctuations are collective dynamics of the system corresponding to low-dimensional trajectories of the reduced equations. It is argued that the amplitude of the fluctuations is determined by the inhomogeneity of the initial phase distribution, resulting in system-size scaling for the random case.

Reorientation of Cellulose Nanowhiskers in Agarose Hydrogels under Tensile Loading

Agarose hydrogels filled with cellulose nanowhiskers were strained in uniaxial stretching under different humidity conditions. The orientation of the cellulose whiskers was examined before and after testing with an X-ray laboratory source and monitored in situ during loading by synchrotron X-ray diffraction. The aim of this approach was to determine the process parameters for reorienting the cellulose nanowhiskers toward a preferential direction. Results show that a controlled drying of the hydrogel is essential to establish interactions between the matrix and the cellulose nanowhiskers which allow for a stress transfer during stretching and thereby promote their alignment. Rewetting of the sample after reorientation of the cellulose nanowhiskers circumvents a critical increase of stress. This improves the extensibility of the hydrogel and is accompanied by a further moderate alignment of the cellulose nanowhiskers. Following this protocol, cellulose nanowhiskers with an initial random distribution can be reoriented toward a preferential direction, creating anisotropic nanocomposites.

Pattern Formation Kinetics for Charged Molecules on Surfaces: Microscopic Correlation Function Analysis

The kinetics of pattern formation and phase separation in a system of two types of oppositely charged molecules with competing short- and long-range interactions on surfaces/interfaces is studied combining three methods: a microscopic formalism of the joint correlation functions, reverse Monte Carlo, and nonequilibrium charge-screening factors. The molecular ordering occurs on the background of the Ostwald ripening and thus is strongly nonequilibrium. We have demonstrated how initial random distribution of molecules is changed for loose similar-molecule aggregates, with further reorganization into dense macroscopic domains of oppositely charged molecules. Pattern formation process is characterized by the correlation length which monotonically increases in time.

Constrained Genetic Disentangling of Close Binary Spectra

AbstractThe spectral disentangling technique makes possible separation of individual component spectra in binary or multiple systems, and determination of the orbital elements in a self-consistent way. Since its introduction, a number of variants of their basic idea have been implemented. We present yet another ‘direct’ approach using optimization by genetic algorithm. Starting with an initial random flux distribution representing individual spectra, genetic optimization returns both individual component spectra and an optimal set of orbital parameters only constrained by time-series of the observed composite spectra of the binary system. Benchmark tests on V453 Cyg, which is an eclipsing binary with total eclipse, as well as tests on the artificial time-series spectra, have proven that ‘constrained genetic disentangling’ is performing correctly and efficiently, albeit with high demand on CPU time. Since genetic optimization can be easily parallelized, we expect our second release to run on cluster in a less time-consuming way.