Propagação de danos no modelo de ising em redes de bravais e em fractais

In this work we have studied, by Monte Carlo computer simulation, several properties that characterize the damage spreading in the Ising model, defined in Bravais lattices (the square and the triangular lattices) and in the Sierpinski Gasket. First, we investigated the antiferromagnetic model in the triangular lattice with uniform magnetic field, by Glauber dynamics; The chaotic-frozen critical frontier that we obtained coincides , within error bars, with the paramegnetic-ferromagnetic frontier of the static transition. Using heat-bath dynamics, we have studied the ferromagnetic model in the Sierpinski Gasket: We have shown that there are two times that characterize the relaxation of the damage: One of them satisfy the generalized scaling theory proposed by Henley (critical exponent z~A/T for low temperatures). On the other hand, the other time does not obey any of the known scaling theories. Finally, we have used methods of time series analysis to study in Glauber dynamics, the damage in the ferromagnetic Ising model on a square lattice. We have obtained a Hurst exponent with value 0.5 in high temperatures and that grows to 1, close to the temperature TD, that separates the chaotic and the frozen phases

Crescimento de filmes nanométricos monocristalinos de Fe/MgO(100) por "SPUTTERING" DC

The research behind this master dissertation started with the installation of a DC sputtering system, from its first stage, the adaptation of a refrigerating system, passing by the introduction of a heating system for the chamber using a thermal belt, until the deposition of a series of Fe/MgO(100) single crystal nanometric film samples. The deposition rates of some materials such as Fe, Py and Cu were investigated through an Atomic Force Microscope (AFM). For the single crystal samples, five of them have the same growth parameters and a thickness of 250Å, except for the temperature, which varies from fifty degrees from one to another, from 100ºC to 300ºC. Three other samples also have the same deposition parameters and a temperature of 300ºC, but with thickness of 62,5Å, 150Å, and 250Å. Magneto-optical Kerr Effect (MOKE) of the magnetic curves measurements and Ferromagnetic Resonance (FMR) were made to in order to study the influence of the temperature and thickness on the sample s magnetic properties. In the present dissertation we discuss such techniques, and the experimental results are interpreted using phenomenological models, by simulation, and discussed from a physical point of view, taking into account the system s free magnetic energy terms. The results show the growth of the cubic anisotropy field (Hac) as the sample s deposition temperature increases, presenting an asymptotic behavior, similar to the characteristic charging curve of a capacitor in a RC circuit. A similar behavior was also observed for the Hac due to the increase in the samples thicknesses. The 250˚A sample, growth at 300°C, presented a Hac field close to the Fe bulk value

Effect of target bias on magnetic field enhanced plasma immersion ion implantation

Recent studies have demonstrated that sheath dynamics in plasma immersion ion implantation (PIII) is significantly affected by an external magnetic field, especially in the case when the magnetic field is parallel to the workpiece surface or intersects it at small angles. In this work we report the results from two-dimensional, particle-in-cell (PIC) computer simulations of magnetic field enhanced plasma immersion implantation system at different bias voltages. The simulations begin with initial low-density nitrogen plasma, which extends with uniform density through a grounded cylindrical chamber. Negative bias voltage is applied to a cylindrical target located on the axis of the vacuum chamber. An axial magnetic field is created by a solenoid installed inside the target holder. A set of simulations at a fixed magnetic field of 0.0025 T at the target surface is performed. Secondary electron emission from the target subjected to ion bombardment is also included. It is found that the plasma density around the cylindrical target increases because of intense background gas ionization by the electrons drifting in the crossed E x B fields. Suppression of the sheath expansion and increase of the implantation current density in front of the high-density plasma region are observed. The effect of target bias on the sheath dynamics and implantation current of the magnetic field enhanced PIII is discussed. (C) 2007 Elsevier B.V. All rights reserved.

Effect of electron magnetic trapping in a plasma immersion ion implantation system

In this work we describe a two-dimensional computer simulation of magnetic field enhanced plasma immersion implantation system. Negative bias voltage of 10.0 kV is applied to a cylindrical target located on the axis of a grounded vacuum chamber filled with uniform nitrogen plasma. A pair of external coils creates a static magnetic field with main vector component along the axial direction. Thus, a system of crossed ExB field is generated inside the vessel forcing plasma electrons to rotate in azimuthal direction. In addition, the axial variation of the magnetic field intensity produces magnetic mirror effect that enables axial particle confinement. It is found that high-density plasma regions are formed around the target due to intense background gas ionization by the trapped electrons. Effect of the magnetic field on the sheath dynamics and the implantation current density of the PIII system is investigated. By changing the magnetic field axial profile (varying coils separation) an enhancement of about 30% of the retained dose can be achieved. The results of the simulation show that the magnetic mirror configuration brings additional benefits to the PIII process, permitting more precise control of the implanted dose.

The Impact on Geographic Location Accuracy due to Different Satellite Orbit Ephemerides

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A planar flexible robotic manipulator

Presents the dynamic modelling of a flexible robotic manipulator with two flexible links and two revolute joints, which rotates in the horizontal plane. The dynamic equations are derived using the Newton-Euler formulation and the finite element method, based on elementary beam theory, which is used to discretize the displacements such that the small motion is represented in terms of nodal displacements. Computer simulation results are presented to illustrate this study. The dynamic model becomes necessary for use in future design and control applications.

New approach to ideal inductors stored energy nature

Nonlinear load compensation required the definition of new concepts of electric power. With basis on these new concepts the nature of the stored energy stored in ideal inductors is theoreticaly characterized in this work. Computer simulation and theory agree when applied to an isolated alternator.

Efeito do campo elétrico em nanocones formados por aln e BN: um estudo por primeiros princípios

The development of computers and algorithms capable of making increasingly accurate and rapid calculations as well as the theoretic foundation provided by quantum mechanics has turned computer simulation into a valuable research tool. The importance of such a tool is due to its success in describing the physical and chemical properties of materials. One way of modifying the electronic properties of a given material is by applying an electric field. These effects are interesting in nanocones because their stability and geometric structure make them promising candidates for electron emission devices. In our study we calculated the first principles based on the density functional theory as implemented in the SIESTA code. We investigated aluminum nitride (AlN), boron nitride (BN) and carbon (C), subjected to external parallel electric field, perpendicular to their main axis. We discuss stability in terms of formation energy, using the chemical potential approach. We also analyze the electronic properties of these nanocones and show that in some cases the perpendicular electric field provokes a greater gap reduction when compared to the parallel field

Simulações de Monte Carlo para os modelos Ising e Blume-Capel em redes complexa

We studied the Ising model ferromagnetic as spin-1/2 and the Blume-Capel model as spin-1, > 0 on small world network, using computer simulation through the Metropolis algorithm. We calculated macroscopic quantities of the system, such as internal energy, magnetization, specific heat, magnetic susceptibility and Binder cumulant. We found for the Ising model the same result obtained by Koreans H. Hong, Beom Jun Kim and M. Y. Choi [6] and critical behavior similar Blume-Capel model

Propriedades eletrônicas, estruturais e constantes elásticas do ZnO

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Jogo da Minoria: um modelo baseado em agentes aplicado ao mercado financeiro

Nos últimos anos houve uma contribuição significativa dos físicos para a construção de um tipo de modelo baseado em agentes que busca reproduzir, em simulação computacional, o comportamento do mercado financeiro. Esse modelo, chamado Jogo da Minoria consiste de um grupo de agentes que vão ao mercado comprar ou vender ativos. Eles tomam decisões com base em estratégias e, por meio delas, os agentes estabelecem um intrincado jogo de competição e coordenação pela distribuição da riqueza. O modelo tem demonstrado resultados bastante ricos e surpreendentes, tanto na dinâmica do sistema como na capacidade de reproduzir características estatísticas e comportamentais do mercado financeiro. Neste artigo, são apresentadas a estrutura e a dinâmica do Jogo da Minoria, bem como as contribuições recentes relacionadas ao Jogo da Minoria denominado de Grande Canônico, que é um modelo mais bem ajustado às características do mercado financeiro e reproduz as regularidades estatísticas do preço dos ativos chamadas fatos estilizados.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning with Concept Drift

Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.

Neural networks training using the constructivism paradigms

The Backpropagation Algorithm (BA) is the standard method for training multilayer Artificial Neural Networks (ANN), although it converges very slowly and can stop in a local minimum. We present a new method for neural network training using the BA inspired on constructivism, an alphabetization method proposed by Emilia Ferreiro based on Piaget philosophy. Simulation results show that the proposed configuration usually obtains a lower final mean square error, when compared with the standard BA and with the BA with momentum factor.

Another prefiltering algorithm for adaptive IIR filtering

An algorithm for adaptive IIR filtering that uses prefiltering structure in direct form is presented. This structure has an estimation error that is a linear function of the coefficients. This property greatly simplifies the derivation of gradient-based algorithms. Computer simulations show that the proposed structure improves convergence speed.

Electric power systems transient stability analysis by neural networks

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)