Free expansion of fermionic dark solitons in a boson-fermion mixture

We use a time-dependent dynamical mean-field-hydrodynamic model to study the formation of fermionic dark solitons in a trapped degenerate Fermi gas mixed with a Bose-Einstein condensate in a harmonic as well as a periodic optical-lattice potential. The dark soliton with a 'notch' in the probability density with a zero at the minimum is simulated numerically as a nonlinear continuation of the first vibrational excitation of the linear mean-field-hydrodynamic equations, as suggested recently for pure bosons. We study the free expansion of these dark solitons as well as the consequent increase in the size of their central notch and discuss the possibility of experimental observation of the notch after free expansion.

Microscopic origin of non-Gaussian distributions of financial returns

In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.

Effects of varying curvature and width on the electronic states of GaAs quantum rings

Stationary states of an electron in thin GaAs elliptical quantum rings are calculated within the effective-mass approximation. The width of the ring varies smoothly along the centerline, which is an ellipse. The solutions of the Schrödinger equation with Dirichlet boundary conditions are approximated by a product of longitudinal and transversal wave functions. The ground-state probability density shows peaks: (i) where the curvature is larger in a constant-with ring, and (ii) in thicker parts of a circular ring. For rings of typical dimensions, it is shown that the effects of a varying width may be stronger than those of the varying curvature. Also, a width profile which compensates the main localization effects of the varying curvature is obtained.

The Poisson-exponential distribution: a Bayesian approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Reliability of timber bridges using nailed plywood box beams

The Nailed Box Beam structural efficiency is directly dependent of the flange-web joint behavior, which determines the partial composition of the section, as the displacement between elements reduces the effective rigidity of the section and changes the stress distribution and the total displacement of the section. This work discusses the use of Nailed Plywood Box Beams in small span timber bridges, focusing on the reliability of the beam element. It is presented the results of tests carried out in 21 full scale Nailed Plywood Box Beams. The analysis of maximum load tests results shows that it presents a normal distribution, permitting the characteristic values calculation as the normal distribution theory specifies. The reliability of those elements was analyzed focusing on a timber bridge design, to estimate the failure probability in function of the load level.

Segmentação de dados de perfilamento a laser em áreas urbanas utilizando uma abordagem Bayesiana

In this paper is presented a region-based methodology for Digital Elevation Model segmentation obtained from laser scanning data. The methodology is based on two sequential techniques, i.e., a recursive splitting technique using the quad tree structure followed by a region merging technique using the Markov Random Field model. The recursive splitting technique starts splitting the Digital Elevation Model into homogeneous regions. However, due to slight height differences in the Digital Elevation Model, region fragmentation can be relatively high. In order to minimize the fragmentation, a region merging technique based on the Markov Random Field model is applied to the previously segmented data. The resulting regions are firstly structured by using the so-called Region Adjacency Graph. Each node of the Region Adjacency Graph represents a region of the Digital Elevation Model segmented and two nodes have connectivity between them if corresponding regions share a common boundary. Next it is assumed that the random variable related to each node, follows the Markov Random Field model. This hypothesis allows the derivation of the posteriori probability distribution function whose solution is obtained by the Maximum a Posteriori estimation. Regions presenting high probability of similarity are merged. Experiments carried out with laser scanning data showed that the methodology allows to separate the objects in the Digital Elevation Model with a low amount of fragmentation.

False alarms in damage detection approaches

Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in structures in order to improve reliability and reduce life-cycle costs. The greatest challenge for designing a SHM system is knowing what changes to look for and how to classify them. Different approaches for SHM have been proposed for damage identification, each one with advantages and drawbacks. This paper presents a methodology for improvement in vibration signal analysis using statistics information involving the probability density. Generally, the presence of noises in input and output signals results in false alarms, then, it is important that the methodology can minimize this problem. In this paper, the proposed approach is experimentally tested in a flexible plate using a piezoelectric (PZT) actuator to provide the disturbance.

A história da origem da curva normal

Pós-graduação em Educação Matemática - IGCE

Identificação de parâmetros modais utilizando apenas as respostas da estrutura: identificação estocástica de subespaço e decomposição no domínio da frequência

Pós-graduação em Engenharia Mecânica - FEIS

Análise modal baseada apenas na resposta: decomposição no domínio da frequência

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

Equações volumétricas e produção de madeira em plantios mistos visando à restauração da floresta estacional semidecidual

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fluxo de potência em redes de distribuição de energia elétrica considerando incertezas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Planejamento da expansão de sistemas de transmissão considerando análise de confiabilidade e incertezas na demanda futura

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Potenciais periódicos: aplicação à espectroscopia do benzeno

Pós-graduação em Física - FEG

Kallen-Lehmann representation of noncommutative quantum electrodynamics

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