149 resultados para Wave-function Approach


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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In the present work the scattering of a fermion in the modified Hulthen potential is considered with a general vector and scalar and we solved the Dirac equation in the one-dimensional space. The transmission and reflection coefficients are reported. The bound-state solution is also given. The study shows the asymptotic behavior of the wave function in bound-state and scattering states solutions.

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In the present work we use an asymptotic approach to obtain the long wave equations. The shallow water equation is put as a function of an external parameter that is a measure of both the spatial scales anisotropy and the fast to slow time ratio. The values given to the external parameters are consistent with those computed using typical values of the perturbations in tropical dynamics. Asymptotically, the model converge toward the long wave model. Thus, it is possible to go toward the long wave approximation through intermediate realizable states. With this approach, the resonant nonlinear wave interactions are studied. To simplify, the reduced dynamics of a single resonant triad is used for some selected equatorial trios. It was verified by both theoretical and numerical results that the nonlinear energy exchange period increases smoothly as we move toward the long wave approach. The magnitude of the energy exchanges is also modified, but in this case depends on the particular triad used and also on the initial energy partition among the triad components. Some implications of the results for the tropical dynamics are disccussed. In particular, we discuss the implications of the results for El Nĩo and the Madden-Julian in connection with other scales of time and spatial variability. © Published under licence by IOP Publishing Ltd.

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

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A thermodynamical analysis for the type IIB superstring in a pp-wave background is considered. The thermal Fock space is built and the temperature SUSY breaking appears naturally by analyzing the thermal vacuum. All the thermodynamical quantities are derived by evaluating matrix elements of operators in the thermal Fock space. This approach seems to be suitable to study thermal effects in the BMN correspondence context. (C) 2004 Elsevier B.V. All rights reserved.

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The first step toward the application of an effective non partial wave (PW) numerical approach to few-body atomic bound states has been taken. The two-body transition amplitude which appears in the kernel of three-dimensional Faddeev-Yakubovsky integral equations is calculated as function of two-body Jacobi momentum vectors, i.e. as a function of the magnitude of initial and final momentum vectors and the angle between them. For numerical calculation the realistic interatomic interactions HFDHE2, HFD-B, LM2M2 and TTY are used. The angular and momentum dependence of the fully off-shell transition amplitude is studied at negative energies. It has been numerically shown that, similar to the nuclear case, the transition amplitude exhibits a characteristic angular behavior in the vicinity of He-4 dimer pole.

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

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

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The Green function for a spin-1/2 charged particle in the presence of an external plane wave electromagnetic field is calculated by algebraic techniques in terms of the free-particle Green function.

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This paper presents a new algorithm for optimal power flow problem. The algorithm is based on Newton's method which it works with an Augmented Lagrangian function associated with the original problem. The function aggregates all the equality and inequality constraints and is solved using the modified-Newton method. The test results have shown the effectiveness of the approach using the IEEE 30 and 638 bus systems.

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This paper presents a new approach for damage detection in structural health monitoring systems exploiting the coherence function between the signals from PZT (Lead Zirconate Titanate) transducers bonded to a host structure. The physical configuration of this new approach is similar to the configuration used in Lamb wave based methods, but the analysis and operation are different. A PZT excited by a signal with a wide frequency range acts as an actuator and others PZTs are used as sensors to receive the signal. The coherences between the signals from the PZT sensors are obtained and the standard deviation for each coherence function is computed. It is demonstrated through experimental results that the standard deviation of the coherence between the signals from the PZTs in healthy and damaged conditions is a very sensitive metric index to detect damage. Tests were carried out on an aluminum plate and the results show that the proposed methodology could be an excellent approach for structural health monitoring (SHM) applications.

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Tooth replacement in the maxillary anterior region is especially difficult when the loss includes significant amounts of the residual ridge and the soft tissue. Several techniques are available, such as dental implants or fixed partial denture, and bone and gingival grafts or gingival prostheses, respectively. This article showed a clinical case of an elderly who was treated with a collarless metal-ceramic fixed partial denture and acrylic removable gingival prosthesis to recover the esthetics in the maxillary anterior region. The association of a metal-ceramic fixed denture and gingival prosthesis was an excellent alternative in cases when surgical procedures are contraindicated. © 2012 Japan Prosthodontic Society.

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Spiking neural networks - networks that encode information in the timing of spikes - are arising as a new approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Learning algorithms have been proposed to this model looking for mapping input pulses into output pulses. Recently, a new method was proposed to encode constant data into a temporal sequence of spikes, stimulating deeper studies in order to establish abilities and frontiers of this new approach. However, a well known problem of this kind of network is the high number of free parameters - more that 15 - to be properly configured or tuned in order to allow network convergence. This work presents for the first time a new learning function for this network training that allow the automatic configuration of one of the key network parameters: the synaptic weight decreasing factor.

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