Mean-field description of a dynamical collapse of a fermionic condensate in a trapped boson-fermion mixture

We suggest a time-dependent dynamical mean-field-hydrodynamic model for the collapse of a trapped boson-fermion condensate and perform numerical simulation based on it to understand some aspects of the experiment by Modugno et al. [Science 297, 2240 (2002)] on the collapse of the fermionic condensate in the K-40-Rb-87 mixture. We show that the mean-field model explains the formation of a stationary boson-fermion condensate at zero temperature with relative sizes compatible with experiment. This model is also found to yield a faithful representation of the collapse dynamics in qualitative agreement with experiment. In particular we consider the collapse of the fermionic condensate associated with (a) an increase of the number of bosonic atoms as in the experiment and (b) an increase of the attractive boson-fermion interaction using a Feshbach resonance. Suggestion for experiments of fermionic collapse using a Feshbach resonance is made.

Chiral symmetry breaking in QCD-like gauge theories with a confining propagator and dynamical gauge boson mass generation

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Dynamical chiral symmetry breaking: the fermionic gap equation with dynamical gluon mass and confinement

Pós-graduação em Física - IFT

Kallen-Lehmann representation of noncommutative quantum electrodynamics

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

Nonlinear dynamical analysis of an aeroelastic system with multi-segmented moment in the pitch degree-of-freedom

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

Plant or fungal sequences? An alternative optimized PCR protocol to avoid ITS (nrDNA) misamplification

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

Optimized architecture for Tyrosinase-containing Langmuir-Blodgett films to detect pyrogallol

The control of molecular architectures has been a key factor for the use of Langmuir-Blodgett (LB) films in biosensors, especially because biomolecules can be immobilized with preserved activity. In this paper we investigated the incorporation of tyrosinase (Tyr) in mixed Langmuir films of arachidic acid (AA) and a lutetium bisphthalocyanine (LuPc2), which is confirmed by a large expansion in the surface pressure isotherm. These mixed films of AA-LuPc2 + Tyr could be transferred onto ITO and Pt electrodes as indicated by FTIR and electrochemical measurements, and there was no need for crosslinking of the enzyme molecules to preserve their activity. Significantly, the activity of the immobilised Tyr was considerably higher than in previous work in the literature, which allowed Tyr-containing LB films to be used as highly sensitive voltammetric sensors to detect pyrogallol. Linear responses have been found up to 400 mu M, with a detection limit of 4.87 x 10(-2) mu M (n = 4) and a sensitivity of 1.54 mu A mu M-1 cm(-2). In addition, the Hill coefficient (h = 1.27) indicates cooperation with LuPc2 that also acts as a catalyst. The enhanced performance of the LB-based biosensor resulted therefore from a preserved activity of Tyr combined with the catalytic activity of LuPc2, in a strategy that can be extended to other enzymes and analytes upon varying the LB film architecture.

Dynamical Elastic Moduli of the Ti-13Nb-13Zr biomaterial alloy by mechanical spectroscopy

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

Optimized synthesis of the melatonin metabolite N(1)-acetyl-N(2)-formyl-5-methoxykynuramine (AFMK)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Using neural networks for estimation of aquifer dynamical behavior

The systems of water distribution from groundwater wells can be monitored using the changes observed on its dynamical behavior. In this paper, artificial neural networks are used to estimate the depth of the dynamical water level of groundwater wells in relation to water flow, operation time and rest time. Simulation results are presented to demonstrate the validity of the proposed approach. These results have shown that artificial neural networks can be effectively used for the identification and estimation of parameters related to systems of water distribution.

An efficient Hopfield network to solve economic dispatch problems with transmission system representation

Economic dispatch (ED) problems have recently been solved by artificial neural network approaches. Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. The ability of neural networks to realize some complex non-linear function makes them attractive for system optimization. All ED models solved by neural approaches described in the literature fail to represent the transmission system. Therefore, such procedures may calculate dispatch policies, which do not take into account important active power constraints. Another drawback pointed out in the literature is that some of the neural approaches fail to converge efficiently toward feasible equilibrium points. A modified Hopfield approach designed to solve ED problems with transmission system representation is presented in this paper. The transmission system is represented through linear load flow equations and constraints on active power flows. The internal parameters of such modified Hopfield networks are computed using the valid-subspace technique. These parameters guarantee the network convergence to feasible equilibrium points, which represent the solution for the ED problem. Simulation results and a sensitivity analysis involving IEEE 14-bus test system are presented to illustrate efficiency of the proposed approach. (C) 2004 Elsevier Ltd. All rights reserved.

Framework for analysis and representation of external systems for online reactive-optimisation studies

The paper proposes a framework for the analysis and representation of external systems for online optimisation studies. The basis for this framework is the equivalent OPF (EOPF), an optimisation model obtained by partitioning of the OPF model. The EOPF is mathematically redefined in the paper to accommodate the concept of a buffer zone. The resulting model is more useful for online optimisation, since external information obtained through intercontrol-centre exchange contracts can be used to improve internal control calculation. Numerical results obtained with original studies involving the boundary-matching procedure have provided a conceptual basis for the definition of a buffer zone for optimisation studies with the EOPF. In the proposed framework, the accuracy of the external representation in optimisation studies is evaluated by comparing the controls obtained by an EOPF procedure with those obtained by the reference-optimisation procedure defined in this paper. The framework is then used to evaluate the accuracy of equivalent optimisation studies involving the IEEE 118-bus test system and the Brazilian South Southeast 810-bus system. The results show that the incorporation of a buffer zone improves the external system representation for all optimisation studies performed.

Application of neural networks to identify features of dynamical grounding systems

The accurate identification of features of dynamical grounding systems are extremely important to define the operational safety and proper functioning of electric power systems. Several experimental tests and theoretical investigations have been carried out to obtain characteristics and parameters associated with the technique of grounding. The grounding system involves a lot of non-linear parameters. This paper describes a novel approach for mapping characteristics of dynamical grounding systems using artificial neural networks. The network acts as identifier of structural features of the grounding processes. So that output parameters can be estimated and generalized from an input parameter set. The results obtained by the network are compared with other approaches also used to model grounding systems.

Notes on Newton-Euler formulation of robotic manipulators

The equations corresponding to Newton-Euler iterative method for the determination of forces and moments acting on the rigid links of a robotic manipulator are given a new treatment using composed vectors for the representation of both kinematical and dynamical quantities. It is shown that Lagrange equations for the motion of a holonomic system are easily found from the composed vectors defined in this note. Application to a simple model of an industrial robot shows that the method developed in these notes is efficient in solving the dynamics of a robotic manipulator. An example is developed, where it is seen that with the application of appropriate control moments applied to each arm of the robot, starting from a given initial position, it is possible to reach equilibrium in a final pre-assigned position.

The stable archipelago in the region of the Pallas and Hansa dynamical families

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