Quasilinear dirichlet problems in RN with critical growth

In this study, a given quasilinear problem is solved using variational methods. In particular, the existence of nontrivial solutions for GP is examined using minimax methods. The main theorem on the existence of a nontrivial solution for GP is detailed.

Estabilidade de sistemas condensados com interação atrativa ou repulsiva

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Singularly perturbed biharmonic problems with superlinear nonlinearities

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multiplicity of solutions for a biharmonic equation with subcritical or critical growth

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Positive Solution for a Class of Degenerate Quasilinear Elliptic Equations in R-N

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Um estudo sobre a equação de Schrödinger biharmônica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Radial sign-changing solutions to biharmonic nonlinear Schrodinger equations

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

Existence and multiplicity of solutions for a prescribed mean-curvature problem with critical growth

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Existência e concentração de soluções para uma equação de schrödinger estacionária

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

DIRAC CONFINEMENT BY A VARIATIONAL APPROACH

An analytical approximate method for the Dirac equation with confining power law scalar plus vector potentials, applicable to the problem of the relativistic quark confinement, is presented. The method consists in an improved version of a saddle-point variational approach and it is applied to the fundamental state of massless single quarks for some especial cases of physical interest. Our treatment emphasizes aspects such as the quantum-mechanical relativistic Virial theorem, the saddle-point character of the critical point of the expectation value of the total energy, as well as the Klein paradox and the behaviour of the saddle-point variational energies and wave functions.

Variational studies and replica symmetry breaking in the generalization problem of the binary perceptron

We analyze the average performance of a general class of learning algorithms for the nondeterministic polynomial time complete problem of rule extraction by a binary perceptron. The examples are generated by a rule implemented by a teacher network of similar architecture. A variational approach is used in trying to identify the potential energy that leads to the largest generalization in the thermodynamic limit. We restrict our search to algorithms that always satisfy the binary constraints. A replica symmetric ansatz leads to a learning algorithm which presents a phase transition in violation of an information theoretical bound. Stability analysis shows that this is due to a failure of the replica symmetric ansatz and the first step of replica symmetry breaking (RSB) is studied. The variational method does not determine a unique potential but it allows construction of a class with a unique minimum within each first order valley. Members of this class improve on the performance of Gibbs algorithm but fail to reach the Bayesian limit in the low generalization phase. They even fail to reach the performance of the best binary, an optimal clipping of the barycenter of version space. We find a trade-off between a good low performance and early onset of perfect generalization. Although the RSB may be locally stable we discuss the possibility that it fails to be the correct saddle point globally. ©2000 The American Physical Society.

Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets

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