Tests and Models of Non-compositional Concepts

The question of under what conditions conceptual representation is compositional remains debatable within cognitive science. This paper proposes a well developed mathematical apparatus for a probabilistic representation of concepts, drawing upon methods developed in quantum theory to propose a formal test that can determine whether a specific conceptual combination is compositional, or not. This test examines a joint probability distribution modeling the combination, asking whether or not it is factorizable. Empirical studies indicate that some combinations should be considered non-compositionally.

On S-matrix factorization of the Landau-Lifshitz model

We consider the three-particle scattering S-matrix for the Landau-Lifshitz model by directly computing the set of the Feynman diagrams up to the second order. We show, following the analogous computations for the non-linear Schrdinger model [1, 2], that the three-particle S-matrix is factorizable in the first non-trivial order.

Uma caracterização de grafos imersíveis

Este trabalho é motivado pelo resultado de Berge, que é uma generalização do teorema de Tutte o qual expressamos na forma: Dado o grafo G de ordem |V(G)| eni(G) o número de arestas em um emparelhamento máximo, existe um conjunto X de vértices de G tal que |V(G)|+|X| - ômega(G\X) - 2n(G)=0, onde ômega(G\X) é o número de componentes de ordem ímpar de G\X. Tal expressão chamamos a equação de Tutte-Berge associada de G, e escrevemos simplesmente T(G; X)=0. Os grafos podem ser classificados a partir das soluções da equação de Tutte-Berge. Um grafo G é chamado imersível se, e somente se, T(G; X)=0 possui pelo menos um conjunto solução não vazio de vértices, e G é denominado não imersível se, e somente se, o conjunto vazio é a única solução de T(G; X)=0. O resultado principal deste artigo é a caracterização de grafos imersíveis pelos conjuntos antifatores completos, além disso, provamos que os grafos fatoráveis estão contidos na classe dos imersíveis.

A SEMICLASSICAL DESCRIPTION OF NONLOCAL EFFECTS ON BARRIER TRANSMISSION

A quantum treatment for nonlocal factorizable potentials is presented in which the Weyl-Wiper quantum phase space description plays an essential role. The nonlocality is treated in an approximated form and allows for a Feynman propagator that can be handled in standard way. The semi-classical limit of the propagator is obtained which permits the calculation of the transmission factor in quantum tunnelling processes. An application in nuclear physics is also discussed.

NONLOCAL EFFECTS IN THE NUCLEUS-NUCLEUS FUSION CROSS-SECTION

Effects of the nonlocality of factorizable potentials are taken into account in the calculation of nucleus-nucleus fusion cross section through an effective mass approach. This cross section makes use of the tunneling factor calculated for the nonlocal barrier, without the explicit introduction of any result coming from coupled channel calculation, besides the approximations of Hill-Wheeler and Wong. Its new expression embodies the nonlocal effects in a factor which redefines the local potential barrier curvature. Applications to different systems, namely O-16 + Co-59, O-16,O-18 + Ni-58,Ni-60,Ni-64, and O-16,O-18 + Cu-63,Cu-65 are presented, where the nonlocal range is treated as a free parameter.

The structure of non-abelian kinks

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

Advanced mean field methods:theory and practice

A major problem in modern probabilistic modeling is the huge computational complexity involved in typical calculations with multivariate probability distributions when the number of random variables is large. Because exact computations are infeasible in such cases and Monte Carlo sampling techniques may reach their limits, there is a need for methods that allow for efficient approximate computations. One of the simplest approximations is based on the mean field method, which has a long history in statistical physics. The method is widely used, particularly in the growing field of graphical models. Researchers from disciplines such as statistical physics, computer science, and mathematical statistics are studying ways to improve this and related methods and are exploring novel application areas. Leading approaches include the variational approach, which goes beyond factorizable distributions to achieve systematic improvements; the TAP (Thouless-Anderson-Palmer) approach, which incorporates correlations by including effective reaction terms in the mean field theory; and the more general methods of graphical models. Bringing together ideas and techniques from these diverse disciplines, this book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling.