Revisiting lepton flavor violation in a supersymmetric type II seesaw mechanism

In view of the recent measurement of the reactor mixing angle theta(13) and updated limit on BRd(mu -> e gamma) by the MEG experiment, we reexamine the charged lepton flavor violations in a framework of the supersymmetric type II seesaw mechanism. The supersymmetric type II seesaw predicts a strong correlation between BR(mu -> e gamma) and BR(tau -> mu gamma) mainly in terms of the neutrino mixing angles. We show that such a correlation can be determined accurately after the measurement of theta(13). We compute different factors that can affect this correlation and show that the minimal supergravity-like scenarios, in which slepton masses are taken to be universal at the high scale, predict 3.5 <= BR(tau -> mu gamma)/= BR(mu -> e gamma) <= 30 for normal hierarchical neutrino masses. Any experimental indication of deviation from this prediction would rule out the minimal models of the supersymmetric type II seesaw. We show that the current MEG limit puts severe constraints on the light sparticle spectrum in the minimal supergravity model if the seesaw scale lies within 10(13)-10(15) GeV. It is shown that these constraints can be relaxed and a relatively light sparticle spectrum can be obtained in a class of models in which the soft mass of a triplet scalar is taken to be nonuniversal at the high scale.

Warped alternatives to Froggatt-Nielsen models

We consider the Randall-Sundrum (RS) setup to be a theory of flavor, as an alternative to Froggatt-Nielsen models instead of as a solution to the hierarchy problem. The RS framework is modified by taking the low-energy brane to be at the grand unified theory (GUT) scale. This also alleviates constraints from flavor physics. Fermion masses and mixing angles are fit at the GUT scale. The ranges of the bulk mass parameters are determined using a chi(2) fit taking into consideration the variation in O(1) parameters. In the hadronic sector, the heavy top quark requires large bulk mass parameters localizing the right-handed top quark close to the IR brane. Two cases of neutrino masses are considered: (a) Planck scale lepton number violation and (b) Dirac neutrino masses. Contrary to the case of weak scale RS models, both these cases give reasonable fits to the data, with the Planck scale lepton number violation fitting slightly better compared to the Dirac case. In the supersymmetric version, the fits are not significantly different except for the variation in tan beta. If the Higgs superfields and the supersymmetry breaking spurion are localized on the same brane, then the structure of the sfermion masses are determined by the profiles of the zero modes of the hypermultiplets in the bulk. Trilinear terms have the same structure as the Yukawa matrices. The resultant squark spectrum is around similar to 2-3 TeV required by the light Higgs mass to be around 125 GeV and to satisfy the flavor violating constraints.

Practical applications of the likelihood, time transcendence and metadata in virtual models of heritage elements

Contributed to: III Bienal de Restauración Monumental: "Sobre la des-restauración" (Sevilla, Spain, Nov 23-25, 2006)

Branes and supersymmetric quantum field theories

Since the discovery of D-branes as non-perturbative, dynamic objects in string theory, various configurations of branes in type IIA/B string theory and M-theory have been considered to study their low-energy dynamics described by supersymmetric quantum field theories.

One example of such a construction is based on the description of Seiberg-Witten curves of four-dimensional N = 2 supersymmetric gauge theories as branes in type IIA string theory and M-theory. This enables us to study the gauge theories in strongly-coupled regimes. Spectral networks are another tool for utilizing branes to study non-perturbative regimes of two- and four-dimensional supersymmetric theories. Using spectral networks of a Seiberg-Witten theory we can find its BPS spectrum, which is protected from quantum corrections by supersymmetry, and also the BPS spectrum of a related two-dimensional N = (2,2) theory whose (twisted) superpotential is determined by the Seiberg-Witten curve. When we don’t know the perturbative description of such a theory, its spectrum obtained via spectral networks is a useful piece of information. In this thesis we illustrate these ideas with examples of the use of Seiberg-Witten curves and spectral networks to understand various two- and four-dimensional supersymmetric theories.

First, we examine how the geometry of a Seiberg-Witten curve serves as a useful tool for identifying various limits of the parameters of the Seiberg-Witten theory, including Argyres-Seiberg duality and Argyres-Douglas fixed points. Next, we consider the low-energy limit of a two-dimensional N = (2, 2) supersymmetric theory from an M-theory brane configuration whose (twisted) superpotential is determined by the geometry of the branes. We show that, when the two-dimensional theory flows to its infra-red fixed point, particular cases realize Kazama-Suzuki coset models. We also study the BPS spectrum of an Argyres-Douglas type superconformal field theory on the Coulomb branch by using its spectral networks. We provide strong evidence of the equivalence of superconformal field theories from different string-theoretic constructions by comparing their BPS spectra.

Contributions to learning Bayesian network models from weakly supervised data: Application to Assisted Reproductive Technologies and Software Defect Classification

162 p.

Distance Metric Between 3D Models and 3D Images for Recognition and Classification

Similarity measurements between 3D objects and 2D images are useful for the tasks of object recognition and classification. We distinguish between two types of similarity metrics: metrics computed in image-space (image metrics) and metrics computed in transformation-space (transformation metrics). Existing methods typically use image and the nearest view of the object. Example for such a measure is the Euclidean distance between feature points in the image and corresponding points in the nearest view. (Computing this measure is equivalent to solving the exterior orientation calibration problem.) In this paper we introduce a different type of metrics: transformation metrics. These metrics penalize for the deformatoins applied to the object to produce the observed image. We present a transformation metric that optimally penalizes for "affine deformations" under weak-perspective. A closed-form solution, together with the nearest view according to this metric, are derived. The metric is shown to be equivalent to the Euclidean image metric, in the sense that they bound each other from both above and below. For Euclidean image metric we offier a sub-optimal closed-form solution and an iterative scheme to compute the exact solution.

Design of neuro-fuzzy models by evolutionary and gradient-based algorithms

All systems found in nature exhibit, with different degrees, a nonlinear behavior. To emulate this behavior, classical systems identification techniques use, typically, linear models, for mathematical simplicity. Models inspired by biological principles (artificial neural networks) and linguistically motivated (fuzzy systems), due to their universal approximation property, are becoming alternatives to classical mathematical models. In systems identification, the design of this type of models is an iterative process, requiring, among other steps, the need to identify the model structure, as well as the estimation of the model parameters. This thesis addresses the applicability of gradient-basis algorithms for the parameter estimation phase, and the use of evolutionary algorithms for model structure selection, for the design of neuro-fuzzy systems, i.e., models that offer the transparency property found in fuzzy systems, but use, for their design, algorithms introduced in the context of neural networks. A new methodology, based on the minimization of the integral of the error, and exploiting the parameter separability property typically found in neuro-fuzzy systems, is proposed for parameter estimation. A recent evolutionary technique (bacterial algorithms), based on the natural phenomenon of microbial evolution, is combined with genetic programming, and the resulting algorithm, bacterial programming, advocated for structure determination. Different versions of this evolutionary technique are combined with gradient-based algorithms, solving problems found in fuzzy and neuro-fuzzy design, namely incorporation of a-priori knowledge, gradient algorithms initialization and model complexity reduction.

Estudo e integração de business models e a sua aplicação em smart-ups e projetos portugueses

Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do Grau de Mestre em Gestão das Organizações, Ramo Gestão de Empresas Orientador: Professor Doutor Eduardo Manuel Lopes de Sá e Silva Co-orientador: Mestre Maria de Fátima Mendes Monteiro

Models humans i models educatius a la Il??lustraci?? mallorquina. 'Modelos humanos y modelos educativos en la Ilustraci??n mallorquina'

Resumen tomado de la propia publicaci??n. Volumen especial dedicado a filosof??a y ciencias de la educaci??n

Els canvis en els valors i models de família. 'Los cambios en los valores y modelos de familia'.

Este artículo se incluye en el monográfico 'Projecte Educatiu de Ciutat'

On duality of the noncommutative supersymmetric Maxwell-Chern-Simons theory

We study the possibility of establishing the dual equivalence between the noncommutative supersymmetric Maxwell-Chern-Simons theory and the noncommutative supersymmetric self-dual theory. It turns to be that whereas in the commutative case the Maxwell-Chern-Simons theory can be mapped into the sum of the self-dual theory and the Chern-Simons theory, in the noncommutative case such a mapping is possible only for the theory with modified Maxwell term. (c) 2008 Elsevier B.V. All rights reserved.

Affine processes, arbitrage-Free Term structures of legendre polynomials,and option pricing

Multivariate Affine term structure models have been increasingly used for pricing derivatives in fixed income markets. In these models, uncertainty of the term structure is driven by a state vector, while the short rate is an affine function of this vector. The model is characterized by a specific form for the stochastic differential equation (SDE) for the evolution of the state vector. This SDE presents restrictions on its drift term which rule out arbitrages in the market. In this paper we solve the following inverse problem: Suppose the term structure of interest rates is modeled by a linear combination of Legendre polynomials with random coefficients. Is there any SDE for these coefficients which rules out arbitrages? This problem is of particular empirical interest because the Legendre model is an example of factor model with clear interpretation for each factor, in which regards movements of the term structure. Moreover, the Affine structure of the Legendre model implies knowledge of its conditional characteristic function. From the econometric perspective, we propose arbitrage-free Legendre models to describe the evolution of the term structure. From the pricing perspective, we follow Duffie et al. (2000) in exploring Legendre conditional characteristic functions to obtain a computational tractable method to price fixed income derivatives. Closing the article, the empirical section presents precise evidence on the reward of implementing arbitrage-free parametric term structure models: The ability of obtaining a good approximation for the state vector by simply using cross sectional data.

N=2 sigma models for Ramond-Ramond backgrounds

Using the U(4) hybrid formalism, manifestly N = (2,2) worldsheet supersymmetric sigma models are constructed for the type-IIB superstring in Ramond-Ramond backgrounds. The Kahler potential in these N = 2 sigma models depends on four chiral and antichiral bosonic superfields and two chiral and antichiral fermionic superfields. When the Kahler potential is quadratic, the model is a free conformal field theory which describes a flat ten-dimensional target space with Ramond-Ramond flux and non-constant dilaton. For more general Kahler potentials, the model describes curved target spaces with Ramond-Ramond flux that are not plane-wave backgrounds. Ricci-flatness of the Kahler metric implies the on-shell conditions for the background up to the usual four-loop conformal anomaly.

Concerning the Landau pole in 3-3-1 models

Some 3 - 3 - 1 models predict the existence of a non-perturbative regime at the TeV scale. We study in these models and their supersymmetric extensions, the energy at which the non-perturbative limit and a Landau-like pole arise. An order of magnitude for the mass of the extra neutral vector boson, Z', present in these models is also obtained.

Supersymmetry flows, semi-symmetric space sine-Gordon models and the Pohlmeyer reduction

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)