Fermion mass hierarchy and non-hierarchical mass ratios in SU(5) x U(1)_F

We consider a SU(5) x U(1)_F GUT-flavor model in which the number of effects that determine the charged fermions Yukawa matrices is much larger than the number of observables, resulting in a hierarchical fermion spectrum with no particular regularities. The GUT-flavor symmetry is broken by flavons in the adjoint of SU(5), realizing a variant of the Froggatt-Nielsen mechanism that gives rise to a large number of effective operators. By assuming a common mass for the heavy fields and universality of the fundamental Yukawa couplings, we reduce the number of free parameters to one. The observed fermion mass spectrum is reproduced thanks to selection rules that discriminate among various contributions. Bottom-tau Yukawa unification is preserved at leading order, but there is no unification for the first two families. Interestingly, U(1)_F charges alone do not determine the hierarchy, and can only give upper bounds on the parametric suppression of the Yukawa operators.Comment: 14 pages, one figure. Few typos correcte

Non-Gaussianities due to Relativistic Corrections to the Observed Galaxy Bispectrum

High-precision constraints on primordial non-Gaussianity (PNG) will significantly improve our understanding of the physics of the early universe. Among all the subtleties in using large scale structure observables to constrain PNG, accounting for relativistic corrections to the clustering statistics is particularly important for the upcoming galaxy surveys covering progressively larger fraction of the sky. We focus on relativistic projection effects due to the fact that we observe the galaxies through the light that reaches the telescope on perturbed geodesics. These projection effects can give rise to an effective $f_{\rm NL}$ that can be misinterpreted as the primordial non-Gaussianity signal and hence is a systematic to be carefully computed and accounted for in modelling of the bispectrum. We develop the technique to properly account for relativistic effects in terms of purely observable quantities, namely angles and redshifts. We give some examples by applying this approach to a subset of the contributions to the tree-level bispectrum of the observed galaxy number counts calculated within perturbation theory and estimate the corresponding non-Gaussianity parameter, $f_{\rm NL}$, for the local, equilateral and orthogonal shapes. For the local shape, we also compute the local non-Gaussianity resulting from terms obtained using the consistency relation for observed number counts. Our goal here is not to give a precise estimate of $f_{\rm NL}$ for each shape but rather we aim to provide a scheme to compute the non-Gaussian contamination due to relativistic projection effects. For the terms considered in this work, we obtain contamination of $f_{\rm NL}^{\rm loc} \sim {\mathcal O}(1)$.Comment: 31 pages, 6 figures, Typos corrected to match the published version in JCA

Bayesian Analysis of Inflation III: Slow Roll Reconstruction Using Model Selection

We implement Slow Roll Reconstruction -- an optimal solution to the inverse problem for inflationary cosmology -- within ModeCode, a publicly available solver for the inflationary dynamics. We obtain up-to-date constraints on the reconstructed inflationary potential, derived from the WMAP 7-year dataset and South Pole Telescope observations, combined with large scale structure data derived from SDSS Data Release 7. Using ModeCode in conjunction with the MultiNest sampler, we compute Bayesian evidence for the reconstructed potential at each order in the truncated slow roll hierarchy. We find that the data are well-described by the first two slow roll parameters, \epsilon and \eta, and that there is no need to include a nontrivial \xi parameter.Comment: 14 pages, 12 figures, minor changes; final version; accepted in PR

Desarrollo aplicación móvil para la gestión de riesgo de sars-cov-2 en la educación media del municipio de Manizales, Caldas

Debido a la prolongada cuarentena, la COVID-19 ha representado una amenaza para la educación presencial global, ya que cerca del 80% de niños y adolescentes del mundo dejaron de asistir a los colegios en marzo de 2020. (Wilches-Visbal and Castillo-Pedraza, 2021). Con el fin de crear una herramienta que ayuden a controlar esta problemática desarrollaremos una aplicación móvil que contribuya a vigilar la propagación de este virus, aplicando los protocolos de bioseguridad en las instituciones de educación media del municipio de Manizales, identificando los posibles casos de manera temprana y alertando sobre estos.Due to the prolonged quarantine, COVID-19 has represented a threat to global face-to-face education, since nearly 80% of the world's children and adolescents stopped attending schools in March 2020. (Wilches-Visbal and Castillo- Pedraza, 2021). In order to create a tool to help control this problem, we will develop a mobile application that helps to monitor the spread of this virus, applying biosafety protocols in secondary education institutions in the municipality of Manizales, identifying possible cases early and warning about these

Application of the sine-cosine algorithm to the optimal design of a closed coil helical spring

This paper proposes the application of the sinecosine algorithm (SCA) to the optimal design of a closed coil helical spring. The optimization problem addressed corresponds to the minimization of total spring volume subject to physical constraints that represents the closed coil helical spring such as maximum working load, shear stress, and minimum diameter requirements, among other. The resulting mathematical formulation is a complex nonlinear and non-convex optimization model that is typically addressed in literature with trial and error methods or heuristic algorithms. To solve this problem efficiently, the SCA is proposed in this research. This optimization algorithm belongs to the family of the metaheuristic optimization techniques, it works with controlled random processes guided by sine and cosine trigonometric functions, that allows exploring and exploiting the solution space in order to find the best solution to the optimization problem. By presenting as main advantage an easy implementation at any programming language using sequential quadratic programming; eliminating the need to uses specialized and costly software. Numerical results demonstrating that the proposes SCA allows reaching lower spring volume values in comparison with literature approaches, such as genetic algorithms, particle swarm optimization methods, among others. All the numerical simulations have been implemented in the MATLAB software

A multidisciplinary European guideline for tinnitus: diagnostics, assessment, and treatment

International audienc

Simultaneous Minimization of Energy Losses and Greenhouse Gas Emissions in AC Distribution Networks Using BESS

The problem of the optimal operation of battery energy storage systems (BESSs) in AC grids is addressed in this paper from the point of view of multi-objective optimization. A nonlinear programming (NLP) model is presented to minimize the total emissions of contaminant gasses to the atmosphere and costs of daily energy losses simultaneously, considering the AC grid complete model. The BESSs are modeled with their linear relation between the state-of-charge and the active power injection/absorption. The Pareto front for the multi-objective optimization NLP model is reached through the general algebraic modeling system, i.e., GAMS, implementing the pondered optimization approach using weighting factors for each objective function. Numerical results in the IEEE 33-bus and IEEE 69-node test feeders demonstrate the multi-objective nature of this optimization problem and the multiple possibilities that allow the grid operators to carry out an efficient operation of their distribution networks when BESS and renewable energy resources are introduced.Universidad Tecnológica de Bolíva

An Improved Calculation of the Non-Gaussian Halo Mass Function

The abundance of collapsed objects in the universe, or halo mass function, is an important theoretical tool in studying the effects of primordially generated non-Gaussianities on the large scale structure. The non-Gaussian mass function has been calculated by several authors in different ways, typically by exploiting the smallness of certain parameters which naturally appear in the calculation, to set up a perturbative expansion. We improve upon the existing results for the mass function by combining path integral methods and saddle point techniques (which have been separately applied in previous approaches). Additionally, we carefully account for the various scale dependent combinations of small parameters which appear. Some of these combinations in fact become of order unity for large mass scales and at high redshifts, and must therefore be treated non-perturbatively. Our approach allows us to do this, and to also account for multi-scale density correlations which appear in the calculation. We thus derive an accurate expression for the mass function which is based on approximations that are valid over a larger range of mass scales and redshifts than those of other authors. By tracking the terms ignored in the analysis, we estimate theoretical errors for our result and also for the results of others. We also discuss the complications introduced by the choice of smoothing filter function, which we take to be a top-hat in real space, and which leads to the dominant errors in our expression. Finally, we present a detailed comparison between the various expressions for the mass functions, exploring the accuracy and range of validity of each.Comment: 28 pages, 13 figures; v2: text reorganized and some figured modified for clarity, results unchanged, references added. Matches version published in JCA