Stretched Horizon for Non-Supersymmetric Black Holes

We review the idea of stretched horizon for extremal black holes in supersymmetric string theories, and we compute it for non-supersymmetric black holes in four dimensions. Only for small masses of the order of the Veneziano wavelength is the stretched horizon bigger than the event horizon.Comment: 4 pages, 2 figures, to appear in the Proceedings of the VIII Mexican School, Oaxaca, AI

Heavy neutralino relic abundance with Sommerfeld enhancements - a study of pMSSM scenarios

We present a detailed discussion of Sommerfeld enhancements in neutralino dark matter relic abundance calculations for several popular benchmark scenarios in the general MSSM. Our analysis is focused on models with heavy wino- and higgsino-like neutralino LSP and models interpolating between these two scenarios. This work is the first phenomenological application of effective field theory methods that we have developed in earlier work and that allow for the consistent study of Sommerfeld enhancements in non-relativistic neutralino and chargino co-annihilation reactions within the general MSSM, away from the pure-wino and pure-higgsino limits.Comment: 38 pages, 14 figures, 3 table

Non-relativistic pair annihilation of nearly mass degenerate neutralinos and charginos I. General framework and S-wave annihilation

We compute analytically the tree-level annihilation rates of a collection of non-relativistic neutralino and chargino two-particle states in the general MSSM, including the previously unknown off-diagonal rates. The results are prerequisites to the calculation of the Sommerfeld enhancement in the MSSM, which will be presented in subsequent work. They can also be used to obtain concise analytic expressions for MSSM dark matter pair annihilation in the present Universe for a large number of exclusive two-particle final states.Comment: LATeX, 24 pages (+ 25 pages Appendix), 11 figures; v2 - replaced incorrect version of Fig. 4 and fixed typos listed in the JHEP erratu

Situations in traffic - how quickly they change

Spatio-temporal correlations of intensity of traffic are analysed for one week data collected in the motorway M-30 around Madrid in January 2009. We found that the lifetime of these correlations is the shortest in the evening, between 6 and 8 p.m. This lifetime is a new indicator how much attention of drivers is demanded in given traffic conditions.Comment: 9 pages, 6 figure

Nongauge bright soliton of the nonlinear Schrodinger (NLS) equation and a family of generalized NLS equations

We present an approach to the bright soliton solution of the NLS equation from the standpoint of introducing a constant potential term in the equation. We discuss a `nongauge' bright soliton for which both the envelope and the phase depend only on the traveling variable. We also construct a family of generalized NLS equations with solitonic sech^p solutions in the traveling variable and find an exact equivalence with other nonlinear equations, such as the Korteveg-de Vries and Benjamin-Bona-Mahony equations when p=2Comment: ~4 pages, 3 figures, 16 references, published versio

Reproducible and User-Controlled Software Environments in HPC with Guix

Support teams of high-performance computing (HPC) systems often find themselves between a rock and a hard place: on one hand, they understandably administrate these large systems in a conservative way, but on the other hand, they try to satisfy their users by deploying up-to-date tool chains as well as libraries and scientific software. HPC system users often have no guarantee that they will be able to reproduce results at a later point in time, even on the same system-software may have been upgraded, removed, or recompiled under their feet, and they have little hope of being able to reproduce the same software environment elsewhere. We present GNU Guix and the functional package management paradigm and show how it can improve reproducibility and sharing among researchers with representative use cases.Comment: 2nd International Workshop on Reproducibility in Parallel Computing (RepPar), Aug 2015, Vienne, Austria. http://reppar.org

Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians

This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of finite mixture models, conjugate families and factorization. Both the joint probability density of the variables and the likelihood function of the (objective or subjective) observation are approximated by a special mixture model, in such a way that any desired conditional distribution can be directly obtained without numerical integration. We have developed an extended version of the expectation maximization (EM) algorithm to estimate the parameters of mixture models from uncertain training examples (indirect observations). As a consequence, any piece of exact or uncertain information about both input and output values is consistently handled in the inference and learning stages. This ability, extremely useful in certain situations, is not found in most alternative methods. The proposed framework is formally justified from standard probabilistic principles and illustrative examples are provided in the fields of nonparametric pattern classification, nonlinear regression and pattern completion. Finally, experiments on a real application and comparative results over standard databases provide empirical evidence of the utility of the method in a wide range of applications