Merging for inhomogeneous finite Markov chains, part II: Nash and log-Sobolev inequalities

We study time-inhomogeneous Markov chains with finite state spaces using Nash and logarithmic-Sobolev inequalities, and the notion of $c$-stability. We develop the basic theory of such functional inequalities in the time-inhomogeneous context and provide illustrating examples.Comment: Published in at http://dx.doi.org/10.1214/10-AOP572 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

Time inhomogeneous Markov chains with wave-like behavior

Starting from a given Markov kernel on a finite set $V$ and a bijection $g$ of $V$, we construct and study a time inhomogeneous Markov chain whose kernel at time $n$ is obtained from $K$ by transport of $g^{n-1}$. We show that this construction leads to interesting examples, and we obtain quantitative results for some of these examples.Comment: Published in at http://dx.doi.org/10.1214/09-AAP661 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Ingesta y modelado de datos de aerolíneas mediante un pipeline utilizando tecnología disponible en la nube

Este trabajo expone la creación de un pipeline de datos en la nube en la plataforma AWS (Amazon Web Services) que mediante un ETL, que por sus siglas en Ingles Extract, Transform and Load se logra resolver el problema de saber cuáles son las aerolíneas registradas en la IATA (International Air Transport Association) que tienen más demoras en la salida, y en la llegada y mediante este análisis exponer un trabajo futuro para agregarlo como una nueva funcionalidad en las aplicaciones de venta de vuelos para que así los usuarios tengan un nuevo parámetro para elegir mediante mayor información, siendo este el objetivo principal del trabajo, el cual es: Crear un pipeline de ingesta de datos que permita recopilarlos y procesarlos de diversas fuentes y prepararlos para su análisis. Para hacerlo efectivo y útil para el análisis, es necesario definir un modelo de datos que estructure los datos de manera coherente y permita extraer información valiosa. AWS ofrece una amplia gama de herramientas que pueden ayudar a crear y gestionar un pipeline de ingesta de datos, como Amazon Glue. Además, es importante generar métricas que consideren las demoras en relación con los tipos de datos, en este caso, sobre las demoras en los vuelos. De esta manera, podremos optimizar el pipeline y garantizar un flujo de datos eficiente y de alta calidad. De igual manera se pretende confirmar la precisión de los datos usando un modelo de machine learning de regresión lineal con la herramienta de pyspark. Este tipo de modelo es muy útil para clasificar datos y puede ayudar a mejorar la precisión de las predicciones. Además, pyspark es una herramienta muy versátil y potente que permite realizar análisis y procesamiento de grandes conjuntos de datos de manera rápida y eficiente. Es importante tener en cuenta que la precisión de los datos es crucial para el éxito de cualquier proyecto de machine learning, por lo que es necesario realizar pruebas y validaciones para asegurarse de que los datos son confiables y están limpios.ITESO, A. C

Turing patterns in a p-adic FitzHugh-Nagumo system on the unit ball

We introduce discrete and p-adic continuous versions of the FitzHugh-Nagumo system on the one-dimensional p-adic unit ball. We provide criteria for the existence of Turing patterns. We present extensive simulations of some of these systems. The simulations show that the Turing patterns are traveling waves in the p-adic unit ball.Comment: Final version accepted in p-Adic Numbers, Ultrametric Analysis and Application

Spitzer and near-infrared observations of a new bi-polar protostellar outflow in the Rosette Molecular Cloud

We present and discuss \emph{Spitzer} and near-infrared H$_{2}$ observations of a new bi-polar protostellar outflow in the Rosette Molecular Cloud. The outflow is seen in all four IRAC bands and partially as diffuse emission in the MIPS 24 $\mu$m band. An embedded MIPS 24 $\mu$m source bisects the outflow and appears to be the driving source. This source is coincident with a dark patch seen in absorption in the 8 $\mu$m IRAC image. \emph{Spitzer} IRAC color analysis of the shocked emission was performed from which thermal and column density maps of the outflow were constructed. Narrow-band near-infrared (NIR) images of the flow reveal H$_2$ emission features coincident with the high temperature regions of the outflow. This outflow has now been given the designation MHO 1321 due to the detection of NIR H$_2$ features. We use these data and maps to probe the physical conditions and structure of the flow.Comment: Accepted for publication in The Astrophysical Journa

Fabrication and Optical Properties of a Fully Hybrid Epitaxial ZnO-Based Microcavity in the Strong Coupling Regime

In order to achieve polariton lasing at room temperature, a new fabrication methodology for planar microcavities is proposed: a ZnO-based microcavity in which the active region is epitaxially grown on an AlGaN/AlN/Si substrate and in which two dielectric mirrors are used. This approach allows as to simultaneously obtain a high-quality active layer together with a high photonic confinement as demonstrated through macro-, and micro-photoluminescence ({\mu}-PL) and reflectivity experiments. A quality factor of 675 and a maximum PL emission at k=0 are evidenced thanks to {\mu}-PL, revealing an efficient polaritonic relaxation even at low excitation power.Comment: 12 pages, 3 figure