Characterizing multipartite symmetric Dicke states under the effects of noise

We study genuine multipartite entanglement (GME) in a system of n qubits prepared in symmetric Dicke states and subjected to the influences of noise. We provide general, setup-independent expressions for experimentally favorable tools such as fidelity- and collective spin-based entanglement witnesses, as well as entangled-class discriminators and multi-point correlation functions. Besides highlighting the effects of the environment on large qubit registers, we also discuss strategies for the robust detection of GME. Our work provides techniques and results for the experimental communities interested in investigating and characterizing multipartite entangled states by introducing realistic milestones for setup design and associated predictions.

Interaction of High Intensity Picosecond Laser Pulses with Large Pre-formed Plasmas

The interaction of short (1-2 ps) laser pulses with solid targets at irradiances of over 1016 Wcm~2 , in the presence of a substantial prepulse has been investigated. High absorption of laser energy is found even at high angles of incidence, with evidence for a resonance absorption peak being found for S, P, and circular polarizations. It is considered that this may be a result of refraction and beam filamentation, which causes loss of distinct polarization. Measurements of hard X-ray emission (~ 100 keV) confirm a resonance absorption type peak at 45-50°, again for all three cases. Typically, 5-15% of the incident light is back-reflected by stimulated Brillouin scatter, with spatially resolved spectra showing evidence of beam hot-spots at high intensity. The possibility that filamentation and refraction of the beam can explain the lack of polarization dependence in the absorption and hard X-ray emission data is discussed.

Disaggregating conservative Protestant groups in Northern Ireland: Overlapping categories and the importance of a born-again self-identification

Rather than treating conservative Protestantism as a homogenous phenomenon, recent literature has underlined the importance of disaggregating this group to illuminate important attitudinal and behavioral differences between conservative Protestants. However, the methods used to empirically operationalize conservative Protestantism have not always been able to capture variations within the groupings. Based on analysis of the 2004 Northern Ireland Life and Times Survey, we argue that religious self-identification is a more useful way of analyzing conservative Protestant subgroups than denomination or religious belief. We show that many of these identifications are overlapping, rather than stand-alone, religious group identifications. Moreover, the identification category of born-again has seldom been included in surveys. We find having a born-again identification to be a better predictor than the more frequently asked fundamentalist and evangelical categories of the religious and social beliefs that are seen as indicative of conservative Protestantism.

Nature as historical protagonist: environment and society in pre-industrial England

This article compares chronologies reconstructed from historical records of prices, wages, grain harvests, and population with corresponding chronologies of growing conditions and climatic variations derived from dendrochronology and Greenland ice-cores. It demonstrates that in pre-industrial, and especially late medieval, England, short-term environmental shocks and more enduring shifts in environmental conditions (sometimes acting in concert with biological agencies) exercised a powerful influence upon the balance struck between population and available resources via their effects upon the reproduction, health and life expectancy of humans, crops, and livestock. Prevailing socio-economic conditions and institutions, in turn, shaped society's susceptibility to these environmental shocks and shifts.

La visión artificial, un nuevo aliado para el análisis de imágenes artísticas

En este estudio se evalúa el rendimiento de los métodos de Bag-of-Visualterms (BOV) para la clasificación automática de imágenes digitales de la base de datos del artista Miquel Planas. Estas imágenes intervienen en la ideación y diseño de su producción escultórica. Constituye un interesante desafío dada la dificultad de la categorización de escenas cuando éstas difieren más por los contenidos semánticos que por los objetos que contienen. Hemos empleado un método de reconocimiento basado en Kernels introducido por Lazebnik, Schmid y Ponce en 2006. Los resultados son prometedores, en promedio, la puntuación del rendimiento es aproximadamente del 70%. Los experimentos sugieren que la categorización automática de imágenes basada en métodos de visión artificial puede proporcionar principios objetivos en la catalogación de imágenes y que los resultados obtenidos pueden ser aplicados en diferentes campos de la creación artística.