National Center for Supercomputing Applications

About: National Center for Supercomputing Applications is a facility organization based out in Sofia, Bulgaria. It is known for research contribution in the topics: Galaxy & Redshift. The organization has 598 authors who have published 2083 publications receiving 76894 citations. The organization is also known as: NCSA.

Direct evidence for neutrino flavor transformation from neutral current interactions in the Sudbury Neutrino Observatory

Abstract: Observations of neutral-current nu interactions on deuterium in the Sudbury Neutrino Observatory are reported. Using the neutral current (NC), elastic scattering, and charged current reactions and assuming the standard 8B shape, the nu(e) component of the 8B solar flux is phis(e) = 1.76(+0.05)(-0.05)(stat)(+0.09)(-0.09)(syst) x 10(6) cm(-2) s(-1) for a kinetic energy threshold of 5 MeV. The non-nu(e) component is phi(mu)(tau) = 3.41(+0.45)(-0.45)(stat)(+0.48)(-0.45)(syst) x 10(6) cm(-2) s(-1), 5.3sigma greater than zero, providing strong evidence for solar nu(e) flavor transformation. The total flux measured with the NC reaction is phi(NC) = 5.09(+0.44)(-0.43)(stat)(+0.46)(-0.43)(syst) x 10(6) cm(-2) s(-1), consistent with solar models.

Multiliteracies: Lit Learning

Abstract: Multiliteracies considers the future of literacy teaching in the context of the rapidly changing English language. Questions are raised about what constitutes appropriate literacy teaching in today's world: a world that is both a global village yet one which local diversity is increasingly important. This is a coherent and accessible overview of the work of the New London Group, with well-known international contributors bringing together their varying national experiences and differences of theoretical and political emphasis. The essays deal with issues such as: * the fundamental premises of literacy pedagogy * the effects of technological change * multilingualism and cultual diversity * social futures and their implications on language teaching. The book concludes with case studies of attempts to put the theories into practice and thereby provides a basis for dialogue with fellow educators around the world.

Statistical Properties of X-Ray Clusters: Analytic and Numerical Comparisons

Abstract: We compare the results of Eulerian hydrodynamic simulations of cluster formation against virial scaling relations between four bulk quantities: the cluster mass, the dark matter velocity dispersion, the gas temperature, and the cluster luminosity. The comparison is made for a large number of clusters at a range of redshifts in three different cosmological models (cold plus hot dark matter, cold dark matter, and open cold dark matter). We find that the analytic formulae provide a good description of the relations between three of the four numerical quantities. The fourth (luminosity) also agrees once we introduce a procedure to correct for the fixed numerical resolution. We also compute the normalizations for the virial relations and compare extensively to the existing literature, finding remarkably good agreement. The Press-Schechter prescription is calibrated with the simulations, again finding results consistent with other authors. We also examine related issues such as the size of the scatter in the virial relations, the effect of metallicity with a fixed passband, and the structure of the halos. All of this is done in order to establish a firm groundwork for the use of clusters as cosmological probes. Implications for the models are briefly discussed.

Statistical Properties of X-ray Clusters: Analytic and Numerical Comparisons

Abstract: We compare the results of Eulerian hydrodynamic simulations of cluster formation against virial scaling relations between four bulk quantities: the cluster mass, the dark matter velocity dispersion, the gas temperature and the cluster luminosity. The comparison is made for a large number of clusters at a range of redshifts in three different cosmological models (CHDM, CDM and OCDM). We find that the analytic formulae provide a good description of the relations between three of the four numerical quantities. The fourth (luminosity) also agrees once we introduce a procedure to correct for the fixed numerical resolution. We also compute the normalizations for the virial relations and compare extensively to the existing literature, finding remarkably good agreement. The Press-Schechter prescription is calibrated with the simulations, again finding results consistent with other authors. We also examine related issues such as the size of the scatter in the virial relations, the effect of metallicity with a fixed pass-band, and the structure of the halos. All of this is done in order to establish a firm groundwork for the use of clusters as cosmological probes. Implications for the models are briefly discussed.

Semantic Image Inpainting with Deep Generative Models

Abstract: Semantic image inpainting is a challenging task where large missing regions have to be filled based on the available visual data. Existing methods which extract information from only a single image generally produce unsatisfactory results due to the lack of high level context. In this paper, we propose a novel method for semantic image inpainting, which generates the missing content by conditioning on the available data. Given a trained generative model, we search for the closest encoding of the corrupted image in the latent image manifold using our context and prior losses. This encoding is then passed through the generative model to infer the missing content. In our method, inference is possible irrespective of how the missing content is structured, while the state-of-the-art learning based method requires specific information about the holes in the training phase. Experiments on three datasets show that our method successfully predicts information in large missing regions and achieves pixel-level photorealism, significantly outperforming the state-of-the-art methods.