572 research outputs found

    Magnetic anisotropy in ordered textured Co nanowires

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    The following article appeared in Applied Physics Letters 100.25 (2012): 252405 and may be found at http://scitation.aip.org/content/aip/journal/apl/100/25/10.1063/1.4729782The magnetization reversal in ordered arrays of Co nanowires with tailored hcp-phase texture, controlled by pH synthesis and nanowires length, has been investigated. The angular dependence of coercivity has been experimentally determined for different crystal textures, and the corresponding magnetization reversal mode is interpreted by analytical modelling. The results show that reversal takes place by propagation of a transverse-like domain wall mode. The fitting of experimental and calculated data allows us the quantitative evaluation of the magnetocrystalline anisotropy constant strength whose magnetization easy direction evolves from parallel to the wires toward in-plane orientation with the change of hcp-phase textureThe project has been performed under bilateral Chile-Spain project 2010CL0018. Additional financial support is acknowledged from the Spanish Ministry of Science and Innovation, MICINN, and MAT2010-20798-C05-01. Financial support from FONDECYT No. 1110784, Grant ICM P10-061-F by Fondo de Innovación para la Competitividad-MINECON and Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia, under project FB0807

    Characterization of neutrino signals with radiopulses in dense media through the LPM effect

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    We discuss the possibilities of detecting radio pulses from high energy showers in ice, such as those produced by PeV and EeV neutrino interactions. It is shown that the rich radiation pattern structure in the 100 MHz to few GHz allows the separation of electromagnetic showers induced by photons or electrons above 100 PeV from those induced by hadrons. This opens up the possibility of measuring the energy fraction transmitted to the electron in a charged current electron neutrino interaction with adequate sampling of the angular distribution of the signal. The radio technique has the potential to complement conventional high energy neutrino detectors with flavor information.Comment: 5 pages, 4 ps figures. Submitted to Phys. Rev. Let

    Interstellar MHD Turbulence and Star Formation

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    This chapter reviews the nature of turbulence in the Galactic interstellar medium (ISM) and its connections to the star formation (SF) process. The ISM is turbulent, magnetized, self-gravitating, and is subject to heating and cooling processes that control its thermodynamic behavior. The turbulence in the warm and hot ionized components of the ISM appears to be trans- or subsonic, and thus to behave nearly incompressibly. However, the neutral warm and cold components are highly compressible, as a consequence of both thermal instability in the atomic gas and of moderately-to-strongly supersonic motions in the roughly isothermal cold atomic and molecular components. Within this context, we discuss: i) the production and statistical distribution of turbulent density fluctuations in both isothermal and polytropic media; ii) the nature of the clumps produced by thermal instability, noting that, contrary to classical ideas, they in general accrete mass from their environment; iii) the density-magnetic field correlation (or lack thereof) in turbulent density fluctuations, as a consequence of the superposition of the different wave modes in the turbulent flow; iv) the evolution of the mass-to-magnetic flux ratio (MFR) in density fluctuations as they are built up by dynamic compressions; v) the formation of cold, dense clouds aided by thermal instability; vi) the expectation that star-forming molecular clouds are likely to be undergoing global gravitational contraction, rather than being near equilibrium, and vii) the regulation of the star formation rate (SFR) in such gravitationally contracting clouds by stellar feedback which, rather than keeping the clouds from collapsing, evaporates and diperses them while they collapse.Comment: 43 pages. Invited chapter for the book "Magnetic Fields in Diffuse Media", edited by Elisabete de Gouveia dal Pino and Alex Lazarian. Revised as per referee's recommendation

    Fitting the integrated Spectral Energy Distributions of Galaxies

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    Fitting the spectral energy distributions (SEDs) of galaxies is an almost universally used technique that has matured significantly in the last decade. Model predictions and fitting procedures have improved significantly over this time, attempting to keep up with the vastly increased volume and quality of available data. We review here the field of SED fitting, describing the modelling of ultraviolet to infrared galaxy SEDs, the creation of multiwavelength data sets, and the methods used to fit model SEDs to observed galaxy data sets. We touch upon the achievements and challenges in the major ingredients of SED fitting, with a special emphasis on describing the interplay between the quality of the available data, the quality of the available models, and the best fitting technique to use in order to obtain a realistic measurement as well as realistic uncertainties. We conclude that SED fitting can be used effectively to derive a range of physical properties of galaxies, such as redshift, stellar masses, star formation rates, dust masses, and metallicities, with care taken not to over-interpret the available data. Yet there still exist many issues such as estimating the age of the oldest stars in a galaxy, finer details ofdust properties and dust-star geometry, and the influences of poorly understood, luminous stellar types and phases. The challenge for the coming years will be to improve both the models and the observational data sets to resolve these uncertainties. The present review will be made available on an interactive, moderated web page (sedfitting.org), where the community can access and change the text. The intention is to expand the text and keep it up to date over the coming years.Comment: 54 pages, 26 figures, Accepted for publication in Astrophysics & Space Scienc

    Toward an internally consistent astronomical distance scale

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    Accurate astronomical distance determination is crucial for all fields in astrophysics, from Galactic to cosmological scales. Despite, or perhaps because of, significant efforts to determine accurate distances, using a wide range of methods, tracers, and techniques, an internally consistent astronomical distance framework has not yet been established. We review current efforts to homogenize the Local Group's distance framework, with particular emphasis on the potential of RR Lyrae stars as distance indicators, and attempt to extend this in an internally consistent manner to cosmological distances. Calibration based on Type Ia supernovae and distance determinations based on gravitational lensing represent particularly promising approaches. We provide a positive outlook to improvements to the status quo expected from future surveys, missions, and facilities. Astronomical distance determination has clearly reached maturity and near-consistency.Comment: Review article, 59 pages (4 figures); Space Science Reviews, in press (chapter 8 of a special collection resulting from the May 2016 ISSI-BJ workshop on Astronomical Distance Determination in the Space Age

    Evidence for a mixed mass composition at the `ankle' in the cosmic-ray spectrum

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    We report a first measurement for ultra-high energy cosmic rays of the correlation between the depth of shower maximum and the signal in the water Cherenkov stations of air-showers registered simultaneously by the fluorescence and the surface detectors of the Pierre Auger Observatory. Such a correlation measurement is a unique feature of a hybrid air-shower observatory with sensitivity to both the electromagnetic and muonic components. It allows an accurate determination of the spread of primary masses in the cosmic-ray flux. Up till now, constraints on the spread of primary masses have been dominated by systematic uncertainties. The present correlation measurement is not affected by systematics in the measurement of the depth of shower maximum or the signal in the water Cherenkov stations. The analysis relies on general characteristics of air showers and is thus robust also with respect to uncertainties in hadronic event generators. The observed correlation in the energy range around the `ankle' at lg(E/eV)=18.519.0\lg(E/{\rm eV})=18.5-19.0 differs significantly from expectations for pure primary cosmic-ray compositions. A light composition made up of proton and helium only is equally inconsistent with observations. The data are explained well by a mixed composition including nuclei with mass A>4A > 4. Scenarios such as the proton dip model, with almost pure compositions, are thus disfavoured as the sole explanation of the ultrahigh-energy cosmic-ray flux at Earth.Comment: Published version. Added journal reference and DOI. Added Report Numbe

    Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

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    Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization
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