5,367 research outputs found

    NLO predictions for the growth of F2F_2 at small xx and comparison with experimental data

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    We present parametrizations for the proton structure function F2F_2 in the next to leading order in perturbative QCD. The calculations show that the dominant term to F2(x,Q2)F_2(x,Q^2) should grow as x^{-\ls} for small xx values, with the exponent \ls being essentially independent of Q2Q^2. Comparisons with the most recent H1 and ZEUS data confirm the value \ls \sim 0.35 obtained previously from fits to low energy data.Comment: 18 page

    Pomerons and Jet Events at HERA

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    We study two and three jet events with a large rapidity gap at HERA. Unlike in the Ingelman-Schlein approach we do not adscribe a structure to the Pomeron. Instead, the coupling of the Pomeron to quarks or gluons is taken pointlike, which makes the model easy to test: the only degrees of freedom are the coupling constants of the Pomeron to the quarks or the gluons and a cutoff procedure to keep the Pomeron-gluon coupling well behaved.Comment: Latex fil

    Identifiability of large nonlinear biochemical networks

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    Dynamic models formulated as a set of ordinary differential equations provide a detailed description of the time-evolution of a system. Such models of (bio)chemical reaction networks have contributed to important advances in biotechnology and biomedical applications, and their impact is foreseen to increase in the near future. Hence, the task of dynamic model building has attracted much attention from scientists working at the intersection of biochemistry, systems theory, mathematics, and computer science, among other disciplines-an area sometimes called systems biology. Before a model can be effectively used, the values of its unknown parameters have to be estimated from experimental data. A necessary condition for parameter estimation is identifiability, the property that, for a certain output, there exists a unique (or finite) set of parameter values that produces it. Identifiability can be analysed from two complementary points of view: structural (which searches for symmetries in the model equations that may prevent parameters from being uniquely determined) or practical (which focuses on the limitations introduced by the quantity and quality of the data available for parameter estimation). Both types of analyses are often difficult for nonlinear models, and their complexity increases rapidly with the problem size. Hence, assessing the identifiability of realistic dynamic models of biochemical networks remains a challenging task. Despite the fact that many methods have been developed for this purpose, it is still an open problem and an active area of research. Here we review the theory and tools available for the study of identifiability, and discuss some closely related concepts such as sensitivity to parameter perturbations, observability, distinguishability, and optimal experimental design, among others.This work was funded by the Galician government (Xunta de Galiza) through the I2C postdoctoral program (fellowship ED481B2014/133-0), and by the Spanish Ministry of Economy and Competitiveness (grant DPI2013-47100-C2-2-P)

    An identification procedure for woolly soft-flesh peaches by instrumental assessment

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    Woolliness in peaches, a negative attribute of sensory texture characterized by the lack of crispness and juiciness, also known as mealiness in other fruits, has been identified fruit-by fruit by instrumental means. The use of a non-supervised clustering data analysis procedure, studying crispness and juiciness, enables four instrumental degrees of texture degradation to be defined, of which woolliness appears to be the last stage. This procedure also provides some information on several experimental factors (ripeness stages, storage time and storage temperature) with regard to the onset of woolliness. It is confirmed through this study that, in Maycrest peaches, woolliness starts to appear after 2 weeks of storage at 5┬░C. Fruits classified at harvest in 'first' and 'second' ripeness stages are more susceptible to woolliness than those in the third ripeness stage. This clustering procedure may also be effective for studying other species, varieties and quality attributes of fruit

    Electromagnetically induced spatial light modulation

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    We theoretically report that, utilizing electromagnetically induced transparency (EIT), the transverse spatial properties of weak probe fields can be fast modulated by using optical patterns (e.g. images) with desired intensity distributions in the coupling fields. Consequently, EIT systems can function as high-speed optically addressed spatial light modulators. To exemplify our proposal, we indicate the generation and manipulation of Laguerre-Gaussian beams based on either phase or amplitude modulation in hot vapor EIT systems.Comment: 8 pages, 3 figure

    Tests of Gaussianity

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    We review two powerful methods to test the Gaussianity of the cosmic microwave background (CMB): one based on the distribution of spherical wavelet coefficients and the other on smooth tests of goodness-of-fit. The spherical wavelet families proposed to analyse the CMB are the Haar and the Mexican Hat ones. The latter is preferred for detecting non-Gaussian homogeneous and isotropic primordial models containing some amount of skewness or kurtosis. Smooth tests of goodness-of-fit have recently been introduced in the field showing some interesting properties. We will discuss the smooth tests of goodness-of-fit developed by Rayner and Best for the univariate as well as for the multivariate analysis.Comment: Proceedings of "The Cosmic Microwave Background and its Polarization", New Astronomy Reviews, (eds. S. Hanany and K.A. Olive), in pres

    An optimal estimator for the CMB-LSS angular power spectrum and its application to WMAP and NVSS data

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    We use a Quadratic Maximum Likelihood (QML) method to estimate the angular power spectrum of the cross-correlation between cosmic microwave background and large scale structure maps as well as their individual auto-spectra. We describe our implementation of this method and demonstrate its accuracy on simulated maps. We apply this optimal estimator to WMAP 7-year and NRAO VLA Sky Survey (NVSS) data and explore the robustness of the angular power spectrum estimates obtained by the QML method. With the correction of the declination systematics in NVSS, we can safely use most of the information contained in this survey. We then make use of the angular power spectrum estimates obtained by the QML method to derive constraints on the dark energy critical density in a flat ╬Ť\LambdaCDM model by different likelihood prescriptions. When using just the cross-correlation between WMAP 7 year and NVSS maps with 1.8Ôłś^\circ resolution, the best-fit model has a cosmological constant of approximatively 70% of the total energy density, disfavouring an Einstein-de Sitter Universe at more than 2 ¤â\sigma CL (confidence level).Comment: 12 pages, 12 figure

    Analysis of CMB maps with 2D wavelets

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    We consider the 2D wavelet transform with two scales to study sky maps of temperature anisotropies in the cosmic microwave background radiation (CMB). We apply this technique to simulated maps of small sky patches of size 12.8 \times 12.8 square degrees and 1.5' \times 1.5' pixels. The relation to the standard approach, based on the cl's is established through the introduction of the scalogram. We consider temperature fluctuations derived from standard, open and flat-Lambda CDM models. We analyze CMB anisotropies maps plus uncorrelated Gaussian noise (uniform and non-uniform) at idfferent S/N levels. We explore in detail the denoising of such maps and compare the results with other techniques already proposed in the literature. Wavelet methods provide a good reconstruction of the image and power spectrum. Moreover, they are faster than previously proposed methods.Comment: latex file 7 pages + 5 postscript files + 1 gif file; accepted for publication in A&A

    Full-sky correlations of peaks in the microwave background

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    We compute precise predictions for the two-point correlation function of local maxima (or minima) in the temperature of the microwave background, under the assumption that it is a random gaussian field. For a given power spectrum and peak threshold there are no adjustable parameters, and since this analysis does not make the small-angle approximation of Heavens & Sheth (1999), it is essentially complete. We find oscillatory features which are absent in the temperature autocorrelation function, and we also find that the small-angle approximation to the peak-peak correlation function is accurate to better than 0.01 on all scales. These high-precision predictions can form the basis of a sensitive test of the gaussian hypothesis with upcoming all-sky microwave background experiments MAP and Planck, affording a thorough test of the inflationary theory of the early Universe. To illustrate the effectiveness of the technique, we apply it to simulated maps of the microwave sky arising from the cosmic string model of structure formation, and compare with the bispectrum as a non-gaussian discriminant. We also show how peak statistics can be a valuable tool in assessing and statistically removing contamination of the map by foreground point sources.Comment: submitted to MNRA
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