4 resultados para SDSS

em Universidade Federal do Rio Grande do Norte(UFRN)


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The recent astronomical observations indicate that the universe has null spatial curvature, is accelerating and its matter-energy content is composed by circa 30% of matter (baryons + dark matter) and 70% of dark energy, a relativistic component with negative pressure. However, in order to built more realistic models it is necessary to consider the evolution of small density perturbations for explaining the richness of observed structures in the scale of galaxies and clusters of galaxies. The structure formation process was pioneering described by Press and Schechter (PS) in 1974, by means of the galaxy cluster mass function. The PS formalism establishes a Gaussian distribution for the primordial density perturbation field. Besides a serious normalization problem, such an approach does not explain the recent cluster X-ray data, and it is also in disagreement with the most up-to-date computational simulations. In this thesis, we discuss several applications of the nonextensive q-statistics (non-Gaussian), proposed in 1988 by C. Tsallis, with special emphasis in the cosmological process of the large structure formation. Initially, we investigate the statistics of the primordial fluctuation field of the density contrast, since the most recent data from the Wilkinson Microwave Anisotropy Probe (WMAP) indicates a deviation from gaussianity. We assume that such deviations may be described by the nonextensive statistics, because it reduces to the Gaussian distribution in the limit of the free parameter q = 1, thereby allowing a direct comparison with the standard theory. We study its application for a galaxy cluster catalog based on the ROSAT All-Sky Survey (hereafter HIFLUGCS). We conclude that the standard Gaussian model applied to HIFLUGCS does not agree with the most recent data independently obtained by WMAP. Using the nonextensive statistics, we obtain values much more aligned with WMAP results. We also demonstrate that the Burr distribution corrects the normalization problem. The cluster mass function formalism was also investigated in the presence of the dark energy. In this case, constraints over several cosmic parameters was also obtained. The nonextensive statistics was implemented yet in 2 distinct problems: (i) the plasma probe and (ii) in the Bremsstrahlung radiation description (the primary radiation from X-ray clusters); a problem of considerable interest in astrophysics. In another line of development, by using supernova data and the gas mass fraction from galaxy clusters, we discuss a redshift variation of the equation of state parameter, by considering two distinct expansions. An interesting aspect of this work is that the results do not need a prior in the mass parameter, as usually occurs in analyzes involving only supernovae data.Finally, we obtain a new estimate of the Hubble parameter, through a joint analysis involving the Sunyaev-Zeldovich effect (SZE), the X-ray data from galaxy clusters and the baryon acoustic oscillations. We show that the degeneracy of the observational data with respect to the mass parameter is broken when the signature of the baryon acoustic oscillations as given by the Sloan Digital Sky Survey (SDSS) catalog is considered. Our analysis, based on the SZE/X-ray data for a sample of 25 galaxy clusters with triaxial morphology, yields a Hubble parameter in good agreement with the independent studies, provided by the Hubble Space Telescope project and the recent estimates of the WMAP

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The northern coast of Rio Grande do Norte State (RN) shows areas of Potiguar basin with high activity in petroleum industry. With the goal of avoiding and reducing the accident risks with oil it is necessary to understand the natural vulnerability, mapping natural resources and monitoring the oil spill. The use of computational tools for environmental monitoring makes possible better analyses and decisions in political management of environmental preservation. This work shows a methodology for monitoring of environment impacts, with purpose of avoiding and preserving the sensible areas in oil contact. That methodology consists in developing and embedding an integrated computational system. Such system is composed by a Spatial Decision Support System (SDSS). The SDSS shows a computational infrastructure composed by Web System of Geo-Environmental and Geographic Information - SWIGG , the System of Environmental Sensibility Maps for Oil Spill AutoMSA , and the Basic System of Environmental Hydrodynamic ( SisBAHIA a System of Modeling and Numerical Simulating SMNS). In a scenario of oil spill occurred coastwise of Rio Grande do Norte State s northern coast, the integration of such systems will give support to decision agents for managing of environmental impacts. Such support is supplied through a system of supporting to spatial decisions

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A significant observational effort has been directed to investigate the nature of the so-called dark energy. In this dissertation we derive constraints on dark energy models using three different observable: measurements of the Hubble rate H(z) (compiled by Meng et al. in 2015.); distance modulus of 580 Supernovae Type Ia (Union catalog Compilation 2.1, 2011); and the observations of baryon acoustic oscilations (BAO) and the cosmic microwave background (CMB) by using the so-called CMB/BAO of six peaks of BAO (a peak determined through the Survey 6dFGS data, two through the SDSS and three through WiggleZ). The statistical analysis used was the method of the χ2 minimum (marginalized or minimized over h whenever possible) to link the cosmological parameter: m, ω and δω0. These tests were applied in two parameterization of the parameter ω of the equation of state of dark energy, p = ωρ (here, p is the pressure and ρ is the component of energy density). In one, ω is considered constant and less than -1/3, known as XCDM model; in the other the parameter of state equantion varies with the redshift, where we the call model GS. This last model is based on arguments that arise from the theory of cosmological inflation. For comparison it was also made the analysis of model CDM. Comparison of cosmological models with different observations lead to different optimal settings. Thus, to classify the observational viability of different theoretical models we use two criteria information, the Bayesian information criterion (BIC) and the Akaike information criteria (AIC). The Fisher matrix tool was incorporated into our testing to provide us with the uncertainty of the parameters of each theoretical model. We found that the complementarity of tests is necessary inorder we do not have degenerate parametric spaces. Making the minimization process we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are m = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059. Performing a marginalization we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are M = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059.

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A significant observational effort has been directed to investigate the nature of the so-called dark energy. In this dissertation we derive constraints on dark energy models using three different observable: measurements of the Hubble rate H(z) (compiled by Meng et al. in 2015.); distance modulus of 580 Supernovae Type Ia (Union catalog Compilation 2.1, 2011); and the observations of baryon acoustic oscilations (BAO) and the cosmic microwave background (CMB) by using the so-called CMB/BAO of six peaks of BAO (a peak determined through the Survey 6dFGS data, two through the SDSS and three through WiggleZ). The statistical analysis used was the method of the χ2 minimum (marginalized or minimized over h whenever possible) to link the cosmological parameter: m, ω and δω0. These tests were applied in two parameterization of the parameter ω of the equation of state of dark energy, p = ωρ (here, p is the pressure and ρ is the component of energy density). In one, ω is considered constant and less than -1/3, known as XCDM model; in the other the parameter of state equantion varies with the redshift, where we the call model GS. This last model is based on arguments that arise from the theory of cosmological inflation. For comparison it was also made the analysis of model CDM. Comparison of cosmological models with different observations lead to different optimal settings. Thus, to classify the observational viability of different theoretical models we use two criteria information, the Bayesian information criterion (BIC) and the Akaike information criteria (AIC). The Fisher matrix tool was incorporated into our testing to provide us with the uncertainty of the parameters of each theoretical model. We found that the complementarity of tests is necessary inorder we do not have degenerate parametric spaces. Making the minimization process we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are m = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059. Performing a marginalization we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are M = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059.