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تسجيل مستخدم جديدConstraining the dark energy and smoothness-parameter with supernovae
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The presence of inhomogeneities modifies the cosmic distances through the gravitational lensing effect, and, indirectly, must affect the main cosmological tests. Assuming that the dark energy is a smooth component, the simplest way to account for the influence of clustering is to suppose that the average evolution of the expanding Universe is governed by the total matter-energy density whereas the focusing of light is only affected by a fraction of the total matter density quantified by the $alpha$ Dyer-Roeder parameter. By using two different samples of SNe type Ia data, the $Omega_m$ and $alpha$ parameters are constrained by applying the Zeldovich-Kantowski-Dyer-Roeder (ZKDR) luminosity distance redshift relation for a flat ($Lambda$CDM) model. A $chi^{2}$-analysis using the 115 SNe Ia data of Astier {it et al.} sample (2006) constrains the density parameter to be $Omega_m=0.26_{-0.07}^{+0.17}$($2sigma$) while the $alpha$ parameter is weakly limited (all the values $in [0,1]$ are allowed even at 1$sigma$). However, a similar analysis based the 182 SNe Ia data of Riess {it et al.} (2007) constrains the pair of parameters to be $Omega_m= 0.33^{+0.09}_{-0.07}$ and $alphageq 0.42$ ($2sigma$). Basically, this occurs because the Riess {it et al.} sample extends to appreciably higher redshifts. As a general result, even considering the existence of inhomogeneities as described by the smoothness $alpha$ parameter, the Einstein-de Sitter model is ruled out by the two samples with a high degree of statistical confidence ($11.5sigma$ and $9.9sigma$, respectively). The inhomogeneous Hubble-Sandage diagram discussed here highlight the necessity of the dark energy, and a transition deceleration/accelerating phase at $zsim 0.5$ is also required.
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The existence of inhomogeneities in the observed Universe modifies the distance-redshift relations thereby affecting the results of cosmological tests in comparison to the ones derived assuming spatially uniform models. By modeling the inhomogeneitie
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