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Register a new userRevisiting a non-parametric reconstruction of the deceleration parameter from observational data
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A non-parametric reconstruction of the deceleration parameter $q$ is carried out. The observational datasets are so chosen that they are model independent as much as possible. The present acceleration and the epoch at which the cosmic acceleration sets in is quite as expected, but beyond a certain redshift ($z sim 2$), a negative value of $q$ appears to be in the allowed region. A survey of existing literature is given and compared with the results obtained in the present work.
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The cosmological jerk parameter $j$ is reconstructed in a non-parametric way from observational data independent of a fiducial cosmological model. From this kinematical quantity, the equation of state parameter for composite matter distribution is also found out. The result shows that there is a deviation from the $Lambda$CDM model close to $z=1.5$, at the $3sigma$ confidence level.
Perturbative quantities, such as the growth rate ($f$) and index ($gamma$), are powerful tools to distinguish different dark energy models or modified gravity theories even if they produce the same cosmic expansion history. In this work, without any assumption about the dynamics of the Universe, we apply a non-parametric method to current measurements of the expansion rate $H(z)$ from cosmic chronometers and high-$z$ quasar data and reconstruct the growth factor and rate of linearised density perturbations in the non-relativistic matter component. Assuming realistic values for the matter density parameter $Omega_{m0}$, as provided by current CMB experiments, we also reconstruct the evolution of the growth index $gamma$ with redshift. We show that the reconstruction of current $H(z)$ data constrains the growth index to $gamma=0.56 pm 0.12$ (2$sigma$) at $z = 0.09$, which is in full agreement with the prediction of the $Lambda$CDM model and some of its extensions.
In order to explore the generic properties of a backreaction model for explaining the accelerated expansion of the Universe, we exploit two metrics to describe the late time Universe. Since the standard FLRW metric cannot precisely describe the late time Universe on small scales, the template metric with an evolving curvature parameter $kappa_{mathcal{D}}(t)$ is employed. However, we doubt the validity of the prescription for $kappa_{mathcal{D}}$, which motivates us apply observational Hubble parameter data (OHD) to constrain parameters in dust cosmology. First, for FLRW metric, by getting best-fit constraints of $Omega^{{mathcal{D}}_0}_m = 0.25^{+0.03}_{-0.03}$, $n = 0.02^{+0.69}_{-0.66}$, and $H_{mathcal{D}_0} = 70.54^{+4.24}_{-3.97} {rm km s^{-1} Mpc^{-1}}$, the evolutions of parameters are explored. Second, in template metric context, by marginalizing over $H_{mathcal{D}_0}$ as a prior of uniform distribution, we obtain the best-fit values of $n=-1.22^{+0.68}_{-0.41}$ and ${{Omega}_{m}^{mathcal{D}_{0}}}=0.12^{+0.04}_{-0.02}$. Moreover, we utilize three different Gaussian priors of $H_{mathcal{D}_0}$, which result in different best-fits of $n$, but almost the same best-fit value of ${{Omega}_{m}^{mathcal{D}_{0}}}sim0.12$. Also, the absolute constraints without marginalization of parameter are obtained: $n=-1.1^{+0.58}_{-0.50}$ and ${{Omega}_{m}^{mathcal{D}_{0}}}=0.13pm0.03$. With these constraints, the evolutions of the effective deceleration parameter $q^{mathcal{D}}$ indicate that the backreaction can account for the accelerated expansion of the Universe without involving extra dark energy component in the scaling solution context. Nevertheless, the results also verify that the prescription of $kappa_{mathcal{D}}$ is insufficient and should be improved.
In the context of a Hubble tension problem that is growing in its statistical significance, we reconsider the effectiveness of non-parametric reconstruction techniques which are independent of prescriptive cosmological models. By taking cosmic chronometers, Type Ia Supernovae and baryonic acoustic oscillation data, we compare and contrast two important reconstruction approaches, namely Gaussian processes (GP) and the Locally weighted Scatterplot Smoothing together with Simulation and extrapolation method (LOESS-Simex or LS). We firstly show how both GP and LOESS-Simex can be used to successively reconstruct various data sets to a high level of precision. We then directly compare both approaches in a quantitative manner by considering several factors, such as how well the reconstructions approximate the data sets themselves to how their respective uncertainties evolve. In light of the puzzling Hubble tension, it is important to consider how the uncertain regions evolve over redshift and the methods compare for estimating cosmological parameters at current times. For cosmic chronometers and baryonic acoustic oscillation compiled data sets, we find that GP generically produce smaller variances for the reconstructed data with a minimum value of $sigma_{rm GP-min} = 1.1$, while the situation for LS is totally different with a minimum of $sigma_{rm LS-min} = 50.8$. Moreover, some of these characteristics can be alliviate at low $z$, where LS presents less underestimation in comparison to GP.
The tomographic Alcock-Paczynski (AP) method can result in tight cosmological constraints by using small and intermediate clustering scales of the large scale structure (LSS) of the galaxy distribution. By focusing on the redshift dependence, the AP distortion can be distinguished from the distortions produced by the redshift space distortions (RSD). In this work, we combine the tomographic AP method with other recent observational datasets of SNIa+BAO+CMB+$H_0$ to reconstruct the dark energy equation-of-state $w$ in a non-parametric form. The result favors a dynamical DE at $zlesssim1$, and shows a mild deviation ($lesssim2sigma$) from $w=-1$ at $z=0.5-0.7$. We find the addition of the AP method improves the low redshift ($zlesssim0.7$) constraint by $sim50%$.
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