Related papers: Reconstructing equation of state of dark energy wi…
We reconstruct late-time cosmology using the technique of Principal Component Analysis (PCA). In particular, we focus on the reconstruction of the dark energy equation of state from two different observational data-sets, Supernovae type Ia…
In the present paper, we investigate the dark energy equation of state using the Gaussian processes analysis method, without confining a particular parametrization. The reconstruction is carried out by adopting the background data including…
We study the power of current and future observational Hubble parameter data (OHD) on non-parametric estimations of the dark energy equation of state, $w(z)$. We propose a new method by conjunction of principal component analysis (PCA) and…
We explore snares in determining the equation of state of dark energy ($\omega$) when one uses the so-called principal component analysis for multiple observations. We demonstrated drawbacks of principal component analysis in an earlier…
One of the main tasks for present and future dark energy surveys is to determine whether the dark energy is dynamical or not. To illustrate this from data, it is commonly used to parameterize the dark energy equation of state w as several…
Reconstructing the evolution history of the dark energy equation of state parameter $w(z)$ directly from observational data is highly valuable in cosmology, since it contains substantial clues in understanding the nature of the accelerated…
With a parametric form of the equation of state parameter of dark energy, a quintessence potential has been reconstructed. The potential is found to be a generalization of a double exponential potential. The constraints on the parameters…
An important issue in cosmology is reconstructing the effective dark energy equation of state directly from observations. With so few physically motivated models, future dark energy studies cannot only be based on constraining a dark energy…
Principal component analysis is considered as an addition to the well-tested parametrization w(a)=w_0+w_a(1-a) for the dark energy equation of state. This brief note cautions against some unjustified assumptions in interpretation of PCA…
We discuss methods based on Principal Component Analysis to constrain the dark energy equation of state using a combination of Type Ia supernovae at low redshift and spectroscopic measurements of varying fundamental couplings at higher…
This review summarizes recent attempts to reconstruct the expansion history of the Universe and to probe the nature of dark energy. Reconstruction methods can be broadly classified into parametric and non-parametric approaches. It is…
The possibility of reconstructing the dark energy equation of state from variations in the fine structure constant is investigated for a class of models where the quintessence field is non-minimally coupled to the electromagnetic field. For…
We compare four different methods that can be used to analyze the type Ia supernovae (SnIa) data, ie to use piecewise-constant functions in terms of: the dark energy equation of state $w(z)$, the deceleration parameter $q(z)$, the Hubble…
We adopt a model independent method to reconstruct the dark energy equation of state by analyzing 5 sets of SNe Ia data along with Baryon Acoustic Oscillation (BAO) and Observational Hubble Data (OHD). The SNe Ia data sets include the most…
A basic aim of ongoing and upcoming cosmological surveys is to unravel the mystery of dark energy. In the absence of a compelling theory to test, a natural approach is to better characterize the properties of dark energy in search of clues…
Principal Component Analysis (PCA) is one of the most used tools for extracting low-dimensional representations of data, in particular for time series. Performances are known to strongly depend on the quality (amount of noise) and the…
Principal Component Analysis (PCA) is a classical method for reducing the dimensionality of data by projecting them onto a subspace that captures most of their variation. Effective use of PCA in modern applications requires understanding…
We look for evidence for the evolution in dark energy density by employing Principal Component Analysis (PCA). Distance redshift data from supernovae and baryon acoustic oscillations (BAO) along with WMAP7 distance priors are used to put…
For the first time, we reconstruct the dark energy equation of the state parameter $w$ from the combination of background and perturbation observations, specifically combining the Hubble parameter data from cosmic chronometer observations…
A model-independent reconstruction of the cosmic expansion rate is essential to a robust analysis of cosmological observations. Our goal is to demonstrate that current data are able to provide reasonable constraints on the behavior of the…