Related papers: Anisotropic cosmology using observational datasets…
We consider a varieties of quintessence scalar field models in a homogeneous and isotropic geometry of the universe with zero spatial curvature aiming to provide stringent constraints using a series of cosmological data sets, namely, the…
Markov-chain Monte Carlo sampling has become a standard technique for exploring the posterior distribution of cosmological parameters constrained by observations of CMB anisotropies. Given an infinite amount of time, any MCMC sampler will…
In this paper, we explore an axially symmetric Bianchi type-I model of the universe with bulk viscous fluid as a source of gravitational field under the framework of Einstein's field equations by assuming barotropic bulk viscous pressure as…
We use recent 36 observational Hubble data (OHD) in the redshift range $0.07\leq z\leq 2.36$, latest \textgravedbl joint light curves\textacutedbl (JLA) sample, comprised of 740 type Ia supernovae (SNIa) in the redshift range $0.01\leq z…
We present a neural net algorithm for parameter estimation in the context of large cosmological data sets. Cosmological data sets present a particular challenge to pattern-recognition algorithms since the input patterns (galaxy redshift…
We use observations of cosmic microwave background anisotropies, supernova luminosities and the baryon acoustic oscillation signal in the galaxy distribution to constrain the cosmological parameters in a simple interacting dark energy model…
The possibility of determining cosmological parameters on the basis of a wide set of observational data including the Abell-ACO cluster power spectrum and mass function, peculiar velocities of galaxies, the distribution of Ly-$\alpha$…
We study the Bianchi-I cosmological model motivated by signals of statistical isotropy violation seen in cosmic microwave background (CMB) observations and others. To that end, we consider various kinds of anisotropic matter that source…
In this paper, a parametrization describing the kinematical state of the universe via cosmographic approach is considered, where the minimum input is the assumption of the cosmological principle, i.e. the Friedmann-Robertson-Walker metric.…
Combining the latest Planck, Wilkinson Microwave Anisotropy Probe (WMAP), and baryon acoustic oscillation (BAO) data, we exploit the recent cosmic microwave background (CMB) B-mode power spectra data released by the BICEP2 collaboration to…
We have extended the analysis of Jaffe et al. to a complete Markov chain Monte Carlo (MCMC) study of the Bianchi type ${\rm VII_h}$ models including a dark energy density, using 1-year and 3-year Wilkinson Microwave Anisotropy Probe (WMAP)…
The future 21 cm intensity mapping observations constitute a promising way to trace the matter distribution of the Universe and probe cosmology. Here we assess its capability for cosmological constraints using as a case study the BINGO…
We report an investigation of cosmological parameters based on the measurements of anisotropy in the cosmic microwave background radiation (CMB) made by ACBAR. We use the ACBAR data in concert with other recent CMB measurements to derive…
We present a Markov Chain Monte Carlo (MCMC)-based parameter estimation package, CosmoReionMC, to jointly constrain cosmological parameters of the $\Lambda$CDM model and the astrophysical parameters related to hydrogen reionization. The…
Most parameter constraints obtained from cosmic microwave background (CMB) anisotropy data are based on power estimates and rely on approximate likelihood functions; computational difficulties generally preclude an exact analysis based on…
In the near future, observations of the cosmic microwave background (CMB) anisotropies will provide accurate determinations of many fundamental cosmological parameters. In this paper, we analyse degeneracies among cosmological parameters to…
A new parametrization of the Hubble parameter is proposed to explore the issue of the cosmological landscape. The constraints on model parameters are derived through the Markov Chain Monte Carlo (MCMC) method by employing a comprehensive…
The cosmological principle is a cornerstone of the standard cosmological model. However, recent observations suggest potential deviations from this assumption, hinting at a small anisotropic expansion. Such an expansion can arise from…
We present a neural net algorithm for parameter estimation in the context of large cosmological data sets. Cosmological data sets present a particular challenge to pattern-recognition algorithms since the input patterns (galaxy redshift…
In this paper we study an anisotropic model generated from a particular Bianchi type-III metric, which is a generalization of G\"odel's metric and an exact solution of Einstein's field equations. We analyse type Ia supernova data, namely…