Bayesian analysis and constraints on kinematic models from union SNIa

Guimarães, Antonio C. C.; Cunha, J. V.; Lima, J. A. S.

doi:10.1088/1475-7516/2009/10/010

Cited by 62 publications

(46 citation statements)

References 45 publications

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“…Observational Data H(z), BAO, CMB, Galaxy Clusters , lookback time etc. to reconstruct q(z) or to constrain the transition redshift [11,12,13,14,15,16,17,18,19,20,21,22,23]. Lima et al (2012) have advocated many techniques that may constrain the transition redshift effectively in the future [24].…”

Section: Many Other Authors Have Used Different Data Sets Such As Gammentioning

confidence: 99%

Transition redshift: new constraints from parametric and nonparametric methods

Rani

Jain

Mahajan

et al. 2015

J. Cosmol. Astropart. Phys.

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In this paper, we use the cosmokinematics approach to study the accelerated expansion of the Universe. This is a model independent approach and depends only on the assumption that the Universe is homogeneous and isotropic and is described by the FRW metric. We parametrize the deceleration parameter, q(z), to constrain the transition redshift (z t ) at which the expansion of the Universe goes from a decelerating to an accelerating phase. We use three different parametrizations of q(z) namely, q I (z) = q 1 + q 2 z, q II (z) = q 3 + q 4 ln(1 + z) and q III (z) = 1 2 + q 5 (1+z) 2 . A joint analysis of the age of galaxies, strong lensing and supernovae Ia data indicates that the transition redshift is less than unity i.e. z t < 1. We also use a nonparametric approach (LOESS+SIMEX) to constrain z t . This too gives z t < 1 which is consistent with the value obtained by the parametric approach.

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Section: Many Other Authors Have Used Different Data Sets Such As Gammentioning

confidence: 99%

Transition redshift: new constraints from parametric and nonparametric methods

Rani

Jain

Mahajan

et al. 2015

J. Cosmol. Astropart. Phys.

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“…For using SNIa data, theoretical dark-energy model parameters are determined by minimizing the quantity [70][71][72][73][74][75][76][77] …”

Section: Type Ia Supernovaementioning

confidence: 99%

Combined constraints on modified Chaplygin gas model from cosmological observed data: Markov Chain Monte Carlo approach

et al. 2010

Gen Relativ Gravit

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We use the Markov Chain Monte Carlo method to investigate a global constraints on the modified Chaplygin gas (MCG) model as the unification of dark matter and dark energy from the latest observational data: the Union2 dataset of type supernovae Ia (SNIa), the observational Hubble data (OHD), the cluster X-ray gas mass fraction, the baryon acoustic oscillation (BAO), and the cosmic microwave background (CMB) data. In a flat universe, the constraint results for MCG model are, b h 2 = 0.02263 +0.00184 −0.00162 (1σ ) +0.00213 −0.00195 (2σ ), B s = 0.7788 +0.0736 −0.0723 (1σ ) +0.0918 −0.0904 (2σ ), α = 0.1079 +0.3397 −0.2539 (1σ ) +0.4678 −0.2911 (2σ ), B = 0.00189 +0.00583 −0.00756 (1σ ) +0.00660 −0.00915 (2σ ), and H 0 = 70.711 +4.188 −3.142 (1σ ) +5.281 −4.149 (2σ ).Keywords Modified Chaplygin gas (MCG) · Unification of dark matter and dark energy

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“…Cosmic constraint from SNIa observation can be determined by calculating [93][94][95][96][97][98][99][100][101][102][103] …”

Section: A3 Sniamentioning

confidence: 99%

Reduced modified Chaplygin gas cosmology

Geng

et al. 2015

J. High Energ. Phys.

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Abstract:In this paper, we study cosmologies containing the reduced modified Chaplygin gas (RMCG) fluid which is reduced from the modified Chaplygin gas p = Aρ − Bρ −α for the value of α = −1/2. In this special case, dark cosmological models can be realized for different values of model parameter A. We investigate the viabilities of these dark cosmological models by discussing the evolutions of cosmological quantities and using the currently available cosmic observations. It is shown that the special RMCG model (A = 0 or A = 1) which unifies the dark matter and dark energy should be abandoned. For A = 1/3, RMCG which unifies the dark energy and dark radiation is the favorite model according to the objective Akaike information criteria. In the case of A < 0, RMCG can achieve the features of the dynamical quintessence and phantom models, where the evolution of the universe is not sensitive to the variation of model parameters.

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Bayesian analysis and constraints on kinematic models from union SNIa

Cited by 62 publications

References 45 publications

Transition redshift: new constraints from parametric and nonparametric methods

Transition redshift: new constraints from parametric and nonparametric methods

Combined constraints on modified Chaplygin gas model from cosmological observed data: Markov Chain Monte Carlo approach

Reduced modified Chaplygin gas cosmology

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