scholarly journals Elucidating cosmological model dependence with $$H_0$$

2021 ◽  
Vol 81 (10) ◽  
Author(s):  
Eoin Ó Colgáin ◽  
M. M. Sheikh-Jabbari
Keyword(s):  
Dark Energy ◽  
Cosmological Model ◽  
Hubble Constant ◽  
Data Reconstruction ◽  
Energy Models ◽  
Model Independence ◽  
Model Independent ◽  
Flrw Cosmology ◽  
Mean Function ◽  
Dynamical Dark Energy

AbstractWe observe that the errors on the Hubble constant $$H_0$$ H 0 , a universal parameter in any FLRW cosmology, can be larger in specific cosmological models than Gaussian processes (GP) data reconstruction. We comment on the prior mean function and trace the smaller GP errors to stronger correlations, which we show precludes all well studied dynamical dark energy models. We also briefly illustrate cosmographic expansions as another model independent cosmological reconstruction. Our analysis suggests that “cosmological model independence”, especially in the statement of Hubble tension, has become a misnomer.

scholarly journals Decaying Dark Energy in Light of the Latest Cosmological Dataset

Symmetry ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 372 ◽  
Author(s):  
Ivan de Martino
Keyword(s):  
Dark Energy ◽  
Cosmic Microwave Background ◽  
Parameter Space ◽  
Hubble Constant ◽  
Two Dimensions ◽  
Matter Density ◽  
Microwave Background ◽  
Energy Models ◽  
Cosmic Microwave Background Temperature ◽  
Background Temperature

Decaying Dark Energy models modify the background evolution of the most common observables, such as the Hubble function, the luminosity distance and the Cosmic Microwave Background temperature–redshift scaling relation. We use the most recent observationally-determined datasets, including Supernovae Type Ia and Gamma Ray Bursts data, along with H ( z ) and Cosmic Microwave Background temperature versus z data and the reduced Cosmic Microwave Background parameters, to improve the previous constraints on these models. We perform a Monte Carlo Markov Chain analysis to constrain the parameter space, on the basis of two distinct methods. In view of the first method, the Hubble constant and the matter density are left to vary freely. In this case, our results are compatible with previous analyses associated with decaying Dark Energy models, as well as with the most recent description of the cosmological background. In view of the second method, we set the Hubble constant and the matter density to their best fit values obtained by the Planck satellite, reducing the parameter space to two dimensions, and improving the existent constraints on the model’s parameters. Our results suggest that the accelerated expansion of the Universe is well described by the cosmological constant, and we argue that forthcoming observations will play a determinant role to constrain/rule out decaying Dark Energy.

scholarly journals Testing for dynamical dark energy models with redshift-space distortions

2013 ◽  
Vol 2013 (01) ◽  
pp. 030-030 ◽  
Author(s):  
Shinji Tsujikawa ◽  
Antonio De Felice ◽  
Jailson Alcaniz
Keyword(s):  
Dark Energy ◽  
Energy Models ◽  
Dynamical Dark Energy

scholarly journals Roles of Dark Energy Perturbations in Dynamical Dark Energy Models: Can We Ignore Them?

2009 ◽  
Vol 103 (15) ◽  
Author(s):  
Chan-Gyung Park ◽  
Jai-chan Hwang ◽  
Jae-heon Lee ◽  
Hyerim Noh
Keyword(s):  
Dark Energy ◽  
Energy Models ◽  
Dynamical Dark Energy

scholarly journals Measurements of $$H_0$$ and reconstruction of the dark energy properties from a model-independent joint analysis

2021 ◽  
Vol 81 (2) ◽  
Author(s):  
Alexander Bonilla ◽  
Suresh Kumar ◽  
Rafael C. Nunes
Keyword(s):  
Dark Energy ◽  
Sound Speed ◽  
Hubble Constant ◽  
State Parameter ◽  
Independent Method ◽  
Joint Analysis ◽  
Acoustic Oscillations ◽  
Type Ia ◽  
Model Independent ◽  
Supernova Type Ia

AbstractGaussian processes (GP) provide an elegant and model-independent method for extracting cosmological information from the observational data. In this work, we employ GP to perform a joint analysis by using the geometrical cosmological probes such as Supernova Type Ia (SN), Cosmic chronometers (CC), Baryon Acoustic Oscillations (BAO), and the H0LiCOW lenses sample to constrain the Hubble constant $$H_0$$ H 0 , and reconstruct some properties of dark energy (DE), viz., the equation of state parameter w, the sound speed of DE perturbations $$c^2_s$$ c s 2 , and the ratio of DE density evolution $$X = \rho _\mathrm{de}/\rho _\mathrm{de,0}$$ X = ρ de / ρ de , 0 . From the joint analysis SN+CC+BAO+H0LiCOW, we find that $$H_0$$ H 0 is constrained at 1.1% precision with $$H_0 = 73.78 \pm 0.84\ \hbox {km}\ \hbox {s}^{-1}\,\hbox {Mpc}^{-1}$$ H 0 = 73.78 ± 0.84 km s - 1 Mpc - 1 , which is in agreement with SH0ES and H0LiCOW estimates, but in $$\sim 6.2 \sigma $$ ∼ 6.2 σ tension with the current CMB measurements of $$H_0$$ H 0 . With regard to the DE parameters, we find $$c^2_s < 0$$ c s 2 < 0 at $$\sim 2 \sigma $$ ∼ 2 σ at high z, and the possibility of X to become negative for $$z > 1.5$$ z > 1.5 . We compare our results with the ones obtained in the literature, and discuss the consequences of our main results on the DE theoretical framework.

scholarly journals Constraints on Dynamical Dark Energy Models from the Abundance of Massive Galaxies at High Redshifts

2020 ◽  
Vol 900 (2) ◽  
pp. 108
Author(s):  
N. Menci ◽  
A. Grazian ◽  
M. Castellano ◽  
P. Santini ◽  
E. Giallongo ◽  
...  
Keyword(s):  
Dark Energy ◽  
Massive Galaxies ◽  
Energy Models ◽  
Dynamical Dark Energy

scholarly journals Interplay between Swampland and Bayesian Machine Learning in constraining cosmological models

2021 ◽  
Vol 81 (4) ◽  
Author(s):  
Emilio Elizalde ◽  
Martiros Khurshudyan
Keyword(s):  
Machine Learning ◽  
Dark Energy ◽  
High Redshift ◽  
Hubble Constant ◽  
State Parameter ◽  
Energy Models ◽  
Important Message ◽  
Phantom Dark Energy ◽  
Probabilistic Machine Learning ◽  
Bayesian Machine Learning

AbstractConstraints on a dark energy dominated Universe are obtained from an interplay Bayesian (Probabilistic) Machine Learning and string Swampland criteria. Unlike in previous studies, here, the field traverse itself has been used to constraint the theory and reveal its connection to the Swampland approach. The field traverse based Bayesian (Probabilistic) Learning approach is applied to two toy models. A parametrization of the Hubble constant is used for the first model, while a parametrization of the deceleration parameter is considered for the second one. The results obtained here allow to estimate how the high-redshift behavior of the Universe will affect the low-redshift one. Moreover, the adopted approach may highlight, in the future, the borders of the Swampland for the low-redshift Universe and help to develop new string-theory motivated dark energy models. The most important message from our study is a hint that the string Swampland criteria might be in tension with recent observations indicating that phantom dark energy cannot be in the Swampland. Finally, another interesting result obtained in our study is a spontaneous sign switch in the dark energy equation of state parameter when the field traverses are in the $$z\in [0,5]$$ z ∈ [ 0 , 5 ] redshift range, a remarkable phenomenon requiring further analysis.

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