scholarly journals Type Ia supernovae from dark matter core collapse

2019 ◽  
Vol 100 (3) ◽  
Author(s):  
Ryan Janish ◽  
Vijay Narayan ◽  
Paul Riggins
2007 ◽  
Vol 16 (10) ◽  
pp. 1573-1579
Author(s):  
CHENGWU ZHANG ◽  
LIXIN XU ◽  
YONGLI PING ◽  
HONGYA LIU

We use a parameterized equation of state (EOS) of dark energy to a 5D Ricci-flat cosmological solution and suppose the universe contains two major components: dark matter and dark energy. Using the recent observational datasets: the latest 182 type Ia Supernovae Gold data, the three-year WMAP CMB shift parameter and the SDSS baryon acoustic peak, we obtain the best fit values of the EOS and two major components' evolution. We find that the best fit EOS crosses -1 in the near past where z ≃ 0.07, the present best fit value of wx(0) < -1 and for this model, the universe experiences the acceleration at about z ≃ 0.5.


2007 ◽  
Vol 22 (31) ◽  
pp. 5735-5746
Author(s):  
Nathalie Palanque-Delabrouille

We present a general overview of recent results in the searches for dark matter and dark energy. We discuss the observation of the collision between two clusters of galaxies, and the impact this has on the relevance of dark matter. We then present the final results from microlensing experiments, which aimed at detecting dark baryonic objects in the halo of our galaxy, and the status of direct searches for WIMPs. We present the evidence for dark energy which initially comes from experiments dedicated to the study of distant type Ia supernovae. The measure of the baryon acoustic oscillation, an independent probe of the evolution of our universe that has recently brought interesting constraints, is finally described.


2004 ◽  
Vol 13 (04) ◽  
pp. 669-693 ◽  
Author(s):  
R. COLISTETE ◽  
J. C. FABRIS ◽  
S. V. B. GONÇALVES ◽  
P. E. DE SOUZA

The type Ia supernovae observational data are used to estimate the parameters of a cosmological model with cold dark matter and the Chaplygin gas. This exotic gas, which is characterized by a negative pressure varying with the inverse of density, represents in this model the dark energy responsible for the acceleration of the Universe. The Chaplygin gas model depends essentially on four parameters: the Hubble constant, the velocity of the sound of the Chaplygin gas, the curvature of the Universe and the fraction density of the Chaplygin gas and the cold dark matter. The Bayesian parameter estimation yields [Formula: see text] and [Formula: see text]. These and other results indicate that a Universe completely dominated by the Chaplygin gas is favoured, what reinforces the idea that the Chaplygin gas may unify the description for dark matter and dark energy, at least as the type Ia supernovae data are concerned. A closed and accelerating Universe is also favoured. The Bayesian statistics indicates that the Chaplygin gas model is more likely than the standard cosmological constant (ΛCDM) model at 55.3% confidence level when an integration on all free parameters is performed. Assuming the spatially flat curvature, this percentage mounts to 65.3%. On the other hand, if the density of dark matter is fixed at zero value, the Chaplygin gas model becomes more preferred than the ΛCDM model at 91.8% confidence level. Finally, the hypothesis of flat Universe and baryonic matter (Ωb0=0.04) implies a Chaplygin gas model preferred over the ΛCDM at a confidence level of 99.4%.


2015 ◽  
Vol 811 (2) ◽  
pp. L25 ◽  
Author(s):  
A. Simionescu ◽  
N. Werner ◽  
O. Urban ◽  
S. W. Allen ◽  
Y. Ichinohe ◽  
...  

2011 ◽  
Vol 7 (S281) ◽  
pp. 32-33
Author(s):  
M. L. Pumo ◽  
L. Zampieri

AbstractUsing our new general-relativistic, radiation hydrodynamics, Lagrangian code, we computed a rather extended grid of hydrogen-rich core-collapse supernovae (CC-SNe) models and explored the potentials of their “standardization” as distance indicators. We discuss the properties of some calibrations previously reported in the literature, and present new correlations based on the behavior of the light curve that can be employed for calibrating hydrogen-rich CC-SNe using only photometric data.


2015 ◽  
Vol 812 (2) ◽  
pp. 110 ◽  
Author(s):  
S.-C. Leung ◽  
M.-C. Chu ◽  
L.-M. Lin

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