Yazar "Oztas, Ahmet Mecit" seçeneğine göre listele

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    Cosmic future of universe inferred from the horizon behaviours in ? ? a-2, ? ? H2, ? ? ? cosmological constant models
    (Indian Acad Sciences, 2021) Oztas, Ahmet Mecit; Dil, Emre; Tufekci, Onur
    To investigate the cosmic future of the universe, first, we obtain the particle and event horizons, and their evolution in time for three well-known varying cosmological constant models. We investigate the implications of these varying cosmological constant models on the particle and event horizons, and their time evolution during the universe history and future. We study the behaviours around the origin and at the far future of the universe for all cases. Finally, we obtained the general behaviours of the horizons and time evolution functions with respect to the general scale factor a for each of the three cases of varying cosmological constant. The results show that for two of our three cases, a big bounce scenario is inevitable for the universe starting from the big bang and ending up with a bouncing re-collapse to its initial state.
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    Entropic source of cosmological constant and implications: Generalization to higher dimensions
    (Elsevier, 2021) Oztas, Ahmet Mecit; Dil, Emre
    Considering the entropic force on the holographic Hubble horizon of the universe which carries a Bekenstein-Hawking entropy and temperature leads to the entropic force cosmology, and it assumes that the entropic force is responsible from the increase of entropy and accelerated expansion of the universe as a source of cosmological constant. This assumption naturally solves the cosmological constant problem with the variable nature of the entropic pressure on the Hubble parameter. We investigate the implications of entropic force cosmology by obtaining the density parameters and the distance measures. Then, we generalize the model into higher dimensional universes in order to investigate the early period accelerations and density values of universe contents. After obtaining the density parameters, we find the luminosity distance and modulus equations. By comparing the luminosity distance values of standard.CDM and our model, we infer that the considered model presents a faster acceleration in the early periods of the universe implied from larger luminosity distances of the model for higher redshift values, which is completely supported by the inflationary paradigm. In addition, it is found that the luminosity distance becomes larger in higher dimensions for higher redshifts implying the early acceleration is larger. Moreover, from the distance modulus comparison of the model and the observational Gold Data, we find the considered model and its higher dimensional generalization are in accordance with the data, also the universe starts from higher dimensions with higher dark energy densities to lower compactified dimensions with lower dark energy densities, while the matter density increases. (C) 2021 Elsevier B.V. All rights reserved.
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    Testing adiabatic expansion of polytropic universe model with SNe Ia data
    (Iop Publishing Ltd, 2020) Dil, Emre; Oztas, Ahmet Mecit; Dil, Elif
    In order to obtain a better fit for the observational data, various cosmological models have been developed in the literature. For this purpose, we propose an adiabatic expansion of the Universe with a polytropic fluid matter-radiation content and a varying cosmological constant. Basic motivation of this study basically differs from the previous models because our model does not neglect the pressure of the matter content of the Universe. We present the details of our new derivations by obtaining the polytropic matter density and luminosity distances. After constructing the model, two large collections of observational data of supernovae type Ia (SNe Ia) are conducted to diagnose the model. Examining the fitness of our new models of a polytropic universe with the observational data, we find a significant influence of polytropic matter on the cosmological parameters of the expanding universe. We find that our flat constant ? model and varying ? model describes the SNe Ia data significantly better than the other models including the standard model for Gold Data and Union2.1 Data, respectively.
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    The varying cosmological constant models tested with Supernovae Type Ia and HII Galaxy Data
    (Elsevier, 2019) Dil, Emre; Oztas, Ahmet Mecit; Dil, Elif
    We have recently proposed a varying cosmological constant model for which we now test our proposal with the use of two large collections of observational Gold data of supernovae Type Ia (SNe Ia) and HII Galaxies (HIIGx) data as standard candles for constructing the Hubble diagram at redshifts beyond the current reach of Type Ia supernovae. For this aim, we obtain the luminosity distances from the proposed varying. models which have been briefly summarized. Using these luminosity distance values, we present the modulus values from which we test the accuracy of the models by probing the Gold data and HII Data confirming that the relation between the emission-line luminosity and ionized-gas velocity dispersion is a reliable modulus indicator. From the chi(2) minimization and the maximization of the likelihood function, we optimize the cosmological parameters in each cosmological model. While the best model is obtained as the Lambda CDM for Gold data, our model with a Lambda depending on the matter density rho is obtained as the best model for HII data. Moreover, the statistical tools, such as the Akaike (AIC), and Bayes (BIC) Information Criteria favor the standard Lambda CDM model over our Lambda proportional to rho model with a relative BIC of 372/383 for Gold data, but same criteria favor our Lambda proportional to rho model over Lambda CDM with 1055/1120 for HII Galaxy data. We also test the accuracy of our models by comparison of the theoretical and observational modulus values for both data, and illustrate the Hubble diagrams for all varying Lambda models showing a worse fit with respect to Lambda CDM model for Gold Data, and a best fit with Lambda proportional to rho model for HII Data, through given statistical confidence tables. (C) 2019 Elsevier B.V. All rights reserved.