Related papers: Information-theoretic model selection applied to s…
In this work, we studied four types of cosmological models with different mechanisms driving the accelerated expansion of the universe, include Braneworld models, Chaplygin Gas models, Emergent Dark Energy models, and cosmological torsion…
The first cosmological results from the ESSENCE supernova survey (Wood-Vasey et al. 2007) are extended to a wider range of cosmological models including dynamical dark energy and non-standard cosmological models. We fold in a greater number…
We explores the Pantheon+SH0ES dataset to identify patterns that can discriminate between different cosmological models. We focus on determining whether the behaviour of dark energy is consistent with the standard $\Lambda$CDM model or…
We use recently observed data: the 192 ESSENCE type Ia supernovae (SNe Ia), the 182 Gold SNe Ia, the 3-year WMAP, the SDSS baryon acoustic peak, the X-ray gas mass fraction in clusters and the observational $H(z)$ data to constrain models…
The supernova type Ia observational data are fitted using a model with cold dark matter and the Chaplygin gas. The Chaplygin gas, which is characterized by a negative pressure varying with the inverse of density, represents in this model…
So far large and different data sets revealed the accelerated expansion rate of the Universe, which is usually explained in terms of dark energy. The nature of dark energy is not yet known, and several models have been introduced: a non…
The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior…
The main goal of the next generation of weak lensing probes is to constrain cosmological parameters by measuring the mass distribution and geometry of the low redshift Universe and thus to test the concordance model of cosmology. A future…
A huge amount of good quality astrophysical data converges towards the picture of a spatially flat universe undergoing the today observed phase of accelerated expansion. This new observational trend is commonly addressed as Precision…
The main aim of this paper is to perform a model comparison for some reconstructions of the key properties that describe the dark energy of the Universe i.e. energy density and the equation of state (EoS). We carry out this process by using…
We use some of the recently released observational data to test the viability of two classes of minimally coupled scalar field models of quintessence with exponential potentials for which exact solutions of the Einstein equations are known.…
Type Ia supernovae have provided fundamental observational data in the discovery of the late acceleration of the expansion of the Universe in cosmology. However, this analysis has relied on the assumption of a Gaussian distribution for the…
We study the effect of a phenomenological parameterized quintessence model on low, intermediate and high redshift observations. At low and intermediate redshifts, we use the Gold sample of supernova Type Ia (SNIa) data and recently observed…
The DESI collaboration have recently analyzed their first year of data, finding a preference for thawing dark energy scenarios when using parameterized equations of state for dark energy. We investigate whether this preference persists when…
We derive two field theory models of interacting dark energy, one in which dark energy is associated with the quintessence and another in which it is associated with the tachyon. In both, instead of choosing arbitrarily the potential of…
We use the Type Ia Supernova gold sample to constrain the parameters of dark energy models namely the Cardassian, Dvali-Turner (DT) and generalized Chaplygin gas (GCG) models. In our best fit analysis for these dark energy proposals we…
Dark energy can be investigated in two complementary ways, by considering either general parameterizations or physically well-defined models. Following the second route, we explore the constraints on quintessence models where the…
The semiparametric estimation approach, which includes inverse-probability-weighted and doubly robust estimation using propensity scores, is a standard tool in causal inference, and it is rapidly being extended in various directions. On the…
We emphasize that it is possible to improve the principle of unbiased risk estimation for model selection by addressing excess risk deviations in the design of penalization procedures. Indeed, we propose a modification of Akaike's…
Model or variable selection is usually achieved through ranking models according to the increasing order of preference. One of methods is applying Kullback-Leibler distance or relative entropy as a selection criterion. Yet that will raise…