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Journal ArticleDOI

Dynamics of dark energy

TLDR
In this article, the authors review the observational evidence for the current accelerated expansion of the universe and present a number of dark energy models in addition to the conventional cosmological constant, paying particular attention to scalar field models such as quintessence, K-essence and tachyon.
Abstract
We review in detail a number of approaches that have been adopted to try and explain the remarkable observation of our accelerating universe. In particular we discuss the arguments for and recent progress made towards understanding the nature of dark energy. We review the observational evidence for the current accelerated expansion of the universe and present a number of dark energy models in addition to the conventional cosmological constant, paying particular attention to scalar field models such as quintessence, K-essence, tachyon, phantom and dilatonic models. The importance of cosmological scaling solutions is emphasized when studying the dynamical system of scalar fields including coupled dark energy. We study the evolution of cosmological perturbations allowing us to confront them with the observation of the Cosmic Microwave Background and Large Scale Structure and demonstrate how it is possible in principle to reconstruct the equation of state of dark energy by also using Supernovae Ia observational data. We also discuss in detail the nature of tracking solutions in cosmology, particle physics and braneworld models of dark energy, the nature of possible future singularities, the effect of higher order curvature terms to avoid a Big Rip singularity, and approaches to modifying gravity which leads to a late-time accelerated expansion without recourse to a new form of dark energy.

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Dark Energy: a Brief Review

TL;DR: The problem of dark energy is briefly reviewed in both theoretical and observational aspects in this article, where dark energy scenarios are classified into symmetry, anthropic principle, tuning mechanism, modified gravity, quantum cosmology, holographic principle, back-reaction and phenomenological types.
Journal ArticleDOI

High-redshift cosmography: auxiliary variables versus Padé polynomials

TL;DR: In this article, the authors compared the convergence problem of the Taylor expansion with the Pade series and concluded that the (2,1) Pade approximation is statistically the optimal approach to explain low and high redshift data, together with the fifth-order $y_2$-parametrization.
Journal ArticleDOI

F(T) gravity and k-essence

TL;DR: In this paper, a thorough reconstruction analysis on the so-called $F(T)$ models with k-essence was performed, and conditions for the equivalence between these models and models with purely kinetic kessence were derived.
Journal ArticleDOI

Sandage-Loeb test for the new agegraphic and Ricci dark energy models

TL;DR: The Sandage-Loeb (SL) test is a unique method to explore dark energy at the "redshift desert" as mentioned in this paper by directly measuring the temporal variation of the redshift of quasar Lyman-α absorption lines.
Journal ArticleDOI

Neutron Interferometry constrains dark energy chameleon fields

TL;DR: In this paper, phase shift measurements for neutron matter waves in vacuum and in low pressure Helium using a method originally developed for neutron scattering length measurements in neutron interferometry were performed.
References
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Journal ArticleDOI

A new look at the statistical model identification

TL;DR: In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.
Journal ArticleDOI

Estimating the Dimension of a Model

TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.

Estimating the dimension of a model

TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
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