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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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Citations
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Journal ArticleDOI

Constraints on cosmological parameters in power-law cosmology

TL;DR: In this paper, the authors examined observational constraints on the power law cosmology; essentially dependent on two parameters H0 (Hubble constant) and q (deceleration parameter).
Journal ArticleDOI

Equation of state for dark energy in $f(T)$ gravity

TL;DR: In this article, the cosmological evolution of the equation of state for dark energy in the exponential and logarithmic as well as their combination $f(T)$ theories was studied.
Journal ArticleDOI

Dark energy from a phantom field near a local potential minimum

TL;DR: In this article, the authors derived a general expression for w as a function of the scale factor and showed that the dynamics of the field depend on the value of ( 1 / V ) ( d 2 V / d ϕ 2 ) near the minimum.
Journal ArticleDOI

Observational Probes of Cosmic Acceleration

TL;DR: In this paper, the authors present extensive forecasts for constraints on the dark energy equation of state and parameterized deviations from GR, achievable with Stage III and Stage IV experimental programs that incorporate supernovae, BAO, weak lensing, and CMB data.
Journal ArticleDOI

Observational constraints on dark matter-dark energy scattering cross section

TL;DR: In this article, the authors report precise and robust observational constraints on the dark matter-dark energy scattering cross section, using the latest data from cosmic microwave background (CMB) Planck temperature and polarization, baryon acoustic oscillations (BAO) measurements and weak gravitational lensing data from Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS).
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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