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Register a new userConfronting Dark Energy Models with Astrophysical Data: Non-Equilibrium vs. Conventional Cosmologies
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We discuss fits of cosmological dark energy models to the available data on high-redshift supernovae. We consider a conventional model with Cold Dark Matter and a cosmological constant (LambdaCDM), a model invoking super-horizon perturbations (SHCDM) and models based on Liouville strings in which dark energy is provided by a rolling dilaton field (Q-cosmology). We show that a complete treatment of Q-cosmology requires a careful discussion of non-equilibrium situations (off-shell effects). The two main high-redshift supernova data sets give compatible constraints on LambdaCDM and the other models. We recover the well-known result that LambdaCDM fits very well the combined supernova data sets, as does the super-horizon model. We discuss the model-dependent off-shell corrections to the Q-cosmology model that are relevant to the supernova data, and show that this model fits the data equally well. This analysis could be extended to other aspects of cosmological phenomenology, in particular to the CMB and Baryon Acoustic Oscillations, which have so far been treated using on-shell models.
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Non-critical string cosmologies may be viewed as the analogue of off-equilibrium models arising within string theory as a result of a cosmically catastrophic event in the early Universe. Such models entail relaxing-to-zero dark energies provided by a rolling dilaton field at late times. We discuss fits of such non-critical models to high-redshift supernovae data, including the recent ones by HST and ESSENCE and compare the results with those of a conventional model with Cold Dark Matter and a cosmological constant and a model invoking super-horizon perturbations.
The aim of this paper is to answer the following two questions: (1) Given cosmological observations of the expansion history and linear perturbations in a range of redshifts and scales as precise as is required, which of the properties of dark energy could actually be reconstructed without imposing any parameterization? (2) Are these observables sufficient to rule out not just a particular dark energy model, but the entire general class of viable models comprising a single scalar field? This paper bears both good and bad news. On one hand, we find that the goal of reconstructing dark energy models is fundamentally limited by the unobservability of the present values of the matter density Omega_m0, the perturbation normalization sigma_8 as well as the present matter power spectrum. On the other, we find that, under certain conditions, cosmological observations can nonetheless rule out the entire class of the most general single scalar-field models, i.e. those based on the Horndeski Lagrangian.
We study the performance of the latest $H(z)$ data in constraining the cosmological parameters of different cosmological models, including that of Chevalier-Polarski-Linder $w_{0}w_{1}$ parametrization. First, we introduce a statistical procedure in which the chi-square estimator is not affected by the value of the Hubble constant. As a result, we find that the $H(z)$ data do not rule out the possibility of either non-flat models or dynamical dark energy cosmological models. However, we verify that the time varying equation of state parameter $w(z)$ is not constrained by the current expansion data. Combining the $H(z)$ and the Type Ia supernova data we find that the $H(z)$/SNIa overall statistical analysis provides a substantial improvement of the cosmological constraints with respect to those of the $H(z)$ analysis. Moreover, the $w_{0}-w_{1}$ parameter space provided by the $H(z)$/SNIa joint analysis is in a very good agreement with that of Planck 2015, which confirms that the present analysis with the $H(z)$ and SNIa probes correctly reveals the expansion of the Universe as found by the team of Planck. Finally, we generate sets of Monte Carlo realizations in order to quantify the ability of the $H(z)$ data to provide strong constraints on the dark energy model parameters. The Monte Carlo approach shows significant improvement of the constraints, when increasing the sample to 100 $H(z)$ measurements. Such a goal can be achieved in the future, especially in the light of the next generation of surveys.
We use linear perturbation theory to study perturbations in dynamical dark energy models. We compare quintessence and tachyonic dark energy models with identical background evolution. We write the corresponding equations for different models in a form that makes it easier to see that the two models are very hard to distinguish in the linear regime, especially for models with $(1 + w) ll 1$. We use Cosmic Microwave Background data and parametric representations for the two models to illustrate that they cannot be distinguished for the same background evolution with existing observations. Further, we constrain tachyonic models with the Planck data. We do this analysis for exponential and inverse square potentials and find that the intrinsic parameters of the potentials remain very weakly constrained. In particular, this is true in the regime allowed by low redshift observations.
In this paper we explore possible extensions of Interacting Dark Energy cosmologies, where Dark Energy and Dark Matter interact non-gravitationally with one another. In particular, we focus on the neutrino sector, analyzing the effect of both neutrino masses and the effective number of neutrino species. We consider the Planck 2018 legacy release data combined with several other cosmological probes, finding no evidence for new physics in the dark radiation sector. The current neutrino constraints from cosmology should be therefore regarded as robust, as they are not strongly dependent on the dark sector physics, once all the available observations are combined. Namely, we find a total neutrino mass $M_ u<0.15$ eV and a number of effective relativistic degrees of freedom of $N_{rm eff}=3.03^{+0.33}_{-0.33}$, both at 95% CL, which are close to those obtained within the $Lambda$CDM cosmology, $M_ u<0.12$ eV and $N_{rm eff}=3.00^{+0.36}_{-0.35}$ for the same data combination.
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