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Register a new userGaussian processes reconstruction of dark energy from observational data
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In the present paper, we investigate the dark energy equation of state using the Gaussian processes analysis method, without confining a particular parametrization. The reconstruction is carried out by adopting the background data including supernova and Hubble parameter, and perturbation data from the growth rate. It suggests that the background and perturbation data both present a hint of dynamical dark energy. However, the perturbation data have a more promising potential to distinguish non-evolution dark energy including the cosmological constant model. We also test the influence of some parameters on the reconstruction. We find that the matter density parameter $Omega_{m0}$ has a slight effect on the background data reconstruction, but has a notable influence on the perturbation data reconstruction. While the Hubble constant presents a significant influence on the reconstruction from background data.
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Recent work has shown that modified gravitational wave (GW) propagation can be a powerful probe of dark energy and modified gravity, specific to GW observations. We use the technique of Gaussian processes, that allows the reconstruction of a function from the data without assuming any parametrization, to measurements of the GW luminosity distance from simulated joint GW-GRB detections, combined with measurements of the electromagnetic luminosity distance by simulated DES data. For the GW events we consider both a second-generation LIGO/Virgo/Kagra (HVLKI) network, and a third-generation detector such as the Einstein Telescope. We find that the HVLKI network at target sensitivity, with $O(15)$ neutron star binaries with electromagnetic counterpart, could already detect deviations from GR at a level predicted by some modified gravity models, and a third-generation detector such as ET would have a remarkable discovery potential. We discuss the complementarity of the Gaussian processes technique to the $(Xi_0,n)$ parametrization of modified GW propagation.
A non-parametric reconstruction of the deceleration parameter $q$ is carried out. The observational datasets are so chosen that they are model independent as much as possible. The present acceleration and the epoch at which the cosmic acceleration sets in is quite as expected, but beyond a certain redshift ($z sim 2$), a negative value of $q$ appears to be in the allowed region. A survey of existing literature is given and compared with the results obtained in the present work.
We focus on three scalar-field dark energy models (i.e., $phi$CDM models), which behave like cosmological trackers with potentials $V(phi)propto phi^{-alpha}$ (inverse power-law (IPL) model), $V(phi)propto coth^{alpha}{phi}$ (L-model) and $V(phi)propto cosh(alphaphi)$ (Oscillatory tracker model). The three $phi$CDM models, which reduce to the $Lambda$CDM model with the parameter $alpha to 0$, are investigated and compared with the recent observations of type Ia supernovae (SNe Ia), baryon acoustic oscillations (BAO) and cosmic microwave background radiation (CMB). The observational constraints from the combining sample (SNe Ia + BAO + CMB) indicate that none of the three $phi$CDM models exclude the $Lambda$CDM model at $68.3%$ confidence level, and a closed universe is strongly supported in the scenarios of the three $phi$CDM models (at 68.3% confidence level). Furthermore, we apply the Bayesian evidence to compare the $phi$CDM models and the $Lambda$CDM model with the analysis of the combining sample. The concordance $Lambda$CDM model is still the most supported one. In addition, among the three $phi$CDM models, the IPL model is the most competitive one, while the L-model/Oscillatory tacker model is moderately/strongly disfavored.
We reconstruct the Equation of State of Dark Energy (EoS) from current data using a non-parametric approach where, rather than assuming a specific time evolution of this function, we bin it in time. We treat the transition between the bins with two different methods, i.e. a smoothed step function and a Gaussian Process reconstruction, investigating whether or not the two approaches lead to compatible results. Additionally, we include in the reconstruction procedure a correlation between the values of the EoS at different times in the form of a theoretical prior that takes into account a set of viability and stability requirements that one can impose on models alternative to $Lambda$CDM. In such case, we necessarily specialize to broad, but specific classes of alternative models, i.e. Quintessence and Horndeski gravity. We use data coming from CMB, Supernovae and BAO surveys. We find an overall agreement between the different reconstruction methods used; with both approaches, we find a time dependence of the mean of the reconstruction, with different trends depending on the class of model studied. The constant EoS predicted by the $Lambda$CDM model falls anyway within the $1sigma$ bounds of our analysis.
The model-independent piecewise parametrizations (0-spline, linear-spline and cubic-spline) are used to estimate constraints of equation of state of dark energy ($w_{de}$) from current observational data (including SNIa, BAO and Hubble parameter) and the simulated future data. A combination of fitting results of $w_{de}$ from these three spline methods reveal essential properties of real equation of state $w_{de}$. It is shown that $w_{de}$ beyond redshift $zsim0.5$ is poorly constrained from current data, and the mock future $sim2300$ supernovae data give poor constraints of $w_{de}$ beyond $zsim1$. The fitting results also indicate that there might exist a rapid transition of $w_{de}$ around $zsim0.5$. The difference between three spline methods in reconstructing and constraining $w_{de}$ has also been discussed.
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