Speaker
Description
This study breaks new ground by reconstructing how dark energy behaves over time, and we do it without tying ourselves to any specific cosmological model or parametrization. Instead, we rely on actual data to guide our analysis, making this the first study to combine the cosmological background and the growth observations to understand dark energy. We use information about the Hubble parameter from cosmic chronometer data and the growth rate from observations related to growth rates. Our method involves a posterior approach of Gaussian process regression analysis to figure out the Hubble parameter and growth rate, plus their changes with redshift, all at the same points in redshift. This study exclusively focuses on the flat Friedmann-Lemaître-Robertson-Walker (FLRW) metric and employs Newtonian perturbation theory on linear scales. The significant discovery of this study lies in the independence of the reconstruction of the dark energy equation of state from any prior knowledge of the present Hubble parameter and matter energy density parameter. From the reconstruction, we look at how the dark energy equation of state evolves between redshifts 0 and 1.5, finding a slight hint of dynamical behavior in dark energy although the evidence is not that strong. We also find a leaning towards non-phantom behavior over phantom behavior. Crucially, our findings are compared with the standard $\Lambda$CDM model. Intriguingly, we observe that the $\Lambda$CDM model nearly touches the lower boundary of the 1$\sigma$ confidence region for the reconstructed dark energy equation of state parameter in the redshift range $0.6 \leq z \leq 0.85$. However, it comfortably resides within the 1$\sigma$ confidence region across other redshift intervals. Consequently, the non-parametric, model-independent reconstruction of dark energy provides no compelling evidence to deviate from the $\Lambda$CDM model when considering cosmic chronometer and growth rate observations.
