# Reconstruction of the Dark Energy equation of state from latest data:   the impact of theoretical priors

**Authors:** Francesca Gerardi, Matteo Martinelli, Alessandra Silvestri

arXiv: 1902.09423 · 2019-08-23

## TL;DR

This paper reconstructs the Dark Energy equation of state using non-parametric methods and theoretical priors, analyzing data from CMB, Supernovae, and BAO to explore its time dependence and model compatibility.

## Contribution

It introduces a non-parametric reconstruction of the EoS with theoretical priors for viability and stability, comparing two methods and applying to broad classes of models.

## Key findings

- Reconstruction methods yield consistent results.
- EoS shows time dependence with model-dependent trends.
- ΛCDM's constant EoS is within 1σ bounds.

## Abstract

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 $1\sigma$ bounds of our analysis.

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/1902.09423/full.md

## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/1902.09423/full.md

## References

65 references — full list in the complete paper: https://tomesphere.com/paper/1902.09423/full.md

---
Source: https://tomesphere.com/paper/1902.09423