Observables and unobservables in dark energy cosmologies
Luca Amendola (ITP, U. Heidelberg), Martin Kunz (Geneva U.), Mariele, Motta (ITP, U. Heidelberg, Campinas State U.), Ippocratis D. Saltas, (Nottingham U.), Ignacy Sawicki (ITP, U. Heidelberg)

TL;DR
This paper investigates the extent to which dark energy properties can be reconstructed from cosmological observations and whether such data can exclude entire classes of scalar-field dark energy models, highlighting fundamental limitations and potential for model exclusion.
Contribution
It demonstrates the fundamental observational limitations in reconstructing dark energy parameters and identifies conditions under which entire classes of scalar-field models can be ruled out.
Findings
Reconstruction of dark energy is limited by unobservable parameters like Omega_m0 and sigma_8.
Cosmological observations can exclude the entire class of Horndeski scalar-field models under certain conditions.
Fundamental limits exist in reconstructing dark energy properties without parameterization.
Abstract
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
