English

Designing Horndeski and the effective fluid approach

Cosmology and Nongalactic Astrophysics 2019-09-25 v2 General Relativity and Quantum Cosmology

Abstract

We present a family of designer Horndeski models, i.e. models that have a background exactly equal to that of the Λ\LambdaCDM model but perturbations given by the Horndeski theory. Then, we extend the effective fluid approach to Horndeski theories, providing simple analytic formulae for the equivalent dark energy effective fluid pressure, density and velocity. We implement the dark energy effective fluid formulae in our code EFCLASS, a modified version of the widely used Boltzmann solver CLASS, and compare the solution of the perturbation equations with those of the code hi_CLASS which already includes Horndeski models. We find that our simple modifications to the vanilla code are accurate to the level of 0.1%\sim 0.1\% with respect to the more complicated hi_CLASS code. Furthermore, we study the kinetic braiding model both on and off the attractor and we find that even though the full case has a proper Λ\LambdaCDM model limit for large nn, it is not appropriately smooth, thus causing the quasistatic approximation to break down. Finally, we focus on our designer model (HDES), which has both a smooth Λ\LambdaCDM limit and well-behaved perturbations, and we use it to perform Markov Chain Monte Carlo analyses to constrain its parameters with the latest cosmological data. We find that our HDES model can also alleviate the soft 2σ2\sigma tension between the growth data and Planck 18 due to a degeneracy between σ8\sigma_8 and one of its model parameters that indicates the deviation from the Λ\LambdaCDM model.

Keywords

Cite

@article{arxiv.1904.06294,
  title  = {Designing Horndeski and the effective fluid approach},
  author = {Rubén Arjona and Wilmar Cardona and Savvas Nesseris},
  journal= {arXiv preprint arXiv:1904.06294},
  year   = {2019}
}

Comments

31 pages, 9 figures, 5 tables, comments welcome. The codes used in the analysis of this paper can be found at https://members.ift.uam-csic.es/savvas.nesseris/efclass.html and at https://github.com/wilmarcardonac/EFCLASS