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(1) Presentation(s)


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Jeu. 23/01/2025 14:00 Salle des Séminaires, Bâtiment 21, Etage 4 (à confirmer)

Séminaire
CELERIER Marie-noelle (Observatoire Paris-Meudon)
An inhomogeneous cosmological solution of GR in the era of precision cosmology: the Szekeres model

(LUPM/Particules, Astroparticules, Cosmologie : Théorie)


Sommaire:

The LambdaCDM model, together with its linear and higher
order perturbations, constitute the roots of contemporary cosmology
allowing us to understand roughly the evolution and the geometry of
our Universe. The following thoughts inspire us to go further. First,
The Universe homogeneity and isotropy are only averaged properties
valid at scales which grow as structures with larger redshifts are
discovered. The advent of precision cosmology results in the emerging
or in the increasing of tensions, even of anomalies, owing to the
mismatch between predictions extrapolated since the early Universe and
observations of the late Universe realized with increased precision.
General Relativity offers a mean to solve these inconsistencies. The
Szekeres model is an exact solution of Einstein's equations,
inhomogeneous and without symmetry, able to represent the
matter/cosmological constant dominated region of our Universe, since
its gravitational source is a pressureless fluid and since the
cosmological constant can be incorporated in its equations. One among
its main advantages is that it includes the homogeneous and isotropic
Friedmann solution as a limiting case. It is therefore able to
reproduce naturally the homogeneity/inhomogeneity transition at the
scale where its defining functions reach the values of the standard
cosmological parameters. The most robust predictions of the early
Universe cosmology are therefore maintained. During this seminar, the
Szekeres solution will be presented together with its main properties
necessary for a cosmological use. The different observations which
will be of use to constrain the parameter-functions determining the
Szekeres model of Universe valid at a given precision will de
described and commented. The perspectives opened by neural networks to
complete this analysis of huge data sets will be discussed.


Pour plus d'informations, merci de contacter Teixeira E.