Testing the Void against Cosmological data: fitting CMB, BAO, SN and H0
Tirthabir Biswas, Alessio Notari, Wessel Valkenburg

TL;DR
This paper explores a large-scale Void model as an alternative to Dark Energy for explaining cosmological observations, incorporating curvature and detailed effects, and demonstrating its potential to fit data nearly as well as standard models.
Contribution
It introduces an improved Void model with curvature and detailed profiles, providing analytical tools and a numerical module for comprehensive parameter analysis.
Findings
Void model with curvature fits cosmological data nearly as well as Dark Energy models.
An off-center observer in the Void can explain large bulk flow anomalies.
The model aligns with CMB dipole measurements for a specific observer position.
Abstract
In this paper, instead of invoking Dark Energy, we try and fit various cosmological observations with a large Gpc scale under-dense region (Void) which is modeled by a Lemaitre-Tolman-Bondi metric that at large distances becomes a homogeneous FLRW metric. We improve on previous analyses by allowing for nonzero overall curvature, accurately computing the distance to the last-scattering surface and the observed scale of the Baryon Acoustic peaks, and investigating important effects that could arise from having nontrivial Void density profiles. We mainly focus on the WMAP 7-yr data (TT and TE), Supernova data (SDSS SN), Hubble constant measurements (HST) and Baryon Acoustic Oscillation data (SDSS and LRG). We find that the inclusion of a nonzero overall curvature drastically improves the goodness of fit of the Void model, bringing it very close to that of a homogeneous universe containing…
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