Banca de DEFESA: CARLOS EDUARDO VIANA DE FREITAS

Applying model selection criteria in the Bayesian context to compare and select cosmological models through SNe Ia data.

 Universe, type Ia supernovae, statistical methods, cosmological models.

We find ourselves in a Universe that is intrinsically composed of two dominant components, dark matter and dark energy, and the mathematical model that best describes it currently is the ΛCDM paradigm. Knowing that there are variations of this scenario in the literature, such as XCDM and CPL, this work focuses on comparing these models with the current model for different cases of curvature (k = 0 and k ≠ 0) seeking to restrict the cosmological parameters and categorize the models through of statistical methods, such as the χ²_min  and the model selection criteria. In order to do this, we will use two type Ia supernova samples, one from the Supernova Cosmology Project (UNION 2.1) and the other from PANTHEON 2018. Each set of data was contrasted by cosmological models, verifying the behavior that they developed to the statistical methods and, consequently, it was selection criteria were used to infer the model that best fits the observed data. For the first sample mentioned above, both criteria, AIC and BIC, favored the ΛCDM_{k = 0} model. For the last sample, the XCDM_{k = 0} model was favored according to the AIC criterion, while for the BIC criterion it was ΛCDM_{k = 0}.