Bayesian analysis of CCDM models

Autor(es)

Jesus, J. F. ; Valentim, R. ; Andrade-Olivera, F.

• Tipo de documento: Artigo Científico
• Fonte: Journal of Cosmology and Astroparticle Physics; v. N/A, n. 9, p. 16-pg., 2017-09-01.

Resumo

Creation of Cold Dark Matter (CCDM), in the context of Einstein Field Equations, produces a negative pressure term which can be used to explain the accelerated expansion of the Universe. In this work we tested six different spatially flat models for matter creation using statistical criteria, in light of SNe Ia data: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Bayesian Evidence (BE). These criteria allow to compare models considering goodness of fit and number of free parameters, penalizing excess of complexity. We find that JO model is slightly favoured over LJO/Lambda CDM model, however, neither of these, nor Gamma = 3 alpha H-0 model can be discarded from the current analysis. Three other scenarios are discarded either because poor fitting or because of the excess of free parameters. A method of increasing Bayesian evidence through reparameterization in order to reducing parameter degeneracy is also developed. (AU)

• Processo FAPESP: 16/09831-0 - Populações de Estrelas de Nêutrons: ferramentas estatísticas bayesianas
• Beneficiário: Rodolfo Valentim da Costa Lima
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 17/05859-0 - O universo acelerado: natureza e testes da energia escura e matéria escura
• Beneficiário: José Fernando de Jesus
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 13/26258-4 - Matéria superdensa no universo
• Beneficiário: Manuel Máximo Bastos Malheiro de Oliveira
• Modalidade de apoio: Auxílio à Pesquisa - Temático