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- Title
Viability tests of f(R)-gravity models with Supernovae Type 1A data.
- Authors
Hough, R. T.; Abebe, A.; Ferreira, S. E. S.
- Abstract
In this work, we will be testing four different general f(R)-gravity models, two of which are the more realistic models (namely the Starobinsky and the Hu–Sawicki models), to determine if they are viable alternative models to pursue a more vigorous constraining test upon them. For the testing of these models, we use 359 low- and intermediate-redshift Supernovae Type 1A data obtained from the SDSS-II/SNLS2 Joint Light-curve Analysis (JLA). We develop a Markov Chain Monte Carlo (MCMC) simulation to find a best-fitting function within reasonable ranges for each f(R)-gravity model, as well as for the Lambda Cold Dark Matter (Λ CDM) model. For simplicity, we assume a flat universe with a negligible radiation density distribution. Therefore, the only difference between the accepted Λ CDM model and the f(R)-gravity models will be the dark energy term and the arbitrary free parameters. By doing a statistical analysis and using the Λ CDM model as our "true model", we can obtain an indication whether or not a certain f(R)-gravity model shows promise and requires a more in-depth view in future studies. In our results, we found that the Starobinsky model obtained a larger likelihood function value than the Λ CDM model, while still obtaining the cosmological parameters to be Ω m = 0. 268 - 0.024 + 0.027 for the matter density distribution and h ¯ = 0. 690 - 0.005 + 0.005 for the Hubble uncertainty parameter. We also found a reduced Starobinsky model that are able to explain the data, as well as being statistically significant.
- Subjects
HUBBLE Space Telescope (Spacecraft); MARKOV chain Monte Carlo; SUPERNOVAE; HUBBLE constant; ARBITRARY constants; DARK matter
- Publication
European Physical Journal C -- Particles & Fields, 2020, Vol 80, Issue 8, p1
- ISSN
1434-6044
- Publication type
Article
- DOI
10.1140/epjc/s10052-020-8342-7