Bayesian correction of H(z) data uncertainties

Author(s)

Jesus, J. F. ^{[1, 2]} ; Gregorio, T. M. ^[1] ; Andrade-Oliveira, F. ^{[3, 4]} ; Valentim, R. ^[5] ; Matos, C. A. O. ^[1]

Affiliation

^[1] Univ Estadual Paulista UNESP, Campus Expt Itapeva, Rua Geraldo Alckmin 519, BR-18409010 Itapeva, SP - Brazil

^[2] Univ Estadual Paulista UNESP, Fac Engn, Dept Fis & Quim, Av Dr Ariberto Pereira Cunha 333, BR-12516410 Guaratingueta, SP - Brazil

^[3] Univ Estadual Paulista UNESP, Inst Fis Teor, BR-01140070 Sao Paulo, SP - Brazil

^[4] Lab Interinst & Astron LIneA, Rua Gen Jose Cristino 77, BR-20921400 Rio De Janeiro, RJ - Brazil

^[5] Univ Fed Sao Paulo UNIFESP, ICAQF, Dep Fis, Unidade Jose Alencar, Rua Sao Nicolau 210, BR-09913030 Diadema, SP - Brazil

• Document type: Journal article
• Source: Monthly Notices of the Royal Astronomical Society; v. 477, n. 3, p. 2867-2873, JUL 2018.
• Web of Science Citations: 5

Abstract

We compile 41 H(z) data from literature and use them to constrain O Lambda CDM and flat Lambda CDM parameters. We show that the available H(z) suffers from uncertainties overestimation and propose a Bayesian method to reduce them. As a result of this method, using H(z) only, we find, in the context of O Lambda CDM, H-0 = 69.5 +/- 2.5 kms(-1) Mpc(-1), Omega(m) = 0.242 +/- 0.036, and Omega(Lambda) = 0.68 +/- 0.14. In the context of flat Lambda CDMmodel, we have found H-0 = 70.4 +/- 1.2 kms(-1) Mpc(-1) and Omega(m) = 0.256 +/- 0.014. This corresponds to an uncertainty reduction of up to approximate to 30 per cent when compared to the uncorrected analysis in both cases. (AU)

• FAPESP's process: 13/26258-4 - Superdense matter in the universe
• Grantee: Manuel Máximo Bastos Malheiro de Oliveira
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 16/09831-0 - Neutron Stars populations: bayesian statistics tools
• Grantee: Rodolfo Valentim da Costa Lima
• Support Opportunities: Regular Research Grants
• FAPESP's process: 17/05859-0 - The accelerating universe: nature and tests of dark energy and dark matter
• Grantee: José Fernando de Jesus
• Support Opportunities: Regular Research Grants