Structure growth in f (Q) cosmology

被引:0
作者
Sahlu, Shambel [1 ,2 ]
de la Cruz-Dombriz, Alvaro [3 ,4 ]
Abebe, Amare [1 ,5 ]
机构
[1] North West Univ, Ctr Space Res, ZA-2531 Potchefstroom, South Africa
[2] Wolkite Univ, Dept Phys, Wolkite, Ethiopia
[3] Univ Cape Town, Dept Math & Appl Math, Cosmol & Grav Grp, ZA-7700 Rondebosch, South Africa
[4] Univ Salamanca, Dept Fis Fundamental, E-37008 Salamanca, Spain
[5] Natl Inst Theoret & Computat Sci NITheCS, ZA-2520 Potchefstroom, South Africa
关键词
cosmological parameters; dark energy; cosmology: observations; cosmology: theory; REDSHIFT-SPACE DISTORTIONS; HUBBLE CONSTANT; GALAXY; PERTURBATIONS; CONSTRAINTS; PARAMETER; SUPERNOVAE; TELESCOPE; EXPANSION; SELECTION;
D O I
10.1093/mnras/staf439
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
We take into account redshift space distortion measurements to investigate the growth of cosmological large-scale structures within the framework of generalized symmetric teleparallel-f(Q) - gravity. After comparing the predictions of the f(Q)- gravity expansion history with Hubble parameter data and SNIa Pantheon + sample data sets and constraining the pertinent cosmological parameters Omega(m) and H-0, together with the exponent n for f(Q) power-law models, we derive the full system of equations governing linear cosmological perturbations to study matter fluctuations using the 1 + 3 covariant formalism when applied to f(Q) gravity. Thus, we resort to both the usual redshift-space distortion data f sigma(8) and some recent separate measurements of the growth rate f and the amplitude of matter fluctuations sigma(8) from the VIPERS (VIMOS Public Extragalactic Redshift Survey) and SDSS (Sloan Digital Sky Survey) collaborations to find the best-fitting cosmological parameters Omega(m), sigma(8) , and n . We also apply a collective analysis of such growth-structure data together with the aforementioned cosmic expansion measurements to constrain these parameters through Monte Carlo Markov Chain simulations. As a result, our analysis is capable of determining the statistical significance for the best-fitting parameter values through the AIC and BIC Bayesian selection criteria.
引用
收藏
页码:690 / 703
页数:14
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