Spatial variations in the distribution of galaxy luminosities, estimated from redshifts as distance proxies, are correlated with the peculiar velocity field. Comparing these variations with the peculiar velocities inferred from galaxy redshift surveys is a powerful test of gravity and dark-energy theories on cosmological scales. Using ~2 ×105 galaxies from the SDSS Data Release 7, we perform this test in the framework of gravitational instability to estimate the normalized growth rate of density perturbations f sigma8=0.37 ±0.13 at z ~0.1 , which is in agreement with the cold dark matter model with a cosmological constant. This unique measurement is complementary to those obtained with more traditional methods, including clustering analysis. The estimated accuracy at z ~0.1 is competitive with other methods when applied to similar data sets.
Feix Martin, Nusser Adi, & Branchini E (2015). Growth Rate of Cosmological Perturbations at z~0.1 from a New Observational Test. PHYSICAL REVIEW LETTERS, 115(1).
Titolo: | Growth Rate of Cosmological Perturbations at z~0.1 from a New Observational Test |
Autori: | |
Data di pubblicazione: | 2015 |
Rivista: | |
Citazione: | Feix Martin, Nusser Adi, & Branchini E (2015). Growth Rate of Cosmological Perturbations at z~0.1 from a New Observational Test. PHYSICAL REVIEW LETTERS, 115(1). |
Abstract: | Spatial variations in the distribution of galaxy luminosities, estimated from redshifts as distance proxies, are correlated with the peculiar velocity field. Comparing these variations with the peculiar velocities inferred from galaxy redshift surveys is a powerful test of gravity and dark-energy theories on cosmological scales. Using ~2 ×105 galaxies from the SDSS Data Release 7, we perform this test in the framework of gravitational instability to estimate the normalized growth rate of density perturbations f sigma8=0.37 ±0.13 at z ~0.1 , which is in agreement with the cold dark matter model with a cosmological constant. This unique measurement is complementary to those obtained with more traditional methods, including clustering analysis. The estimated accuracy at z ~0.1 is competitive with other methods when applied to similar data sets. |
Handle: | http://hdl.handle.net/11590/134912 |
Appare nelle tipologie: | 1.1 Articolo in rivista |