Clustering and redshift-space distortions in interacting dark energy cosmologies

Details Clustering and redshift-space distortions in interacting dark energy cosmologies Clustering and redshift-space distortions in interacting dark energy cosmologies

2011-10-13

arxiv.org/abs/1110.3045v2

Mon. Not. R. Astron. Soc. 420 (2012), 2377

Astronomy and Astrophysics

Astrophysics

Cosmology and Extragalactic Astrophysics

11 pages, 7 figures. Minor changes, references added. MNRAS published

Scientific paper

10.1111/j.1365-2966.2011.20199.x

We investigate the spatial properties of the large scale structure (LSS) of the Universe in the framework of coupled dark energy (cDE) cosmologies. Using the public halo catalogues from the CoDECS simulations -- the largest set of N-body experiments to date for such cosmological scenarios -- we estimate the clustering and bias functions of cold dark matter (CDM) haloes, both in real- and redshift-space. Moreover, we investigate the effects of the dark energy (DE) coupling on the geometric and dynamic redshift-space distortions, quantifying the difference with respect to the concordance LambdaCDM model. At z~0, the spatial properties of CDM haloes in cDE models appear very similar to the LambdaCDM case, even if the cDE models are normalized at last scattering in order to be consistent with the latest Cosmic Microwave Background (CMB) data. At higher redshifts, we find that the DE coupling produces a significant scale-dependent suppression of the halo clustering and bias function. This effect, that strongly depends on the coupling strength, is not degenerate with sigma8 at scales r<5-10 Mpc/h. Moreover, we find that the coupled DE strongly affects both the linear distortion parameter, beta, and the pairwise peculiar velocity dispersion, sigma12. Although the models considered in this work are found to be all in agreement with presently available observational data, the next generation of galaxy surveys will be able to put strong constraints on the level of coupling between DE and CDM exploiting the shape of redshift-space clustering anisotropies.

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