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Abstract:

Using mean relative peculiar velocity measurements for pairs of galaxies, we estimate the cosmological density parameter $\Omega_m$ and the amplitude of density fluctuations $\sigma_8$. Our results suggest that our statistic is a robust and reproducible measure of the mean pairwise velocity and thereby the $\Omega_m$ parameter. We get $\Omega_m = 0.30^{+0.17}_{-0.07}$ and $\sigma_8 = 1.13^{+0.22}_{-0.23}$. These estimates do not depend on prior assumptions on the adiabaticity of the initial density fluctuations, the ionization history, or the values of other cosmological parameters.

Abstract:

We present the Mock Map Facility, a powerful tool to generate mock catalogues or images from semi-analytically post-processed snapshots of cosmological N-body simulations. The paper describes in detail an efficient technique to create such mocks from the GALICS semi-analytic model, providing the reader with an accurate quantification of the artifacts it introduces at every step. We show that replication effects introduce a negative bias on the clustering signal -- typically peaking at less than 10 percent around the correlation length. We also thoroughly discuss how the clustering signal is affected by finite volume effects, and show that it vanishes at scales larger than about a tenth of the simulation box size. For the purpose of analysing our method, we show that number counts and redshift distributions obtained with GALICS and MOMAF compare well to K-band observations and to the 2dFGRS. Given finite volume effects, we also show that the model can reproduce the APM angular correlation function. The MOMAF results discussed here are made publicly available to the astronomical community through a public database. Moreover, a user-friendly Web interface (http://galics.iap.fr) allows any user to recover her/his own favourite galaxy samples through simple SQL queries. The flexibility of this tool should permit a variety of uses ranging from extensive comparisons between real observations and those predicted by hierarchical models of galaxy formation, to the preparation of observing strategies for deep surveys and tests of data processing pipelines.