Spatial and Dynamical Biases in Velocity Statistics of Galaxies

Details Spatial and Dynamical Biases in Velocity Statistics of Galaxies Spatial and Dynamical Biases in Velocity Statistics of Galaxies

2003-03-03

arxiv.org/abs/astro-ph/0303053v1

Astrophys.J. 590 (2003) 654-663

Astronomy and Astrophysics

Astrophysics

29 pages, 11 figures, accepted for publication in the ApJ

Scientific paper

10.1086/375148

We present velocity statistics of galaxies and their biases inferred from the statistics of the underlying dark matter using a cosmological hydrodynamic simulation of galaxy formation in low-density and spatially flat cold dark matter cosmogony. We find that the pairwise velocity dispersion (PVD) of all galaxies is significantly lower than that of the dark matter particles, and that the PVD of the young galaxies is lower than that of the old types, and even of all galaxies together, especially at small separations. These results are in reasonable agreement with the recent measurements of PVDs in the Las Campanas redshift survey, the PSCz catalogue and the SDSS data. We also find that the low PVD of young galaxies is due to the effects of dynamical friction as well as the different spatial distribution. We also consider the mean infall velocity and the POTENT density reconstruction that are often used to measure the cosmological parameters, and investigate the effects of spatial bias and dynamical friction. In our simulation, the mean infall velocity of young galaxies is significantly lower than that of all the galaxies or of the old galaxies, and the dynamical bias becomes important on scales less than 3Mpc/h. The mass density field reconstructed from the velocity field of young galaxies using the POTENT-style method suffers in accuracy both from the spatial bias and the dynamical friction on the smoothing scale of R_s=8Mpc/h. On the other hand, in the case of R_s=12Mpc/h, which is typically adopted in the actual POTENT analysis, the density reconstruction based on various tracers of galaxies is reasonably accurate.

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