Astronomy and Astrophysics – Astrophysics
Scientific paper
2005-04-21
Mon.Not.Roy.Astron.Soc. 362 (2005) 711-726
Astronomy and Astrophysics
Astrophysics
18 pages, 11 figures. Accepted for publication in MNRAS, 1 table added, fig7 replaced
Scientific paper
10.1111/j.1365-2966.2005.09351.x
We determine the cross-correlation function between galaxies and galaxy groups, using both the Two-Degree Field Galaxy Redshift Survey (2dFGRS) and the Sloan Digital Sky Survey (SDSS). We study the cross-correlation as a function of group mass, and as a function of the luminosity, stellar mass, colour, spectral type and specific star formation rate of the galaxies. All these cross-correlation functions show a clear transition from the `1-halo' to the `2-halo' regimes on a scale comparable to the virial radius of the groups in consideration. On scales larger than the virial radius, all cross-correlation functions are roughly parallel, consistent with the linear bias model. In particular, the large scale correlation amplitudes are higher for more massive groups, and for brighter and redder galaxies. In the `1-halo' regime, the cross-correlation function depends strongly on the definition of the group center. We consider both a luminosity-weighted center (LWC) and a center defined by the location of the brightest group galaxy (BGC). With the first definition, the bright early-type galaxies in massive groups are found to be more centrally concentrated than the fainter, late-type galaxies. Using the BGC, and excluding the brightest galaxy from the cross correlation analysis, we only find significant segregation in massive groups ($M \gta 10^{13}h^{-1}\msun$) for galaxies of different spectral types (or colours or specific star formation rates). In haloes with masses $\la 10^{13}h^{-1}\msun$, there is a significant deficit of bright satellite galaxies. Comparing the results from the 2dFGRS with those obtained from realistic mock samples, we find that the distribution of galaxies in groups is much less concentrated than dark matter haloes predicted by the current $\Lambda$CDM model. (Abridged)
Jing Yi-Peng
Li Cheng
Mo Hou-Jun
van den Bosch Frank C.
Weinmann Simone M.
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