Galaxy Groups in the SDSS DR4. II. Halo Occupation Statistics

By Xiaohu Yang, H. Mo, F. V. D. Bosch. 2007

269 citations recorded by the source corpus.

We investigate various galaxy occupation statistics of dark matter halos using a large galaxy group catalog constructed from the Sloan Digital Sky Survey Data Release 4 (SDSS DR4) with an adaptive halo-based group finder. The conditional luminosity function (CLF) is measured separately for all, red, and blue galaxies, as well as in terms of central and satellite galaxies. The CLFs for central and satellite galaxies can be well modeled with a lognormal distribution and a modified Schechter form, respectively. About 85% of the central galaxies and about 80% of the satellite galaxies in halos with masses Mh≳ 1014 h−1 M☉ are red galaxies. These numbers decrease to 50% and 40%, respectively, in halos with Mh ∼ 1012 h−1 M☉. For halos of a given mass, the distribution of the luminosities of central galaxies, Lc, has a dispersion of about 0.15 dex. The mean luminosity (stellar mass) of the central galaxies scales with halo mass as Lc ∝ Mh0.17 (M*,c ∝ Mh0.22) for halos with masses M ≫ 1012.5 h−1 M☉, and both relations are significantly steeper for less massive halos. We also measure the luminosity and stellar mass gaps between the first and second brightest (most massive) member galaxies, log L1 − log L2 (log M*,1 − log M*,2). These gap statistics, especially in halos with Mh≲ 1014.0 h−1 M☉, indicate that the luminosities of central galaxies are clearly distinct from those of their satellites. The fraction of fossil groups, defined as those groups with log L1 − log L2 ⩾ 0.8, ranges from ~2.5% for groups with Mh ∼ 1014 h−1 M☉ to 18%-60% for groups with Mh ∼ 1013 h−1 M☉. Finally, we measure the fraction of satellites, which changes from ~5.0% for galaxies with 0.1Mr − 5 log h ∼ − 22.0 to ~40% for galaxies with 0.1Mr − 5 log h ∼ − 17.0.

Subfields: Astronomy and Astrophysics, Computer Vision and Pattern Recognition, Ecology

View Paper: https://www.semanticscholar.org/paper/260cdcc3d4eb1e7310e7192baa5d2aefb81b1909

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In Astronomy and Astrophysics

  1. P. Hopkins
  2. L. Hernquist
  3. C. Conroy
  4. R. Somerville
  5. F. V. D. Bosch
  6. R. Dav'e
  7. A. Dekel
  8. Volker Springel

In Computer Vision and Pattern Recognition

  1. F. V. D. Bosch
  2. Xiaohu Yang
  3. H. Mo
  4. S. More
  5. Andrew Wetzel
  6. P. Hopkins
  7. M. Cacciato
  8. R. Somerville

In Ecology

  1. F. V. D. Bosch
  2. Xiaohu Yang
  3. H. Mo
  4. S. More
  5. Andrew Wetzel
  6. M. White
  7. R. Skibba
  8. L. Hernquist

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