Constraining the Projected Radial Distribution of Galactic Satellites with the Sloan Digital Sky Survey

Details Constraining the Projected Radial Distribution of Galactic Satellites with the Sloan Digital Sky Survey Constraining the Projected Radial Distribution of Galactic Satellites with the Sloan Digital Sky Survey

2005-12-14

arxiv.org/abs/astro-ph/0512376v2

Astrophys.J.647:86-101,2006

Astronomy and Astrophysics

Astrophysics

16 pages, 13 figures, ApJ accepted version. Minor changes from submitted version, added comparison to Conroy et al. (2005)

Scientific paper

10.1086/504462

We use the Sloan Digital Sky Survey (SDSS) spectroscopic sample to constrain the projected radial distribution of satellites around isolated ~ L* galaxies. We employ mock galaxy catalogs derived from high-resolution cosmological simulations to investigate the effects of interloper contamination and show that interlopers significantly bias the estimated slope of the projected radial distribution of satellites. We also show that the distribution of interlopers around galaxies is expected to be non-uniform in velocity space because galaxies are clustered and reside in crowded environments. Successful methods of interloper contamination correction should therefore take into account environments of the host galaxies. Two such new methods are presented and the most reliable of them is used to correct for interloper contamination in analyses of the SDSS galaxy sample. The best fit power-law slope of the interloper-corrected surface density distribution of satellites, Sigma(R) ~ R^alpha, in the volume-limited SDSS sample is alpha ~ -1.7 +/- 0.1, independent of the galaxy and satellite luminosities. Comparison with Lambda-CDM simulations shows that the radial distribution of the SDSS satellites is more concentrated than that of subhalos around galaxy-sized halos, especially at R < 100 kpc/h. The predicted dark matter radial distribution is somewhat more concentrated than the profile of the SDSS satellites, but the difference is not statistically significant for our sample.

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