The Galaxy Cross-Correlation Function as a Probe of the Spatial Distribution of Galactic Satellites

TL;DR

This paper uses galaxy cross-correlation and halo models to analyze the spatial distribution of satellite galaxies, comparing results with previous interloper subtraction methods and testing on SDSS data.

Contribution

It introduces a novel approach combining cross-correlation analysis with HOD models to study satellite distributions, validated on mock catalogs and applied to SDSS data.

Findings

Results are consistent with previous interloper subtraction methods.

Large errors indicate need for bigger data samples.

Analysis extends to larger scales up to 6.3 Mpc/h.

Abstract

The spatial distribution of satellite galaxies around host galaxies can illuminate the relationship between satellites and dark matter subhalos and aid in developing and testing galaxy formation models. Previous efforts to constrain the distribution attempted to eliminate interlopers from the measured projected number density of satellites and found that the distribution is generally consistent with the expected dark matter halo profile of the parent hosts, with a best-fit power-law slope of ~ -1.7 between projected separations of ~30 kpc/h and 0.5 Mpc/h. Here, I use the projected cross-correlation of bright and faint galaxies to analyze contributions from satellites and interlopers together, using a halo occupation distribution (HOD) analytic model for galaxy clustering. This approach is tested on mock catalogs constructed from simulations. I find that analysis of Sloan Digital Sky Survey (SDSS) data gives results generally consistent with interloper subtraction methods between the projected separations of 10 kpc/h and 6.3 Mpc/h, although the errors on the parameters that constrain the radial profile are large, and larger samples of data are required.