THE SPATIAL CLUSTERING OF<i>ROSAT</i>ALL-SKY SURVEY AGNs. II. HALO OCCUPATION DISTRIBUTION MODELING OF THE CROSS-CORRELATION FUNCTION

Abstract

This is the second paper of a series that reports on our investigation of the\nclustering properties of AGNs in the ROSAT All-Sky Survey (RASS) through\ncross-correlation functions (CCFs) with Sloan Digital Sky Survey (SDSS)\ngalaxies. In this paper, we apply the Halo Occupation Distribution (HOD) model\nto the CCFs between the RASS Broad-line AGNs with SDSS Luminous Red Galaxies\n(LRGs) in the redshift range 0.16&lt;z&lt;0.36 that was calculated in paper I. In our\nHOD modeling approach, we use the known HOD of LRGs and constrain the HOD of\nthe AGNs by a model fit to the CCF. For the first time, we are able to go\nbeyond quoting merely a `typical' AGN host halo mass, M_h, and model the full\ndistribution function of AGN host dark matter halos. In addition, we are able\nto determine the large-scale bias and the mean M_h more accurately. We explore\nthe behavior of three simple HOD models. Our first model (Model A) is a\ntruncated power-law HOD model in which all AGNs are satellites. With this\nmodel, we find an upper limit to the slope (\\alpha) of the AGN HOD that is far\nbelow unity. The other two models have a central component, which has a step\nfunction form, where the HOD is constant above a minimum mass, without (Model\nB) or with (Model C) an upper mass cutoff, in addition to the truncated\npower-law satellite component, similar to the HOD that is found for galaxies.\nIn these two models we find the upper limits of \\alpha &lt; 0.95 and \\alpha &lt; 0.84\nfor Model B and C respectively. Our analysis suggests that the satellite AGN\noccupation increases slower than, or may even decrease with, M_h, in contrast\nto the satellite's HODs of luminosity-threshold samples of galaxies, which, in\ncontrast, grow approximately as \\propto M_h^\\alpha with \\alpha\\approx 1. These\nresults are consistent with observations that the AGN fraction in groups and\nclusters decreases with richness.\n