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Constraining the HI-Halo Mass Relation From Galaxy Clustering

Published 7 Jul 2017 in astro-ph.GA and astro-ph.CO | (1707.01999v2)

Abstract: We study the dependence of galaxy clustering on atomic gas mass using a sample of $\sim$16,000 galaxies with redshift in the range of $0.0025<z\<0.05$ and HI mass of $M_{\rm HI}\>108M_{\odot}$, drawn from the 70% complete sample of the Arecibo Legacy Fast ALFA survey. We construct subsamples of galaxies with $M_{\rm HI}$ above different thresholds, and make volume-limited clustering measurements in terms of three statistics: the projected two-point correlation function, the projected cross-correlation function with respect to a reference sample selected from the Sloan Digital Sky Survey, and the redshift-space monopole moment. In contrast to previous studies, which found no/weak HI-mass dependence, we find both the clustering amplitude on scales above a few Mpc and the bias factors to increase significantly with increasing HI mass for subsamples with HI mass thresholds above $109M_{\odot}$. For HI mass thresholds below $109M_{\odot}$, while the measurements have large uncertainties caused by the limited survey volume and sample size, the inferred galaxy bias factors are systematically lower than the minimum halo bias factor from mass-selected halo samples. The simple halo model, in which galaxy content is only determined by halo mass, has difficulties in interpreting the clustering measurements of the HI-selected samples. We extend the simple model by including the halo formation time as an additional parameter. A model that puts HI-rich galaxies into halos that formed late can reproduce the clustering measurements reasonably well. We present the implications of our best-fitting model on the correlation of HI mass with halo mass and formation time, as well as the halo occupation distributions and HI mass functions for central and satellite galaxies. These results are compared with the predictions from semi-analytic galaxy formation models and hydrodynamic galaxy formation simulations.

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