http://arxiv.org/abs/1712.07261
We present a local dust mass function (DMF) of 15,355 galaxies drawn from the overlapping GAMA and H-ATLAS fields out to redshifts of 0.1. We derive this fundamental measurement of the dust content of galaxies using the traditional density corrected $V$max method where we use: (i) the normal photometric selection limit ($pV$max) and (ii) a bivariate brightness distribution (BBD) technique, which accounts for two selection effects. A single Schechter function adequately represents both the $pV$max and BBD estimates. We derive Schechter function parameters of $\alpha$=(-1.21+/-0.01), M$^$=(4.70+/-0.17)$\times10^{7}h^{2}{70}M{\odot}$, $\phi^$=(6.18+/-0.26)$\times10^{-3}h^{3}{70}\rm Mpc^{-3}dex^{-1}$. The dust mass density parameter integrated down to our limit of $10^{4}M{\odot}$ is $\Omega_{d}$=(1.09+/-0.02)$\times10^{-6}$ with an overall fraction of baryons (by mass) stored in dust $f_{mb}$=(4.59+/-0.08)$\times10^{-5}$; the additional error due to cosmic variance is ~17 per cent. We show that the observed DMF does not agree with theoretical predictions derived from semi-analytic models or hydrodynamical cosmological simulations. We show that the former attributes too much dust to high stellar mass galaxies. The dust-to-stellar mass ratio is higher for low-mass disks than currently assumed in the models. The latter underpredicts the high mass end of the DMF potentially due to long grain growth timescales. In comparing the DMFs and galaxy stellar mass functions (GSMF) we find there may be a simple approximate linear scaling of (7.61+/-0.36)$\times10^{-4}$ from the late-type galaxy (LTG) GSMF to the LTG DMF. The LTG DMF can also be approximated by scaling the disk GSMF by a factor of (9.63+/-0.46)$\times10^{-4}$. We derive dust mass densities of ${\Omega}{d}$=(0.83+/-0.03)$\times10^{-6}$ and ${\Omega}{d}$=(0.060+/-0.004)$\times10^{-6}$ for LTGs and early-types respectively.
R. Beeston, A. Wright, S. Maddox, et. al.
Thu, 21 Dec 17
6/76
Comments: 21 Pages, 16 Figures. Submitted December 2017