The dust mass function from z ∼0 to z ∼2.5

Abstract

We derive for the first time the dust mass function (DMF) in a wide redshift range, from z ∼ 0.2 up to z ∼ 2.5. In order to trace the dust emission, we start from a far-IR (160-µm) Herschel selected catalogue in the COSMOS field. We estimate the dust masses by fitting the far-IR data (λ rest > ∼ 50µm) with a modified black body function and we present a detailed analysis to take into account the incompleteness in dust masses from a far-IR perspective. By parametrizing the observed DMF with a Schechter function in the redshift range 0.1 < z ≤ 0.25, where we are able to sample faint dust masses, we measure a steep slope (α ∼1.48), as found by the majority of works in the Local Universe. We detect a strong dust mass evolution, with M d at z ∼ 2.5 almost one dex larger than in the local Universe, combined with a decrease in their number density. Integrating our DMFs we estimate the dust mass density (DMD), finding a broad peak at z ∼ 1, with a decrease by a factor of ∼ 3 towards z ∼ 0 and z ∼ 2.5. In general, the trend found for the DMD mostly agrees with the derivation of Driver et al. (2018), another DMD determination based also on far-IR detections, and with other measures based on indirect tracers.

The ALMA Spectroscopic Survey in the HUDF: The Cosmic Dust and Gas Mass Densities in Galaxies up to z ∼ 3

“…As noted in Section 5.1 and Figure 4, this redshift evolution is consistent with that inferred by Dunne et al (2003Dunne et al ( , 2011 and Driver et al (2018). It also broadly agrees with recent measurements by Pozzi et al (2019), which were obtained using Herschel observations in the COSMOS field. We only notice a significant disagreement with this later study at z>2; i.e., a redshift range where their observations mostly constrain the bright-end slope of the dust mass function.…”

“…To alleviate some of these uncertainties, independent constraints on the cosmic gas mass density using dust-based gas mass estimates are needed. These studies would simultaneously measure the redshift evolution of the cosmic dust mass density in galaxies, which to date remains only sparsely constrained (e.g., Dunne et al 2003Dunne et al , 2011Driver et al 2018;Pozzi et al 2019). This latter measurement would be instrumental for the growing number of galaxy evolution models that selfconsistently track the production and destruction of dust (e.g., Popping et al 2017;Aoyama et al 2018;Davé et al 2019;Vijayan et al 2019).…”

Tracing the evolution of dust-obscured activity using sub-millimetre galaxy populations from STUDIES and AS2UDS

“…The χ 2 contours for the two samples do not overlap, indicating evolution in both characteristic dust mass and space density. As these subsets are rest-wavelength matched, this change in the shape of their dust mass function suggests a change of normalization and characteristic dust mass of galaxies with redshift, similar to the findings of Pozzi et al (2020). However, since we have only limited constraints on the z ∼ 1.5 function due to the small sample size, we caution that the uncertainties can be substantial.…”

“…For comparison, we overlay the 'local' dust mass function of z < 0.1 galaxies from the GAMA sample by Beeston et al (2018). We also show the z = 2 results from a 160-μm survey by Pozzi et al (2020), though we note that at this redshift their selection wavelength is ∼50 μm and their survey is thus sensitive to relatively hot dust, potentially including AGN-heated sources. We observe that low-redshift sources have higher space density at lower dust masses, but the space density decreases steeply with increasing dust mass.…”

“…The arrow indicates a 2-σ upper limit for the z ∼ 1.5 sources. For comparison, we overlay the local (z < 0.1) dust mass function from the GAMA sample of Beeston et al (2018) and z = 2 results from 160-μm survey by Pozzi et al (2020). We also show z = 2 predictions from a semi-analytical model from Popping, Somerville & Galametz (2017) assuming a fixed time-scale for dust accretion in the ISM of 100 Myr, and from the cosmological hydrodynamic simulation SIMBA by Li et al (2019).…”