The Dust-to-Gas and Dust-to-Metals Ratio in Galaxies from z=0-6. (arXiv:1906.09277v1 [astro-ph.GA])
<a href="http://arxiv.org/find/astro-ph/1/au:+Li_Q/0/1/0/all/0/1">Qi Li</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Narayanan_D/0/1/0/all/0/1">Desika Narayanan</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Dave_R/0/1/0/all/0/1">Romeel Dav&#xe9;</a>

We present predictions for the evolution of the galaxy dust-to-gas (DGR) and
dust-to-metal (DTM) ratios from z=0 to 6, using a model for the production,
growth, and destruction of dust grains implemented into the simba
cosmological hydrodynamic galaxy formation simulation. In our model, dust forms
in stellar ejecta, grows by the accretion of metals, and is destroyed by
thermal sputtering and supernovae. Our simulation reproduces the observed dust
mass function at z=0, but modestly under-predicts the mass function by ~x3 at z
~ 1-2. The z=0 DGR vs metallicity relationship shows a tight positive
correlation for star-forming galaxies, while it is uncorrelated for quenched
systems. There is little evolution in the DGR-metallicity relationship between
z=0-6. We use machine learning techniques to search for the galaxy physical
properties that best correlate with the DGR and DTM. We find that the DGR is
primarily correlated with the gas-phase metallicity, though correlations with
the depletion timescale, stellar mass and gas fraction are non-negligible. We
provide a crude fitting relationship for DGR and DTM vs. the gas-phase
metallicity, along with a public code package that estimates the DGR and DTM
given a set of galaxy physical properties.

We present predictions for the evolution of the galaxy dust-to-gas (DGR) and
dust-to-metal (DTM) ratios from z=0 to 6, using a model for the production,
growth, and destruction of dust grains implemented into the simba
cosmological hydrodynamic galaxy formation simulation. In our model, dust forms
in stellar ejecta, grows by the accretion of metals, and is destroyed by
thermal sputtering and supernovae. Our simulation reproduces the observed dust
mass function at z=0, but modestly under-predicts the mass function by ~x3 at z
~ 1-2. The z=0 DGR vs metallicity relationship shows a tight positive
correlation for star-forming galaxies, while it is uncorrelated for quenched
systems. There is little evolution in the DGR-metallicity relationship between
z=0-6. We use machine learning techniques to search for the galaxy physical
properties that best correlate with the DGR and DTM. We find that the DGR is
primarily correlated with the gas-phase metallicity, though correlations with
the depletion timescale, stellar mass and gas fraction are non-negligible. We
provide a crude fitting relationship for DGR and DTM vs. the gas-phase
metallicity, along with a public code package that estimates the DGR and DTM
given a set of galaxy physical properties.

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