Modelling the evolution and influence of dust in cosmological simulations that include the cold phase of the interstellar medium

ABSTRACT While marginal in mass terms, dust grains play an outsized role in both the physics and observation of the interstellar medium (ISM). However, explicit modelling of this ISM constituent remains uncommon in large cosmological simulations. In this work, we present a model for the life-cycle of dust in the ISM that couples to the forthcoming COLIBRE galaxy formation model, which explicitly simulates the cold ISM. We follow six distinct grain types: three chemical species, including carbon and two silicate grains, with two size bins each. Our dust model accounts for seeding of grains from stellar ejecta, self-consistent element-by-element metal yields and growth by accretion, grain size transfer (shattering and coagulation) and destruction of dust by thermal sputtering in the ISM. We detail the calibration of this model, particularly the use of a clumping factor, to account for unresolved gas clouds in which dust readily evolves. We present a fiducial run in a 25$^3$ cMpc$^3$ cosmological volume that displays good agreement with observations of the cosmic evolution of dust density, as well as the $z=0$ galaxy dust mass function and dust scaling relations. We highlight known tensions between observational data sets of the dust-to-gas ratio as a function of metallicity depending on which metallicity calibrator is used; our model favours higher normalization metallicity calibrators, which agree with the observations within 0.1 dex for stellar masses $>10^9 \,\, {\rm M_\odot }$. We compare the grain size distribution to observations of local galaxies, and find that our simulation suggests a higher concentration of small grains, associated with more diffuse ISM and the warm-neutral medium, which both play a key role in boosting H$_2$ content. Putting these results and modelling approaches in context, we set the stage for upcoming insights into the dusty ISM of galaxies using the COLIBRE simulations.