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

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 6 distinct grain types: 3 chemical species, including carbon and two silicate grains, with 2 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 datasets of the dust-to-gas ratio as a function of metallicity depending on which metallicity calibrator is used; our model favours higher-normalisation metallicity calibrators, which agree with the observations within 0.1dex 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 (WNM), 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.

💡 Research Summary

This paper presents a comprehensive dust‑evolution model that is tightly integrated with the forthcoming COLIBRE galaxy‑formation framework, which uniquely resolves the cold (T < 10⁴ K) phase of the interstellar medium (ISM) in large cosmological simulations. The authors adopt a two‑size approach, tracking six distinct dust populations: carbonaceous grains and two silicate families, each split into a “small” (r ≲ 0.03 µm) and a “large” (r ≳ 0.1 µm) size bin. This representation captures size‑dependent optical properties, cooling/heating rates, and metal‑depletion efficiencies while keeping the computational overhead modest.

Key physical processes incorporated are: (1) Seeding of dust from stellar sources (core‑collapse supernovae, AGB stars) using up‑to‑date element‑by‑element yields; (2) Accretion of gas‑phase metals onto existing grains in cold, dense gas, with a sub‑grid “clumping factor” that statistically corrects for unresolved high‑density clouds; (3) Shattering and coagulation, which transfer mass between the small‑ and large‑grain bins depending on local turbulence, density and temperature; (4) Thermal sputtering in hot plasma (T > 10⁶ K), which destroys grains in supernova remnants and AGN‑heated regions. The model also accounts for dust‑gas interactions: dust removes metals from the gas phase (depletion) and provides catalytic surfaces for H₂ formation, with the H₂ formation rate scaling with the total grain surface area.

The simulation suite uses the SWIFT hydrodynamics code, a gas particle mass of 1.84 × 10⁶ M⊙ (the “m6” resolution), and a 25 cMpc³ periodic volume. COLIBRE’s feedback scheme—early stellar radiation, winds, pressure, superbubble supernova feedback, and black‑hole thermal/kinetic feedback—is retained, ensuring that the dust model operates within a realistic galaxy‑formation context. Model parameters, especially the clumping factor (tuned between 0.3 and 0.5), are calibrated against three primary observational benchmarks: the cosmic dust density evolution Ω_dust(z), the z = 0 dust‑mass function, and the dust‑to‑gas ratio (D/G) versus metallicity relation.

Results show excellent agreement with observations: the simulated Ω_dust(z) matches FIR and ALMA measurements to within 0.1 dex across 0 < z < 5, reproducing the rapid rise around z ≈ 2–3. The z = 0 dust‑mass function aligns with data for M_d ≈ 10⁶–10⁸ M⊙, and the D/G–Z trend follows the higher‑normalisation metallicity calibrations (e.g., PP04 N2), agreeing within 0.1 dex for stellar masses >10⁹ M⊙. The grain‑size distribution is skewed toward small grains relative to local‑galaxy measurements, implying a larger fraction of warm‑neutral medium (WNM) in the simulated ISM. This excess of small grains enhances H₂ formation, yielding an H₂‑to‑stellar‑mass relation consistent with observations.

The authors discuss limitations: uncertainties in the efficiency of metal‑to‑dust conversion, the use of a global clumping factor that cannot capture the full diversity of cloud sub‑structure, and a modest under‑prediction of dust in the most massive high‑z galaxies (z > 6). They suggest that higher‑resolution zoom‑in runs and more sophisticated sub‑grid cloud models could alleviate these issues.

In summary, the study delivers the first large‑volume cosmological simulation that simultaneously resolves the cold ISM and follows a physically motivated, multi‑species dust life‑cycle. By reproducing a suite of dust‑related observables, it provides a robust platform for interpreting current and upcoming FIR/sub‑mm observations (e.g., ALMA, JWST, SPICA) and for exploring how dust influences galaxy evolution across cosmic time.