Bibliographic record
Abstract
The dust-to-stellar mass ratio (Mdust/M⋆) is a crucial, albeit poorly constrained, parameter for improving our understanding of the complex physical processes involved in the production of dust, metals, and stars in galaxy evolution. In this work, we explore trends of Mdust/M⋆ with different physical parameters and using observations of 300 massive dusty star-forming galaxies detected with ALMA up to z ≈ 5. Additionally, we interpret our findings with different models of dusty galaxy formation. We find that Mdust/M⋆ evolves with redshift, stellar mass, specific star formation rates, and integrated dust size, but that evolution is different for main-sequence galaxies than it is for starburst galaxies. In both galaxy populations, Mdust/M⋆ increases until z ∼ 2, followed by a roughly flat trend towards higher redshifts, suggesting efficient dust growth in the distant universe. We confirm that the inverse relation between Mdust/M⋆ and M⋆ holds up to z ≈ 5 and can be interpreted as an evolutionary transition from early to late starburst phases. We demonstrate that the Mdust/M⋆ in starbursts reflects the increase in molecular gas fraction with redshift and attains the highest values for sources with the most compact dusty star formation. State-of-the-art cosmological simulations that include self-consistent dust growth have the capacity to broadly reproduce the evolution of Mdust/M⋆ in main-sequence galaxies, but underestimating it in starbursts. The latter is found to be linked to lower gas-phase metallicities and longer dust-growth timescales relative to observations. The results of phenomenological models based on the main-sequence and starburst dichotomy as well as analytical models that include recipes for rapid metal enrichment are consistent with our observations. Therefore, our results strongly suggest that high Mdust/M⋆ is due to rapid dust grain growth in the metal-enriched interstellar medium. This work highlights the multi-fold benefits of using Mdust/M⋆ as a diagnostic tool for: (1) disentangling main-sequence and starburst galaxies up to z ∼ 5; (2) probing the evolutionary phase of massive objects; and (3) refining the treatment of the dust life cycle in simulations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".