PHANGS-MeerKAT and MHONGOOSE HI observations of nearby spiral galaxies: Physical drivers of the molecular gas fraction, <i>R</i><sub>mol</sub>
Bibliographic record
Abstract
The molecular-to-atomic gas ratio is crucial to our understanding of the evolution of the interstellar medium (ISM) in galaxies. We investigated the balance between the atomic (ΣHI) and molecular gas (ΣH2) surface densities in eight nearby star-forming galaxies using new high-quality observations from MeerKAT and ALMA (for H I and CO, respectively). We defined the molecular gas ratio as Rmol = ΣH2/ΣHI and measured how Rmol depends on local conditions in the galaxy disks using multiwavelength observations. We find that, depending on the galaxy, H I is detected at > 3σ out to 20 − 120 kpc in galactocentric radius (rgal). The typical radius at which ΣHI reaches 1 M⊙ pc−2 is rH I ≈ 22 kpc, which corresponds to 1 − 3 times the optical radius (r25). We note that, Rmol correlates best with the dynamical equilibrium pressure, PDE, among potential drivers studied, with a median correlation coefficient of ⟨ρ⟩ = 0.89. Correlations between Rmol and the star formation rate surface density, total gas surface density, stellar surface density, metallicity, and ΣSFR/PDE (a proxy for the combined effect of the UV radiation field and number density) are present but somewhat weaker. Our results also show a direct correlation between PDE and ΣSFR, supporting self-regulation models. Quantitatively, we measured similar scalings as previous works, and attribute the modest differences that we do find to the effect of varying resolution and sensitivity. At rgal ≳ 0.4r25, atomic gas dominates over molecular gas among our studied galaxies, and at the balance of these two gas phases (Rmol = 1), we find that the baryon mass is dominated by stars, with Σ* > 5 Σgas. Our study constitutes an important step in the statistical investigation of how local galaxy properties (stellar mass, star formation rate, or morphology) impact the conversion from atomic to molecular gas in nearby galaxies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".