Polycyclic Aromatic Hydrocarbon and CO(2–1) Emission at 50–150 pc Scales in 70 Nearby Galaxies
Bibliographic record
Abstract
Abstract Combining Atacama Large Millimeter/submillimeter Array CO(2–1) mapping and JWST near- and mid-infrared imaging, we characterize the relationship between CO(2–1) and polycyclic aromatic hydrocarbon (PAH) emission at ≈100 pc resolution in 70 nearby star-forming galaxies. Leveraging a new Cycle 2 JWST Treasury program targeting nearby galaxies, we expand the sample size by more than an order of magnitude compared to previous ≈100 pc resolution CO–PAH comparisons. In regions of galaxies where most of the gas is likely to be molecular, we find strong correlations between CO(2–1) and 3.3 μ m, 7.7 μ m, and 11.3 μ m PAH emission, estimated from JWST’s F335M, F770W, and F1130W filters. We derive power-law relations between CO(2–1) and PAH emission, with indices in the range 0.8–1.3, implying relatively weak variations in the observed CO-to-PAH ratios across our sample. We find that CO-to-PAH ratios and scaling relationships near H ii regions are similar to those in diffuse sight lines. The main difference between the two types of regions is that sight lines near H ii regions show higher intensities in all tracers. Galaxy centers show higher overall intensities and enhanced CO-to-PAH ratios compared to galaxy disks. Individual galaxies show 0.19 dex scatter in the normalization of CO at fixed I PAH , and this normalization anticorrelates with specific star formation rate and correlates with stellar mass. We provide a prescription that accounts for galaxy-to-galaxy variations, representing our best current empirical predictor to estimate CO(2–1) intensity from PAH emission, allowing one to take advantage of JWST’s excellent sensitivity and resolution to trace cold gas.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".