PHANGS–JWST First Results: The Dust Filament Network of NGC 628 and Its Relation to Star Formation Activity
Bibliographic record
Abstract
Abstract PHANGS–JWST mid-infrared (MIR) imaging of nearby spiral galaxies has revealed ubiquitous filaments of dust emission in intricate detail. We present a pilot study to systematically map the dust filament network (DFN) at multiple scales between 25 and 400 pc in NGC 628. MIRI images at 7.7, 10, 11.3, and 21 μ m of NGC 628 are used to generate maps of the filaments in emission, while PHANGS–HST B -band imaging yields maps of dust attenuation features. We quantify the correspondence between filaments traced by MIR thermal continuum/polycyclic aromatic hydrocarbon (PAH) emission and filaments detected via extinction/scattering of visible light; the fraction of MIR flux contained in the DFN; and the fraction of H ii regions, young star clusters, and associations within the DFN. We examine the dependence of these quantities on the physical scale at which the DFN is extracted. With our highest-resolution DFN maps (25 pc filament width), we find that filaments in emission and attenuation are cospatial in 40% of sight lines, often exhibiting detailed morphological agreement; that ∼30% of the MIR flux is associated with the DFN; and that 75%–80% of the star formation in H ii regions and 60% of the mass in star clusters younger than 5 Myr are contained within the DFN. However, the DFN at this scale is anticorrelated with looser associations of stars younger than 5 Myr identified using PHANGS–HST near-UV imaging. We discuss the impact of these findings on studies of star formation and the interstellar medium, and the broad range of new investigations enabled by multiscale maps of the DFN.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".