PHANGS–JWST First Results: A Statistical View on Bubble Evolution in NGC 628
Bibliographic record
Abstract
Abstract The first JWST observations of nearby galaxies have unveiled a rich population of bubbles that trace the stellar-feedback mechanisms responsible for their creation. Studying these bubbles therefore allows us to chart the interaction between stellar feedback and the interstellar medium, and the larger galactic flows needed to regulate star formation processes globally. We present the first catalog of bubbles in NGC 628, visually identified using Mid-Infrared Instrument F770W Physics at High Angular resolution in Nearby GalaxieS (PHANGS)–JWST observations, and use them to statistically evaluate bubble characteristics. We classify 1694 structures as bubbles with radii between 6 and 552 pc. Of these, 31% contain at least one smaller bubble at their edge, indicating that previous generations of star formation have a local impact on where new stars form. On large scales, most bubbles lie near a spiral arm, and their radii increase downstream compared to upstream. Furthermore, bubbles are elongated in a similar direction to the spiral-arm ridgeline. These azimuthal trends demonstrate that star formation is intimately connected to the spiral-arm passage. Finally, the bubble size distribution follows a power law of index p = −2.2 ± 0.1, which is slightly shallower than the theoretical value by 1–3.5σ that did not include bubble mergers. The fraction of bubbles identified within the shells of larger bubbles suggests that bubble merging is a common process. Our analysis therefore allows us to quantify the number of star-forming regions that are influenced by an earlier generation, and the role feedback processes have in setting the global star formation rate. With the full PHANGS–JWST sample, we can do this for more 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".