PHANGS–JWST First Results: Massive Young Star Clusters and New Insights from JWST Observations of NGC 1365
Bibliographic record
Abstract
Abstract A primary new capability of JWST is the ability to penetrate the dust in star-forming galaxies to identify and study the properties of young star clusters that remain embedded in dust and gas. In this Letter we combine new infrared images taken with JWST with our optical Hubble Space Telescope (HST) images of the starbursting barred (Seyfert2) spiral galaxy NGC 1365. We find that this galaxy has the richest population of massive young clusters of any known galaxy within 30 Mpc, with ∼30 star clusters that are more massive than 106 M ⊙ and younger than 10 Myr. Sixteen of these clusters are newly discovered from our JWST observations. An examination of the optical images reveals that 4 of 30 (∼13%) are so deeply embedded that they cannot be seen in the Hubble I band (A V ≳ 10 mag), and that 11 of 30 (∼37%) are missing in the HST B band, so age and mass estimates from optical measurements alone are challenging. These numbers suggest that massive clusters in NGC 1365 remain completely obscured in the visible for ∼1.3 ± 0.7 Myr and are either completely or partially obscured for ∼3.7 ± 1.1 Myr. We also use the JWST observations to gain new insights into the triggering of star cluster formation by the collision of gas and dust streamers with gas and dust in the bar. The JWST images reveal previously unknown structures (e.g., bridges and overshoot regions from stars that form in the bar) that help us better understand the orbital dynamics of barred galaxies and associated star-forming rings. Finally, we note that the excellent spatial resolution of the NIRCAM F200W filter provides a better way to separate barely resolved compact clusters from individual stars based on their sizes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".