PHANGS–JWST First Results: Dust-embedded Star Clusters in NGC 7496 Selected via 3.3 μm PAH Emission
Bibliographic record
Abstract
Abstract The earliest stages of star formation occur enshrouded in dust and are not observable in the optical. Here we leverage the extraordinary new high-resolution infrared imaging from JWST to begin the study of dust-embedded star clusters in nearby galaxies throughout the Local Volume. We present a technique for identifying dust-embedded clusters in NGC 7496 (18.7 Mpc), the first galaxy to be observed by the PHANGS–JWST Cycle 1 Treasury Survey. We select sources that have strong 3.3 μm PAH emission based on a F300M − F335M color excess and identify 67 candidate embedded clusters. Only eight of these are found in the PHANGS-HST optically selected cluster catalog, and all are young (six have SED fit ages of ∼1 Myr). We find that this sample of embedded cluster candidates may significantly increase the census of young clusters in NGC 7496 from the PHANGS-HST catalog; the number of clusters younger than ∼2 Myr could be increased by a factor of 2. Candidates are preferentially located in dust lanes and are coincident with the peaks in the PHANGS-ALMA CO (2–1) maps. We take a first look at concentration indices, luminosity functions, SEDs spanning from 2700 Å to 21 μm, and stellar masses (estimated to be between ∼104 and 105 M ⊙). The methods tested here provide a basis for future work to derive accurate constraints on the physical properties of embedded clusters, characterize the completeness of cluster samples, and expand analysis to all 19 galaxies in the PHANGS–JWST sample, which will enable basic unsolved problems in star formation and cluster evolution to be addressed.
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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 | 0.001 | 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) | 0.002 | 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".