A JWST Study of Polycyclic Aromatic Hydrocarbon Emission in a Region of 30 Doradus
Bibliographic record
Abstract
Abstract Polycyclic aromatic hydrocarbons (PAHs) are responsible for strong mid-IR emission features near star-forming regions. It is well known that low-metallicity environments exhibit weaker PAH emission, but it is not clear how metallicity affects the properties of the emitting PAH population. We present a detailed study of the PAH emission in a region of 30 Doradus (30 Dor), a well-known low-metallicity star-forming environment in the Large Magellanic Cloud and we compare it to PAH emission in the Orion Bar to investigate the characteristics of the PAH population and how the environments affect the resulting IR emission. We analyze JWST observations of 30 Dor that include imaging (NIRCam and MIRI) and spectroscopy (NIRSpec integral-field unit (IFU) and MIRI Medium Resolution Spectroscopy (MRS)). We extracted NIRSpec/IFU and MIRI/MRS spectra from 18 apertures that cover the morphological structures present within the observed region of 30 Dor. We characterize the profiles and relative intensities of PAH emission in these apertures. The detailed profiles of the PAH emission bands in 30 Dor are all similar and match with one of the dissociation fronts (DF2) in the Orion Bar, but their relative band ratios show a much larger range than in the Orion Bar. The PAH emission in 30 Dor originates from a population with a lower or similar ionization fraction than in the Orion Bar, and a size distribution that has more small-sized PAHs. Since smaller PAHs typically photofragment before larger PAHs, our findings support the hypothesis that the lower PAH emission due to lower metallicities is the result of the inhibition of growth toward larger PAHs rather than photofragmentation.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".