Polycyclic aromatic hydrocarbon destruction in star-forming regions across 42 nearby galaxies
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) are widespread in the interstellar medium (ISM) of near solar metallicity galaxies, where they play a critical role in ISM heating, cooling, and reprocessing stellar radiation. The PAH fraction, the abundance of PAHs relative to total dust mass, is a key parameter in ISM physics. Using JWST and MUSE observations of 42 galaxies from the PHANGS survey, we analyzed the PAH fraction in over 17 000 H II regions spanning a gas-phase oxygen abundance of 12 + log(O/H) = 8.0–8.8 ( Z ∼ 0.2–1.3 Z ⊙ ), and ∼400 isolated supernova remnants (SNRs). We find a significantly lower PAH fraction toward H II regions compared to a reference sample of diffuse ISM areas at matched metallicity. At 12 + log(O/H) > 8.2, the PAH fraction toward H II regions is strongly anti-correlated with the local ionization parameter, suggesting that PAH destruction is correlated with ionized gas and/or hydrogen-ionizing UV radiation. At lower metallicities, the PAH fraction declines steeply in H II regions and in the diffuse ISM, likely reflecting less efficient PAH formation in metal-poor environments. Carefully isolating dust emission from the vicinity of optically identified supernova remnants, we see evidence of selective PAH destruction from measurements of lower PAH fractions, which is, however, indistinguishable at ∼50 pc scales. Overall, our results point to ionizing radiation as the dominant agent of PAH destruction within H II regions; metallicity plays a key role in their global abundance in 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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".