Polycyclic Aromatic Hydrocarbon emission model in photodissociation regions – I. Application to the 3.3, 6.2, and 11.2 μm bands
Bibliographic record
Abstract
ABSTRACT We present a charge distribution based model that computes the infrared spectrum of polycyclic aromatic hydrocarbon (PAH) molecules using recent measurements or quantum chemical calculations of specific PAHs. The model is applied to a sample of well-studied photodissociation regions (PDRs) with well-determined physical conditions (the radiation field strength, G0, electron density ne, and the gas temperature, Tgas). Specifically, we modelled the emission of five PAHs ranging in size from 18 to 96 carbon atoms, over a range of physical conditions characterized by the ionization parameter $\gamma = G_{0}\times T_{\rm gas}^{1/2}/n_{e}$. The anions emerge as the dominant charge carriers in low γ (<2 × 102) environments, neutrals in the intermediate γ (103 – 104) environments, and cations in the high γ (>105) environments. Furthermore, the PAH anions and cations exhibit similar spectral characteristics. The similarity in the cationic and anionic spectra translates into the interpretation of the 6.2/(11.0+11.2) band ratio, with high values of this ratio associated with large contributions from either cations or anions. The model’s predicted values of 6.2/(11.0+11.2) and 3.3/6.2 compared well to the observations in the PDRs NGC 7023, NGC 2023, the horsehead nebula, the Orion bar, and the diffuse interstellar medium, demonstrating that changes in the charge state can account for the variations in the observed PAH emission. We also reassess the diagnostic potential of the 6.2/(11.0+11.2) versus 3.3/(11.0+11.2) ratios and show that without any prior knowledge about γ, the 3.3/(11.0+11.2) can predict the PAH size, but the 6.2/(11.0 + 11.2) cannot predict the γ of the astrophysical environment.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".