Grain size distributions and photoelectric heating in ionized media
Bibliographic record
Abstract
Ever since the pioneering study of Spitzer, it has been widely recognized that grains play an important role in the heating and cooling of photoionized environments. This includes the diffuse interstellar medium and H ii regions, planetary nebulae and photodissociation regions. A detailed code is necessary to model grains in a photoionized medium since the interactions of grains with their environment include a host of microphysical processes. In this paper we will use the spectral synthesis code cloudy for this purpose. A comprehensive upgrade of the grain model has been recently incorporated into cloudy. One of these upgrades is the newly developed hybrid grain charge model. This model allows discrete charge states of very small grains to be modelled accurately, while simultaneously avoiding the overhead of fully resolving the charge distribution of large grains, thus making the model both accurate and computationally efficient. A comprehensive comparison with the fully resolved charge state models of Weingartner & Draine shows that the agreement is very satisfactory for realistic size distributions. The effect of the grain size distribution on the line emission from photoionized regions is studied by taking standard models for an H ii region and a planetary nebula and adding a dust component to the models with varying grain size distributions. A comparison of the models shows that varying the size distribution has a dramatic effect on the emitted spectrum. The strongest enhancement is always found in optical/UV lines of the highest ionization stages present in the spectrum (with factors up to 2.5–4), while the strongest decrease is typically found in optical/UV lines of low ionization lines or infrared fine-structure lines of low/intermediate ionization stages (with reductions up to 10–25 per cent). Changing the grain size distribution also affects the ionization balance, and can affect resonance lines which are very sensitive to changes in the background opacity. All these results clearly demonstrate that the grain size distribution is an important parameter in photoionization models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".