Investigating the structure of the windy torus in quasars
Bibliographic record
Abstract
Thermal mid-infrared emission of quasars requires an obscuring structure that can be modelled as a magneto-hydrodynamic wind in which radiation pressure on dust shapes the outflow. We have taken the dusty-wind models presented by Keating and collaborators that generated quasar mid-infrared spectral energy distributions (SEDs), and explore their properties (such as geometry, opening angle, and ionic column densities) as a function of Eddington ratio and X-ray weakness. In addition, we present new models with a range of magnetic field strengths and column densities of the dust-free shielding gas interior to the dusty wind. We find this family of models – with input parameters tuned to accurately match the observed mid-IR power in quasar SEDs – provides reasonable values of the Type 1 fraction of quasars and the column densities of warm absorber gas, though it does not explain a purely luminosity-dependent covering fraction for either. Furthermore, we provide predictions of the cumulative distribution of E(B − V) values of quasars from extinction by the wind and the shape of the wind as imaged in the mid-infrared. Within the framework of this model, we predict that the strength of the near-infrared bump from hot dust emission will be correlated primarily with L/LEdd rather than luminosity alone, with scatter induced by the distribution of magnetic field strengths. The empirical successes and shortcomings of these models warrant further investigations into the composition and behaviour of dust and the nature of magnetic fields in the vicinity of actively accreting supermassive black holes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".