SWEEPING AWAY THE MYSTERIES OF DUSTY CONTINUOUS WINDS IN ACTIVE GALACTIC NUCLEI
Bibliographic record
Abstract
An integral part of the unified model for active galactic nuclei (AGNs) is an axisymmetric obscuring medium, which is commonly depicted as a torus of gas and dust surrounding the central engine. However, a robust, dynamical model of the torus is required in order to understand the fundamental physics of AGNs and interpret their observational signatures. Here, we explore self-similar, dusty disk winds, driven by both magnetocentrifugal forces and radiation pressure, as an explanation for the torus. Using these models, we make predictions of AGN infrared (IR) spectral energy distributions from 2 to 100 μm by varying parameters such as the viewing angle (from i = 0° to 90°), the base column density of the wind (from N H, 0 = 10 23 to 10 25 cm −2 ), the Eddington ratio (from L / L Edd = 0.01 to 0.1), the black hole mass (from M BH = 10 8 to 10 9 M ☉ ), and the amount of power in the input spectrum emitted in the X-ray relative to that emitted in the UV/optical (from α ox = 1.1 to 2.1). We find that models with N H, 0 = 10 25 cm −2 , L / L Edd = 0.1, and M BH ⩾ 10 8 M ☉ are able to adequately approximate the general shape and amount of power expected in the IR as observed in a composite of optically luminous Sloan Digital Sky Survey quasars. The effect of varying the relative power coming out in X-rays relative to the UV is a change in the emission below ∼5 μm from the hottest dust grains; this arises from the differing contributions to heating and acceleration of UV and X-ray photons. We see mass outflows ranging from ∼1 to 4 M ☉ yr −1 , terminal velocities ranging from ∼1900 to 8000 km s −1 , and kinetic luminosities ranging from ∼1 × 10 42 to 8 × 10 43 erg s −1 . Further development of this model holds promise for using specific features of observed IR spectra in AGNs to infer fundamental physical parameters of the systems.
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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 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".