Spatially Resolved UV Diagnostics of AGN Feedback: Radiation Pressure Dominates in a Prototypical Quasar-driven Superwind
Bibliographic record
Abstract
Abstract Galactic-scale winds driven by active galactic nuclei (AGN) are often invoked to suppress star formation in galaxy evolution models, but the mechanisms driving these outflows are hotly debated. Two key AGN feedback models are (1) radiation pressure accelerating cool gas and (2) a hot outflowing wind entraining the interstellar medium (ISM). Highly ionized emission-line diagnostics represent a powerful means of differentiating these scenarios because of their sensitivity to the expected compression of the ISM clouds by the hot wind. Here, we report the first spatially resolved UV emission spectroscopy of a prototypical (radio-quiet) quasar-driven superwind around the obscured quasar SDSS J1356+1026 at z = 0.123. We observe ratios of O vi/C iv, N v/C iv, and C iv/He ii that are remarkably similar for outflowing gas clouds ≲100 pc and ≈10 kpc from the nucleus. Such similarity is expected for clouds with AGN radiation-pressure-dominated dynamics. Comparing the observed line emission to models of clouds in balance with radiation pressure and/or a hot wind, we rule out the presence of a dynamically important hot wind and constrain the ratio of hot gas pressure to radiation pressure to P hot/P rad ≲ 0.25 both at ≲100 pc and ≈10 kpc from the nucleus. Moreover, the predictions of the radiation pressure confined cloud models that best fit observed UV line ratios are consistent with the observed diffuse X-ray spectrum. These results indicate that this AGN superwind is driven by radiation pressure or was driven by a hot wind that has since dissipated despite ongoing AGN activity.
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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 | 0.000 |
| 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) | 0.001 | 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".