Quasar outflow energetics from broad absorption line variability
Bibliographic record
Abstract
Quasar outflows have long been recognized as potential contributors to the co-evolution between supermassive black holes (SMBHs) and their host galaxies. The role of outflows in AGN feedback processes can be better understood by placing observational constraints on wind locations and kinetic energies. We utilize broad absorption line (BAL) variability to investigate the properties of a sample of 71 BAL quasars with P$\thinspace$V broad absorption. The presence of P$\thinspace$V BALs indicates that other BALs like C$\thinspace$IV are saturated, such that variability in those lines favours clouds crossing the line of sight. We use these constraints with measurements of BAL variability to estimate outflow locations and energetics. Our data set consists of multiple-epoch spectra from the Sloan Digital Sky Survey and MDM Observatory. We detect significant (4$\sigma$) BAL variations from 10 quasars in our sample over rest frame time-scales between < 0.2-3.8 yr. Our derived distances for the 10 variable outflows are nominally < 1-10 pc from the SMBH using the transverse-motion scenario, and < 100-1000 pc from the central source using ionization-change considerations. These distances, in combination with the estimated high outflow column densities (i.e. $N_{\textrm{H}}$ > 10$^{22}$ cm$^{-2}$), yield outflow kinetic luminosities between ~ 0.001-1 times the bolometric luminosity of the quasar, indicating that many absorber energies within our sample are viable for AGN feedback.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".