Discovery of a Remarkably Powerful Broad Absorption-line Quasar Outflow in SDSS J135246.37+423923.5
Bibliographic record
Abstract
Abstract Broad absorption-line (BAL) features in quasar spectra reveal an unambiguous signature of energetic outflows from central supermassive black holes, and thus, BAL quasars are prime targets for investigating the potential process of luminous quasar feedback on galaxies. We analyzed the rest-UV spectrum of an “overlapping trough” iron low-ionization broad absorption-line quasar (FeLoBAL) SDSS J135246.37+423923.5 using the novel spectral synthesis code SimBAL and discovered an extraordinarily fast and energetic BAL outflow. Our analysis revealed outflow velocities reaching with a velocity width of , which is the largest FeLoBAL outflow velocity measured to date. The column density of the outflow gas is log with the log kinetic luminosity (erg s −1 ), which exceeds the bolometric luminosity of the quasar and is energetic enough to effectively drive quasar feedback. The energy estimate for the outflow is far greater than the estimates from any BAL object previously reported. The object also shows “anomalous reddening” and a significant scattered component that we were able to model with SimBAL . We found the first definitive case for radiation filtering in an additional zero-velocity absorption component that required an absorbed continuum to produce the particular absorption lines observed (Mg ii , Al iii , and Al ii ) without also producing the high-ionization lines such as C iv .
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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 | 0.001 | 0.000 |
| 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".