The Relativistic Jet-accretion Flow–wind Connection in Mrk 231
Bibliographic record
Abstract
Abstract Long-term radio monitoring of the broad absorption line (BAL) quasar Mrk 231 at 17.6 GHz detected a strong flare in 2015. This triggered four epochs of Very Long Baseline Array (VLBA) observations from 8.4 to 43 GHz as well as three epochs of X-ray observations with NuSTAR and two with XMM over a 15 week period. Two ejected components were detected by the VLBA observations. A conservative lower bound on the apparent speed of the first ejection is attained by assuming that it was ejected when the flare began, . Serendipitous far-UV Hubble Space Telescope observations combined with our long-term radio monitoring seem to indicate that episodes of relativistic ejections suppress flux that is emitted at wavelengths shortward of the peak of the far-UV spectral energy distribution, similar to what has been observed in radio-loud quasars. Episodes of strong jet production also seem to suppress the high-ionization BAL wind seen in weak jet states. We found a statistically significant increase ( ) of the 3–12 keV flux during the radio flare relative to a quiescent radio state. This is explained by an ultra-fast (∼0.06c) X-ray-absorbing photoionized wind that is significantly detected only in the low-radio state (similar to Galactic black holes). Mrk 231 is becoming more radio loud. We found that the putative parsec-scale radio lobe doubled in brightness in nine years. Furthermore, large flares are more frequent, with three major flares occurring at ∼2 year intervals.
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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".