XRISM/Resolve Spectroscopy of the Central Engine in the Seyfert-1 AGN Mrk 279
Bibliographic record
Abstract
Abstract High-resolution X-ray spectroscopy with XRISM gives an unprecedented view of the “central engine” in active galactic nuclei (AGN), providing unique insights into black hole accretion and feedback. We present an analysis of the first XRISM/Resolve spectrum of the Seyfert-1 galaxy Mrk 279, known for its complex line profiles and variability. The data reveal velocity components within the Fe K α emission line that can be associated with the inner face of the molecular torus ( r ≥ 10 4 GM / c 2 ), the broad-line region (BLR; r = 165 0 − 1480 + 5780 G M / c 2 ), and the inner accretion disk ( r = 8 1 − 75 + 280 G M / c 2 ). We find evidence of low-velocity, highly ionized gas that contributes an H-like Fe XXVI emission line at 6.97 keV, confirming suggestions from prior low-resolution spectra. The data do not show slow winds in absorption, but two pairs of lines—consistent with He-like and H-like Fe shifted by v ≃ 0.22 c and v ≃ 0.33 c —improve the fit and could represent an ultrafast outflow (UFO). Their addition to the model only reduces the Akaike information criterion by 3.6 and 3.5, respectively, signaling modest support. Additional observations are needed to definitively test for the presence of fast X-ray winds in Mrk 279. We discuss these results in the context of the geometry of the central engine in AGN, emerging trends in XRISM studies of AGN, and the nature of the potential UFOs.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".