WISDOM Project – XIII. Feeding molecular gas to the supermassive black hole in the starburst AGN-host galaxy Fairall 49
Bibliographic record
Abstract
ABSTRACT The mm-Wave Interferometric Survey of Dark Object Masses (WISDOM) is probing supermassive black holes (SMBHs) in galaxies across the Hubble sequence via molecular gas dynamics. We present the first WISDOM study of a luminous infrared galaxy with an active galactic nuclei (AGNs): Fairall 49. We use new ALMA observations of the CO(2 − 1) line with a spatial resolution of ∼80 pc together with ancillary HST imaging. We reach the following results: (1) The CO kinematics are well described by a regularly rotating gas disc with a radial inflow motion, suggesting weak feedback on the cold gas from both AGN and starburst activity; (2) The dynamically inferred SMBH mass is 1.6 ± 0.4(rnd) ± 0.8(sys) × 108 M⊙ assuming that we have accurately subtracted the AGN and starburst light contributions, which have a luminosity of ∼109 L⊙; (3) The SMBH mass agrees with the SMBH−stellar mass relation but is ∼50 times higher than previous estimates from X-ray variability; (4) The dynamically inferred molecular gas mass is 30 times smaller than that inferred from adopting the Galactic CO-to-H2 conversion factor (XCO) for thermalized gas, suggesting low values of XCO; (5) the molecular gas inflow rate increases steadily with radius and may be as high as ∼5 M⊙ yr−1. This work highlights the potential of using high-resolution CO data to estimate, in addition to SMBH masses, the XCO factor, and gas inflow rates in nearby galaxies.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".