Black Hole Masses and Eddington Ratios at 0.3 <<i>z</i>< 4
Bibliographic record
Abstract
We study the distribution of Eddington luminosity ratios, L bol / L Edd , of active galactic nuclei (AGNs) discovered in the AGN and Galaxy Evolution Survey (AGES). We combine Hβ, Mg II, and C IV line widths with continuum luminosities to estimate black hole (BH) masses in 407 AGNs, covering the redshift range z ~ 0.3-4 and the bolometric luminosity range L bol ~ 10 45 -10 47 ergs s -1 . The sample consists of X-ray or mid-infrared (24 μm) point sources with optical magnitude R ≤ 21.5 mag and optical emission-line spectra characteristic of AGNs. For the range of luminosity and redshift probed by AGES, the distribution of estimated Eddington ratios is well described as log-normal, with a peak at L bol / L Edd ≃ 1/4 and a dispersion of 0.3 dex. Since additional sources of scatter are minimal, this dispersion must account for contributions from the scatter between estimated and true BH mass and the scatter between estimated and true bolometric luminosity. Therefore, we conclude that (1) neither of these sources of error can contribute more than ~0.3 dex rms, and (2) the true Eddington ratios of optically luminous AGNs are even more sharply peaked. Because the mass estimation errors must be smaller than ~0.3 dex, we can also investigate the distribution of Eddington ratios at fixed BH mass. We show for the first time that the distribution of Eddington ratios at fixed BH mass is peaked, and that the dearth of AGNs at a factor of ~10 below Eddington is real and not an artifact of sample selection. These results provide strong evidence that supermassive BHs gain most of their mass while radiating close to the Eddington limit, and they suggest that the fueling rates in luminous AGNs are ultimately determined by BH self-regulation of the accretion flow rather than galactic-scale dynamical disturbances.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".