Constraints on QSO models from a relation between the QSO luminosity function and the local black hole mass function
Bibliographic record
Abstract
QSOs are believed to be powered by accretion onto massive black holes (BHs). In this paper, with assuming that each central BH in nearby galaxies has experienced the QSO phase and ignoring BH mergers, we establish a relation between the QSO luminosity function (LF) and the local BH mass function (MF). The QSOLF is jointly controlled by the luminosity evolution of individual QSOs and the triggering history of the accretion onto seed BHs. By comparing the time integral of the QSOLF with that inferred from local BHs, we separate the effect of the luminosity evolution of individual QSOs from the effect of the triggering history. With assuming that the nuclear luminosity evolution includes two phases (first increasing at the Eddington luminosity with growth of BHs and then declining), we find that observations are generally consistent with the expected relation between the QSOLF and the local BHMF, and obtain the constraints on QSO models and BH growth. We point out that the value of the QSO lifetime is hard to be accurately estimated from the QSOLF and/or the local BHMF, if it is longer than a certain value (e.g., four times of the Salpeter timescale in this study). We discuss the importance of accurate measurements of the intrinsic scatter in the BH mass and velocity dispersion relation of local galaxies and the scatter in the bolometric correction of QSOs. We also discuss some possible applications of the work in this paper, such as to the study of the demography of QSOs and the demography of normal galaxies at intermediate redshift (abridged).
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".