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Record W2952323009 · doi:10.1086/421380

The Black Hole Mass versus Velocity Dispersion Relation in QSOs/Active Galactic Nuclei: Observational Appearance and Black Hole Growth

2004· article· en· W2952323009 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsCanadian Institute for Theoretical Astrophysics
Fundersnot available
KeywordsVelocity dispersionLuminosityBlack hole (networking)Accretion (finance)GalaxyDispersion relationSupermassive black holeDispersion (optics)Eddington luminosity

Abstract

fetched live from OpenAlex

Studies of massive black holes (BHs) in nearby galactic centers have revealed a tight correlation between BH mass and galactic velocity dispersion. In this paper we investigate how the BH mass versus velocity dispersion relation and the nuclear luminosity versus velocity dispersion relation in QSOs/active galactic nuclei (AGNs) are connected with the BH mass versus velocity dispersion relation in local galaxies, through the nuclear luminosity evolution of individual QSOs/AGNs and the mass growth of individual BHs. In the study we ignore the effects of BH mergers and assume that the velocity dispersion does not change significantly during and after the nuclear activity phase. Using the observed correlation in local galaxies and an assumed form of the QSO/AGN luminosity evolution and BH growth, we obtain the simulated observational appearance of the BH mass versus velocity dispersion relation in QSOs/AGNs. The simulation results illustrate how the BH accretion history (e.g., the lifetime of nuclear activity and the possibility that QSOs/AGNs accrete at a super-Eddington accretion rate at the early evolutionary stage) can be inferred from the difference between the relation in QSOs/AGNs and that in local galaxies. We also show how the difference may be weakened by the flux limit of telescopes. We expect that a large complete sample of QSOs/AGNs with accurate BH mass and velocity dispersion measurements will help to quantitatively constrain QSO/AGN luminosity evolution and BH growth models.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.220
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2004
Admission routes1
Has abstractyes

Explore more

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