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Record W2791385925 · doi:10.3389/fspas.2017.00070

The Virial Factor and Biases in Single Epoch Black Hole Mass Determinations

2018· article· en· W2791385925 on OpenAlexaff
Julián E. Mejía-Restrepo, P. Lira, Benny Trakhtenbrot, Daniel M. Capellupo

Bibliographic record

VenueFrontiers in Astronomy and Space Sciences · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsMcGill University
FundersFondo Nacional de Desarrollo Científico y TecnológicoComisión Nacional de Investigación Científica y TecnológicaIsrael Science FoundationEidgenössische Technische Hochschule Zürich
KeywordsPhysicsAstrophysicsVirial theoremSupermassive black holeVirial massBlack hole (networking)GalaxyActive galactic nucleusQuasarAstronomyMass distribution

Abstract

fetched live from OpenAlex

Accurately determining the masses of supermassive black holes is crucial to understand their evolution and the establishment of their relationship with their host galaxy properties. Beyond the local universe, the single epoch mass estimation method provides a simple procedure to estimate black hole masses in large spectroscopic samples of type-1 active galactic nuclei. The method assumes virialized motion of gas in the close vicinity to the active black holes, traced through broad emission lines. However, because of the assumption of a universal virial factor, this procedure has uncertainties associated with the unknown distribution of the gas clouds. Here, using a sample of 39 quasars observed with the VLT/X-shooter spectrograph, we compare alternative estimations of black hole masses determined from the properties of the accretion disk emission around the black hole with the single epoch virial mass estimations. We find that the virial factor is inversely proportional to the observed width of the broad emission lines. This result implies that current virial masses can be miss-estimated by up to a factor of 6. Our analysis indicates that either the effect of line-of-sight inclination in a planar distribution of the broad line emitting gas or the radiation pressure perturbations to the distribution of gas can reproduce our findings.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.157
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.249
Teacher spread0.229 · 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 teacher head, 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

Citations6
Published2018
Admission routes1
Has abstractyes

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