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Record W2066087926 · doi:10.1086/527462

Quasar Broad Absorption Line Variability on Multiyear Timescales

2008· article· en· W2066087926 on OpenAlexaff
R. R. Gibson, W. N. Brandt, Donald P. Schneider, S. C. Gallagher

Bibliographic record

VenueThe Astrophysical Journal · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsWestern University
Fundersnot available
KeywordsQuasarQSOSAstrophysicsVariation (astronomy)PhotoionizationPhysicsAbsorption (acoustics)Absorption spectroscopyOutflowEquivalent widthLine (geometry)Emission spectrumSpectral lineAstronomyOpticsGeometryGalaxyMeteorologyIonization

Abstract

fetched live from OpenAlex

We use quantitative metrics to characterize the variation of CIV 1549 A broad absorption lines (BALs) over 3--6 (rest-frame) years in a sample of 13 quasars at 1.7 <= z <= 2.8 and compare the results to previous studies of BAL variability on shorter time scales. The strong BALs in our study change in complex ways over 3--6 yr. Variation occurs in discrete regions which are only a few thousand km/s wide, and the distribution of the change in absorption equivalent width broadens over time. We constrain the typical CIV BAL lifetime to be at least a few decades. While we do not find evidence to support a scenario in which the variation is primarily driven by photoionization on multi-year time scales, there is some indication that the variation is produced by changes in outflow geometry. We do not observe significant changes in the BAL onset velocity, indicating that the absorber is either far from the source or is being continually replenished and is azimuthally symmetric. It is not possible in a human lifetime to expand the time scales in our study by more than a factor of a few using optical spectroscopy. However, the strong variation we have observed in some BALs indicates that future studies of large numbers of BAL QSOs will be valuable to constrain BAL lifetimes and the physics of variation.

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 score0.069
Threshold uncertainty score0.992

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.012
GPT teacher head0.223
Teacher spread0.212 · 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

Citations145
Published2008
Admission routes1
Has abstractyes

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