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Record W1999519547 · doi:10.1086/529068

Evidence for Merger Remnants in Early‐Type Host Galaxies of Low‐Redshift QSOs1

2008· article· en· W1999519547 on OpenAlexaff
Nicola Bennert, Gabriela Canalizo, B. Jungwiert, Alan Stockton, F. Schweizer, Chien Y. Peng, Mark Lacy

Bibliographic record

VenueThe Astrophysical Journal · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsAstrophysicsPhysicsGalaxyRedshiftLuminosityHost (biology)AstronomyGalaxy formation and evolutionEcologyBiology

Abstract

fetched live from OpenAlex

We present results from a pilot HSTACS deep imaging study in broadband Vof five low-redshift QSO host galaxies classified in the literature as ellipticals. The aim of our study is to determine whether these early-type hosts formed at high redshift and have since evolved passively, or whether they have undergone relatively recent mergers that may be related to the triggering of the nuclear activity. We perform two-dimensional modeling of the light distributions to analyze the host galaxies’morphology.We find that,while each host galaxy is reasonablywell fitted by a deVaucouleurs profile, the majority of them (4/5) reveal significant fine structure such as shells and tidal tails. These structures contribute between ~5% and 10% to the total V-band luminosity of each host galaxy within a region of r~3r_(eff) and are indicative of merger events that occurred between a few hundred Myr and a Gyr ago. These timescales are comparable to starburst ages in the QSO hosts previously inferred from Keck spectroscopy. Our results thus support a consistent scenario in which most of the QSO host galaxies suffered mergers with accompanying starbursts that likely also triggered the QSO activity in some way, but we are also left with considerable uncertainty on physical mechanisms that might have delayed this triggering for several hundred Myr after the merger.

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 score0.009
Threshold uncertainty score0.503

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.255
Teacher spread0.227 · 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

Citations158
Published2008
Admission routes1
Has abstractyes

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