First Stellar Velocity Dispersion Measurement of a Luminous Quasar Host with Gemini North Laser Guide Star Adaptive Optics
Bibliographic record
Abstract
We present the first use of the Gemini North laser guide star adaptive optics (LGS AO) system and an integral field unit (IFU) to measure the stellar velocity dispersion of the host of a luminous quasar. The quasar PG 1426+015 ( z = 0.086) was observed with the Near-Infrared Integral Field Spectrometer (NIFS) on the 8 m Gemini North telescope in the H band as part of the Science Verification phase of the new ALTAIR LGS AO system. The NIFS IFU and LGS AO are well suited for host studies of luminous quasars because one can achieve a large ratio of host to quasar light. We have measured the stellar velocity dispersion of PG 1426+015 from 0.1'' to 1'' (0.16 to 1.6 kpc) to be 217 ± 15 km s −1 based on high signal-to-noise ratio measurements of Si I, Mg I, and several CO band heads. This new measurement is a factor of 4 more precise than a previous measurement obtained with long-slit spectroscopy and good, natural seeing, yet was obtained with a shorter net integration time. We find that PG 1426+015 has a velocity dispersion that places it significantly above the M BH -σ * relation of quiescent galaxies and lower luminosity active galactic nuclei with black hole masses estimated from reverberation mapping. We discuss several possible explanations for this discrepancy that could be addressed with similar observations of a larger sample of luminous quasars.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".