The Sloan Digital Sky Survey Reverberation Mapping Project: Quasar Host Galaxies at z < 0.8 from Image Decomposition
Bibliographic record
Abstract
Abstract We present the rest-frame UV and optical photometry and morphology of low-redshift broad-line quasar host galaxies from the Sloan Digital Sky Survey Reverberation Mapping project. Our sample consists of 103 quasars at z < 0.8, spanning a luminosity range of −25 ≤ M g ≤ −17 mag. We stack the multi-epoch images in the g and i bands taken by the Canada–France–Hawaii Telescope. The combined g-band (i-band) images reach a 5σ depth of 26.2 (25.2) mag, with a typical point-spread function (PSF) size of 0.″7 (0.″6). Each quasar is decomposed into a PSF and a Sérsic profile, representing the components of the central active galactic nucleus (AGN) and the host galaxy, respectively. The systematic errors of the measured host galaxy flux in the two bands are 0.23 and 0.18 mag. The relative errors of the measured galaxy half-light radii (R e ) are about 13%. We estimate the rest-frame u- and g-band flux of the host galaxies, and find that the AGN-to-galaxy flux ratios in the g band are between 0.9 and 4.4 (68.3% confidence). These galaxies have high stellar masses . They have similar colors to star-forming galaxies at similar redshifts, which is consistent with AGN positive feedback in these quasars. We find that the relation in our sample is shallower than the local M Bulge–M BH relation. The Sérsic indices and the M *–R e relation indicate that the majority of the host galaxies are disk-like.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".