Gemini Imaging of QSO Host Galaxies at<i>z</i> ∼ 2
Bibliographic record
Abstract
We present results of a Gemini adaptive optics (AO) imaging program to investigate the host galaxies of typical QSOs at z ~ 2. Our aim is to study the host galaxies of typical L QSOs at the epoch of peak QSO and star formation activity. The large database of faint QSOs provided by the Two-Degree Field QSO Redshift Survey allows us to select a sample of QSOs at z = 1.75-2.5 that have nearby (<12'' separation) bright stars suitable for use as AO guide stars. We have observed a sample of nine QSOs. The images of these sources have AO-corrected FWHM of between 0 11 and 0 25. We use multiple observations of point-spread function (PSF) calibration star pairs to quantify any uncertainty in the PSF. We then factored these uncertainties into our modeling of the QSO plus host galaxy. In only one case did we convincingly detect a host (2QZ J133311.4+001949, at z = 1.93). This host galaxy has K = 18.5 ± 0.2 mag with a half-light radius R e = 0 55 ± 0 1 equivalent to ~3 L , assuming a simple passively evolving model. From detailed simulations of our host galaxy modeling process, we find that for four of our targets we should be sensitive to host galaxies that are equivalent to ~2 L (passively evolved). Our nondetections therefore place tight constraints on the properties of L QSO host galaxies, which can be no brighter (after allowing for passive evolution) than the host galaxies of L active galactic nuclei at low redshift, although the QSOs themselves are a factor of ~50 brighter. This implies that either the fueling efficiency is much greater at high redshift or that more massive black holes are active at high redshift.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 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".