Host galaxies of high-redshift extremely red and obscured quasars
Bibliographic record
Abstract
Abstract We present Hubble Space Telescope 1.4–1.6 $\mu$m images of the hosts of 10 extremely red quasars (ERQs) and six type 2 quasar candidates at z = 2–3. ERQs, whose bolometric luminosities range between 1047 and 1048 erg s−1, show spectroscopic signs of powerful ionized winds, whereas type 2 quasar candidates are less luminous and show only mild outflows. After performing careful subtraction of the quasar light, we clearly detect almost all host galaxies. The median rest-frame B-band luminosity of the ERQ hosts in our sample is $10^{11.2}\, \mathrm{L}_{\odot }$, or ∼4L* at this redshift. Two of the 10 hosts of ERQs are in ongoing mergers. The hosts of the type 2 quasar candidates are 0.6 dex less luminous, with 2/6 in likely ongoing mergers. Intriguingly, despite some signs of interaction and presence of low-mass companions, our objects do not show nearly as much major merger activity as do high-redshift radio-loud galaxies and quasars. In the absence of an overt connection to major ongoing gas-rich merger activity, our observations are consistent with a model in which the near-Eddington accretion and strong feedback of ERQs are associated with relatively late stages of mergers resulting in early-type remnants. These results are in some tension with theoretical expectations of galaxy formation models, in which rapid black hole growth occurs within a short time of a major merger. Type 2 quasar candidates are less luminous, so they may instead be powered by internal galactic processes.
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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 | 0.001 |
| 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 | 0.000 |
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".