Evidence for Merger Remnants in Early‐Type Host Galaxies of Low‐Redshift QSOs1
Bibliographic record
Abstract
We present results from a pilot HST ACS deep imaging study in broadband V of 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 reasonably well fitted by a de Vaucouleurs 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 ∼ 3 r 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.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".