Is there any evidence that ionized outflows quench star formation in type 1 quasars at
Bibliographic record
Abstract
Aims. The aim of this paper is to test the basic model of negative active galactic nuclei (AGN) feedback. According to this model, once the central black hole accretes at the Eddington limit and reaches a certain critical mass, AGN driven outflows blow out gas, suppressing star formation in the host galaxy and self-regulating black hole growth. Methods. We consider a sample of 224 quasars selected from the Sloan Digital Sky Survey (SDSS) at z< 1 observed in the infrared band by the Herschel Space Observatory in point source photometry mode. We evaluate the star formation rate in relation to several outflow signatures traced by the [O III] λ4959, 5007 and [O II] λ3726, 3729 emission lines in about half of the sample with high quality spectra. Results. Most of the quasars show asymmetric and broad wings in [O III], which we interpret as outflow signatures. We separate the quasars in two groups, “weakly” and “strongly” outflowing, using three different criteria. When we compare the mean star formation rate in five redshift bins in the two groups, we find that the star formation rate (SFR) are comparable or slightly larger in the strongly outflowing quasars. We estimate the stellar mass from spectral energy distribution (SED) fitting and the quasars are distributed along the star formation main sequence, although with a large scatter. The scatter from this relation is uncorrelated with respect to the kinematic properties of the outflow. Moreover, for quasars dominated in the infrared by starburst or by AGN emission, we do not find any correlation between the star formation rate and the velocity of the outflow, a trend previously reported in the literature for pure starburst galaxies. Conclusions. We conclude that the basic AGN negative feedback scenario seems not to agree with our results. Although we use a large sample of quasars, we did not find any evidence that the star formation rate is suppressed in the presence of AGN driven outflows on large scale. A possibility is that feedback is effective over much longer timescales than those of single episodes of quasar activity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".