Observing AGN feedback with CO intensity mapping
Bibliographic record
Abstract
ABSTRACT Current models of galaxy formation require star formation in high-mass galaxies to be limited by poorly understood mechanisms of quasar feedback. Feedback processes can be studied by examining the molecular gas content of AGN hosts through the CO rotational ladder, but the complexity of these observations means that current data are limited to only extremely CO-bright objects. Upcoming CO intensity mapping experiments offer an opportunity for a less biased probe of quasar feedback. By correlating intensity maps with spectroscopic AGN surveys, we can obtain a measurement of the mean CO luminosity of a large population of quasars simultaneously. We show that experiments like COMAP, CCAT-prime, and CONCERTO have enough sensitivity to detect this cross-correlation if existing AGN observations are representative of the whole population, and to place interesting upper limits if they are not. Future surveys will be able to increase the precision of these measurements by orders of magnitude, allowing detailed studies of quasar properties across a wide range of cosmic history.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".