COLDz: Shape of the CO Luminosity Function at High Redshift and the Cold Gas History of the Universe
Bibliographic record
Abstract
We report the first detailed measurement of the shape of the CO luminosity function at high redshift, based on >320 hr of the NSF's Karl G. Jansky Very Large Array (VLA) observations over an area of ~60 arcmin2 taken as part of the CO Luminosity Density at High Redshift (COLDz) survey. COLDz "blindly" selects galaxies based on their cold gas content through CO(J=1?0) emission at z~2-3 and CO(J=2?1) at z~5-7 down to a CO luminosity limit of log(L'CO/K km s-1 pc2)?9.5. We find that the characteristic luminosity and bright end of the CO luminosity function are substantially higher than predicted by semi-analytical models, but consistent with empirical estimates based on the infrared luminosity function at z~2. We also present the currently most reliable measurement of the cosmic density of cold gas in galaxies at early epochs, i.e., the cold gas history of the universe, as determined over a large cosmic volume of ~375,000 Mpc3. Our measurements are in agreement with an increase of the cold gas density from z~0 to z~2-3, followed by a possible decline towards z~5-7. These findings are consistent with recent surveys based on higher-J CO line measurements, upon which COLDz improves in terms of statistical uncertainties by probing ~50-100 times larger areas and in the reliability of total gas mass estimates by probing the low-J CO lines accessible to the VLA. Our results thus appear to suggest that the cosmic star-formation rate density follows an increased cold molecular gas content in galaxies towards its peak about 10 billion years ago, and that its decline towards the earliest epochs is likely related to a lower overall amount of cold molecular gas (as traced by CO) bound in galaxies towards the first billion years after the Big Bang.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".