MOLECULAR AND ATOMIC LINE SURVEYS OF GALAXIES. I. THE DENSE, STAR-FORMING GAS PHASE AS A BEACON
Bibliographic record
Abstract
We predict the space density of molecular gas reservoirs in the universe and place a lower limit on the number counts of carbon monoxide (CO), hydrogen cyanide (HCN) molecular, and [C ii ] atomic emission lines in blind redshift surveys in the submillimeter–centimeter spectral regime. Our model uses (1) recently available HCN spectral line energy distributions (SLEDs) of local luminous infrared galaxies (LIRGs, L IR > 10 11 L ☉ ), (2) a value for ⋆ = SFR/ M dense (H 2 ) provided by new developments in the study of star formation feedback on the interstellar medium, and (3) a model for the evolution of the infrared luminosity density. Minimal "emergent" CO SLEDs from the dense gas reservoirs expected in all star-forming systems in the universe are then computed from the HCN SLEDs since warm, HCN-bright gas will necessarily be CO-bright, with the dense star-forming gas phase setting an obvious minimum to the total molecular gas mass of any star-forming galaxy. We include [C ii ] as the most important of the far-infrared cooling lines. Optimal blind surveys with the Atacama Large Millimeter Array (ALMA) could potentially detect very distant ( z ∼ 10–12) [C ii ] emitters in the ⩾ULIRG galaxy class at a rate of ∼0.1–1 hr −1 (although this prediction is strongly dependent on the star formation and enrichment history at this early epoch), whereas the (high-frequency) Square Kilometer Array will be capable of blindly detecting z > 3 low- J CO emitters at a rate of ∼40–70 hr −1 . The [C ii ] line holds special promise for detecting metal-poor systems with extensive reservoirs of CO-dark molecular gas where detection rates with ALMA can reach up to 2–7 hr −1 in Bands 4–6.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".