Predictions for the CO emission of galaxies from a coupled simulation of galaxy formation and photon-dominated regions
Bibliographic record
Abstract
We combine the galaxy formation model galform with the photon-dominated region code ucl−pdr to study the emission from the rotational transitions of 12CO (CO) in galaxies from z = 0 to z = 6 in the Λcold dark matter framework. galform is used to predict the molecular (H2) and atomic hydrogen (H i) gas contents of galaxies using the pressure-based empirical star formation relation of Blitz & Rosolowsky. From the predicted H2 mass and the conditions in the interstellar medium, we estimate the CO emission in the rotational transitions 1–0 to 10–9 by applying the ucl−pdr model to each galaxy. We find that deviations from the Milky Way CO–H2 conversion factor come mainly from variations in metallicity, and in the average gas and star formation rate surface densities. In the local universe, the model predicts a CO(1–0) luminosity function (LF), CO-to-total infrared (IR) luminosity ratios for multiple CO lines and a CO spectral line energy distribution (SLED) which are in good agreement with observations of luminous and ultra-luminous IR galaxies. At high redshifts, the predicted CO SLED of the brightest IR galaxies reproduces the shape and normalization of the observed CO SLED. The model predicts little evolution in the CO-to-IR luminosity ratio for different CO transitions, in good agreement with observations up to z ≈ 5. We use this new hybrid model to explore the potential of using colour-selected samples of high-redshift star-forming galaxies to characterize the evolution of the cold gas mass in galaxies through observations with the Atacama Large Millimetre Array.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".