VALIDATION OF THE EQUILIBRIUM MODEL FOR GALAXY EVOLUTION TO<i>z</i>∼ 3 THROUGH MOLECULAR GAS AND DUST OBSERVATIONS OF LENSED STAR-FORMING GALAXIES
Bibliographic record
Abstract
We combine IRAM Plateau de Bure Interferometer and Herschel PACS and SPIRE measurements to study the dust and gas contents of high-redshift star forming galaxies. We present new observations for a sample of 17 lensed galaxies at z=1.4-3.1, which allow us to directly probe the cold ISM of normal star-forming galaxies with stellar masses of ~10^10Msun, a regime otherwise not (yet) accessible by individual detections in Herschel and molecular gas studies. The lensed galaxies are combined with reference samples of sub-millimeter and normal z~1-2 star-forming galaxies with similar far-infrared photometry to study the gas and dust properties of galaxies in the SFR-M*-redshift parameter space. The mean gas depletion timescale of main sequence galaxies at z>2 is measured to be only ~450Myr, a factor of ~1.5 (~5) shorter than at z=1 (z=0), in agreement with a (1+z)^-1 scaling. The mean gas mass fraction at z=2.8 is 40+/-15% (44% after incompleteness correction), suggesting a flattening or even a reversal of the trend of increasing gas fractions with redshift recently observed up to z~2. The depletion timescale and gas fractions of the z>2 normal star-forming galaxies can be explained under the "equilibrium model" for galaxy evolution, in which the gas reservoir of galaxies is the primary driver of the redshift evolution of specific star formation rates. Due to their high star formation efficiencies and low metallicities, the z>2 lensed galaxies have warm dust despite being located on the star formation main sequence. At fixed metallicity, they also have a gas-to-dust ratio 1.7 times larger than observed locally when using the same standard techniques, suggesting that applying the local calibration of the relation between gas-to-dust ratio and metallicity to infer the molecular gas mass of high redshift galaxies may lead to systematic differences with CO-based estimates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".