Kiloparsec-Scale Variations in the Star Formation Efficiency of Dense Gas: The Antennae Galaxies (NGC 4038/39)
Bibliographic record
Abstract
Abstract We study the relationship between dense gas and star formation in the Antennae galaxies by comparing Atacama large millimeter/submillimeter array (ALMA) observations of dense-gas tracers (HCN, HCO + , and HNC J = 1–0) with the total infrared luminosity ( L TIR ) calculated using data from the Herschel Space Observatory and the Spitzer Space Telescope . We compare the luminosities of our star formation rate (SFR) and gas tracers using aperture photometry and employing two methods for defining apertures. We taper the ALMA data set to match the resolution of our L TIR maps and present new detections of dense-gas emission from complexes in the overlap and western arm regions. Using Owens Valley Radio Observatory CO J = 1–0 data, we compare with the total molecular gas content, , and calculate star formation efficiencies and dense-gas mass fractions for these different regions. We derive HCN, HCO + , and HNC upper limits for apertures where emission was not significantly detected, because we expect that emission from dense gas should be present in most star-forming regions. The Antennae extends the linear relationship found in previous studies. The ratio varies by up to a factor of ∼10 across different regions of the Antennae, implying variations in the star formation efficiency of dense gas, with the nuclei, NGC 4038 and NGC 4039, showing the lowest SFE dense (0.44 and 0.70 × 10 −8 yr −1 ). The nuclei also exhibit the highest dense-gas fractions (∼9.1% and ∼7.9%).
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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 | 0.001 | 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 | 0.000 |
| 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".