The ATLAS3D project – XXII. Low-efficiency star formation in early-type galaxies: hydrodynamic models and observations
Bibliographic record
Abstract
We study the global efficiency of star formation in high-resolution hydrodynamical simulations of gas discs embedded in isolated early-type and spiral galaxies. Despite using a universal local law to form stars in the simulations, we find that the early-type galaxies are offset from the spirals on the large-scale Kennicutt relation, and form stars two to five times less efficiently. This offset is in agreement with previous results on morphological quenching: gas discs are more stable against star formation when embedded in early-type galaxies due to the lower disc self-gravity and increased shear. As a result, these gas discs do not fragment into dense clumps and do not reach as high densities as in the spiral galaxies. Even if some molecular gas is present, the fraction of very dense gas (typically above 104 cm−3) is significantly reduced, which explains the overall lower star formation efficiency. We also analyse a sample of local early-type and spiral galaxies, measuring their CO and H i surface densities and their star formation rates as determined by their non-stellar 8 μm emission. As predicted by the simulations, we find that the early-type galaxies are offset from the Kennicutt relation compared to the spirals, with a twice lower efficiency. Finally, we validate our approach by performing a direct comparison between models and observations. We run a simulation designed to mimic the stellar and gaseous properties of NGC 524, a local lenticular galaxy, and find a gas disc structure and global star formation rate in good agreement with the observations. Morphological quenching thus seems to be a robust mechanism, and is also consistent with other observations of a reduced star formation efficiency in early-type galaxies in the COLD GASS survey. This lower efficiency of star formation is not enough to explain the formation of the whole red sequence, but can contribute to the reddening of some galaxies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.011 |
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".