Do spiral arms enhance star formation efficiency?
Bibliographic record
Abstract
Spiral arms, as those of our own Milky Way, are some of the most spectacular features in disc galaxies. It has been argued that star formation should proceed more efficiently in spiral arms as a result of gas compression. Yet, observational studies have so far yielded contradictory results. Here, we examine arm/interarm surface density contrasts at ∼100 pc resolution in 28 spiral galaxies from the PHANGS survey. We find that the arm/interarm contrast in stellar mass surface density (Σ ⋆ ) is very modest, typically a few tens of percent. This is much smaller than the contrasts measured for molecular gas (Σ mol ) or star formation rate (Σ SFR ) surface density, which typically reach a factor of ∼2 − 3. However, Σ mol and Σ SFR contrasts show a significant correlation with the enhancement in Σ ⋆ , suggesting that the small stellar contrast largely dictates the stronger accumulation of gas and star formation. All these contrasts increase for grand-design spirals compared to multi-armed and flocculent systems (and for galaxies with high stellar mass). The median star formation efficiency (SFE) of the molecular gas is 16% higher in spiral arms than in interarm regions, with a large scatter, and the contrast increases significantly (median SFE contrast 2.34) for regions of particularly enhanced stellar contrast (Σ ⋆ contrast > 1.97). The molecular-to-atomic gas ratio (Σ mol /Σ atom ) is higher in spiral arms, pointing to a transformation of atomic to molecular gas. As a consequence, the total gas contrast (Σ mol + Σ atom ) slightly drops compared to Σ mol (median 4% lower, working at ∼kpc resolution), while the SFE contrast increases when we include atomic gas (median 8% higher than for Σ mol ). The contrasts show important fluctuations with galactocentric radius. We confirm that our results are robust against a number of effects, such as spiral mask width, tracers, resolution, and binning. In conclusion, the boost in the SFE of molecular gas in spiral arms is generally modest or absent, except for locations with exceptionally large stellar contrasts.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".