The mass dependence of star formation histories in barred spiral galaxies
Bibliographic record
Abstract
We performed a series of 29 gas dynamical simulations of disc galaxies, barred and unbarred, with various stellar masses, to study the impact of the bar on star formation history. Unbarred galaxies evolve very smoothly, with a star formation rate (SFR) that varies by at most a factor of 3 over a period of 2 Gyr. The evolution of barred galaxies is much more irregular, especially at high stellar masses. In these galaxies, the bar drives a substantial amount of gas towards the centre, resulting in a high SFR, and producing a starburst in the most massive galaxies. Most of the gas is converted into stars, and gas exhaustion leads to a rapid drop of star formation after the starburst. In massive barred galaxies (stellar mass |$M_{\ast }>2{\times} 10^{10}\,{\mathrm{M}_{\odot}}$|) the large amount of gas funnelled towards the centre is completely consumed by the starburst, while in lower mass barred galaxies it is only partially consumed. Gas concentration is thus higher in lower mass barred galaxies than it is in higher mass ones. Even though unbarred galaxies funnelled less gas towards their centre, the lower SFR allows this gas to accumulate. At late times, the star formation efficiency is higher in barred galaxies than unbarred ones, enabling these galaxies to maintain a higher SFR with a smaller gas supply. Several properties, such as the global SFR, central SFR, or central gas concentration, vary monotonically with time for unbarred galaxies, but not for barred galaxies. Therefore one must be careful when comparing barred and unbarred galaxies that share one observational property, since these galaxies might be at very different stages of their respective evolution.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".