Testable Predictions of Outside-in Age Gradients in Dwarf Galaxies of All Types
Bibliographic record
Abstract
Abstract We use a sample of 73 simulated satellite and central dwarf galaxies spanning a stellar mass range of 105.3–109.1 M ⊙ to investigate the origin of their stellar age gradients. We find that dwarf galaxies often form their stars “inside-out,” i.e., the stars form at successively larger radii over time. However, the oldest stars get reshuffled beyond the star-forming radius by fluctuations in the gravitational potential well caused by stellar feedback (the same mechanisms that cause dwarfs to form dark matter cores). The result is that many dwarfs appear to have an “outside-in” age gradient at z = 0, with younger stellar populations more centrally concentrated. However, for the reshuffled galaxies with the most extended star formation, young stars can form out to the large radii to which the old stars have been reshuffled, erasing the age gradient. We find that major mergers do not play a significant role in setting the age gradients of dwarfs. We find similar age gradient trends in satellites and field dwarfs, suggesting that environment plays only a minor role, if any. Finally, we find that the age gradient trends are imprinted on the galaxies at later times, suggesting that the stellar reshuffling dominates after the galaxies have formed 50% of their stellar mass. The later reshuffling is at odds with results from the fire-2 simulations. Hence, age gradients offer a test of current star formation and feedback models that can be probed via observations of resolved stellar populations.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".