No evidence for significant age spreads in young massive LMC clusters
Bibliographic record
Abstract
Recent discoveries have put the picture of stellar clusters being simple stellar populations into question. In particular, the color–magnitude diagrams of intermediate age (1–2 Gyr) massive clusters in the Large Magellanic Cloud (LMC) show features that could be interpreted as age spreads of 100–500 Myr. If multiple generations of stars are present in these clusters then, as a consequence, young (<1 Gyr) clusters with similar properties should have age spreads of the same order. In this paper we use archival Hubble Space Telescope (HST) data of eight young massive LMC clusters (NGC 1831, NGC 1847, NGC 1850, NGC 2004, NGC 2100, NGC 2136, NGC 2157 and NGC 2249) to test this hypothesis. We analyzed the color–magnitude diagrams of these clusters and fitted their star formation history to derive upper limits of potential age spreads. We find that none of the clusters analyzed in this work shows evidence for an extended star formation history that would be consistent with the age spreads proposed for intermediate age LMC clusters. Tests with artificial single age clusters show that the fitted age dispersion of the youngest clusters is consistent with spreads that are purely induced by photometric errors. As an additional result we determined a new age of NGC 1850 of ~100 Myr, significantly higher than the commonly used value of about 30 Myr, although consistent with early HST estimates.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".