H α morphologies of star clusters: a LEGUS study of H ii region evolution time-scales and stochasticity in low-mass clusters
Bibliographic record
Abstract
ABSTRACT The morphology of H ii regions around young star clusters provides insight into the time-scales and physical processes that clear a cluster’s natal gas. We study ∼700 young clusters (≤10 Myr) in three nearby spiral galaxies (NGC 7793, NGC 4395, and NGC 1313) using Hubble Space Telescope (HST) imaging from LEGUS (Legacy ExtraGalactic Ultraviolet Survey). Clusters are classified by their H α morphology (concentrated, partially exposed, no-emission) and whether they have neighbouring clusters (which could affect the clearing time-scales). Through visual inspection of the HST images, and analysis of ages, reddenings, and stellar masses from spectral energy distributions fitting, together with the (U− B), (V − I) colours, we find (1) the median ages indicate a progression from concentrated (∼3 Myr), to partially exposed (∼4 Myr), to no H α emission (>5 Myr), consistent with the expected temporal evolution of H ii regions and previous results. However, (2) similarities in the age distributions for clusters with concentrated and partially exposed H α morphologies imply a short time-scale for gas clearing (≲1 Myr). Also, (3) our cluster sample’s median mass is ∼1000 M⊙, and a significant fraction ($\sim 20{{\ \rm per\ cent}}$) contain one or more bright red sources (presumably supergiants), which can mimic reddening effects. Finally, (4) the median E(B − V) values for clusters with concentrated H α and those without H α emission appear to be more similar than expected (∼0.18 versus ∼0.14, respectively), but when accounting for stochastic effects, clusters without H α emission are less reddened. To mitigate stochastic effects, we experiment with synthesizing more massive clusters by stacking fluxes of clusters within each H α morphological class. Composite isolated clusters also reveal a colour and age progression for H α morphological classes, consistent with analysis of the individual clusters.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".