Centrally concentrated star formation in young clusters
Bibliographic record
Abstract
The study of star cluster evolution necessitates modeling how their density profiles develop from their natal gas distribution. Observational evidence indicates that many star clusters follow a Plummer-like density profile. However, most studies have focused on the phase after gas ejection, neglecting the influence of gas on early dynamical evolution. We investigate the development of star clusters forming within gas clouds, particularly those with a centrally concentrated gas profile. Simulations were conducted using the Torch framework, integrating the FLASH magnetohydrodynamics code into AMUSE. This permitted detailed modeling of star formation, stellar evolution, stellar dynamics, radiative transfer, and gas magnetohydrodynamics. We study the collapse of centrally concentrated, turbulent spheres with a total mass of 2.5 × 10 3 M ⊙ , investigating the effects of varying numerical resolution and star formation scenarios. The free-fall time is shorter at the center than at the edges of the cloud, with a minimum value of 0.55 Myr. The key conclusions from this study are: (1) the final stellar density profile is more centrally concentrated than was analytically predicted, reflecting the role of global gas collapse and feedback; (2) subclusters can initially form even in centrally concentrated gas clouds; (3) gas collapses globally toward the center on the central free-fall timescale, contradicting the assumption in analytical models of local fragmentation and star formation; and (4) the mass of the most massive star formed is directly correlated with the cluster effective radius and inversely correlated with the velocity dispersion, while the duration of star formation correlates with the star formation efficiency.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".