Embedded Young Massive Star Clusters in the Antennae Merger
Bibliographic record
Abstract
Abstract The properties of young massive clusters (YMCs) are key to understanding the star formation mechanism in starburst systems, especially mergers. We present Atacama Large Millimeter/submillimeter Array high-resolution (∼10 pc) continuum (100 and 345 GHz) data of YMCs in the overlap region of the Antennae galaxy. We identify six sources in the overlap region, including two sources that lie in the same giant molecular cloud (GMC). These YMCs correspond well with radio sources in lower-resolution continuum (100 and 220 GHz) images at GMC scales (∼60 pc). We find most of these YMCs are bound clusters through virial analysis. We estimate their ages to be ∼1 Myr and that they are either embedded or just beginning to emerge from their parent cloud. We also compare each radio source with a Paβ source, and find they have consistent total ionizing photon numbers, which indicates they are tracing the same physical source. By comparing the free–free emission at ∼10 pc scale and ∼60 pc scale, we find that ∼50% of the free–free emission in GMCs actually comes from these YMCs. This indicates that roughly half of the stars in massive GMCs are formed in bound clusters. We further explore the mass correlation between YMCs and GMCs in the Antennae and find it generally agrees with the predictions of the star cluster simulations. The most massive YMC has a stellar mass that is 1%–5% of its host GMC mass.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".