Identification of a Turnover in the Initial Mass Function of a Young Stellar Cluster Down to 0.5 <i>M</i> <sub>J</sub>
Bibliographic record
Abstract
Abstract A successful theory of star formation should predict the number of objects as a function of their mass produced through star-forming events. Previous studies in star-forming regions and the solar neighborhood have identified a mass function increasing from the hydrogen-burning limit down to about 10 M J. Theory predicts a limit to the fragmentation process, providing a natural turnover in the mass function down to the opacity limit of turbulent fragmentation, thought to be near 1–10 M J. Programs to date have not been sensitive enough to probe the hypothesized opacity limit of fragmentation. We present the first identification of a turnover in the initial mass function below 12 M J within NGC 2024, a young star-forming region. With JWST/NIRCam deep exposures across 0.7–5 μm, we identified several free-floating objects down to roughly 3 M J with sensitivity to 0.5 M J. We present evidence for a double power-law model increasing from about 60 M J to roughly 12 M J, consistent with previous studies, followed by a decrease down to 0.5 M J. Our results support the predictions of star and brown dwarf formation theory, identifying the theoretical turnover in the mass function and suggesting the fundamental limit of turbulent fragmentation to be near 3 M J.
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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 | 0.000 |
| 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) | 0.002 | 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".