On the Constancy of the Characteristic Mass of Young Stars
Bibliographic record
Abstract
The characteristic mass M c in the stellar initial mass function (IMF) is about constant for most star-forming regions. Numerical simulations consistently show a proportionality between M c and the thermal Jeans mass M J at the time of cloud fragmentation, but no models have explained how it can be the same in diverse conditions. Here we show that M J depends weakly on density, temperature, metallicity, and radiation field in three environments: the dense cores where stars form, larger star-forming regions ranging from GMCs to galactic disks, and the interiors of H II regions and super star clusters. In dense cores, the quantity T 3/2 n −1/2 that appears in M J scales with core density as n 0.25 or with radiation density as U 0.1 at the density where dust and gas come into thermal equilibrium. On larger scales, this quantity varies with ambient density as n −0.05 and ambient radiation field as U −0.033 when the Kennicutt-Schmidt law of star formation determines U ( n ) . In super star clusters with ionization and compression of prestellar globules, M J varies as the 0.13 power of the cluster column density. These weak dependencies on n , U , and column density imply that most environmental variations affect the thermal Jeans mass by at most a factor of ~2. Cosmological increases in M J , which have been suggested by observations, may be explained if the star formation efficiency is systematically higher at high redshift for a given density and pressure, if dust grains are smaller at lower metallicity, and so hotter for a given radiation field, or if small prestellar cores are more severely ionized in extreme starburst conditions.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".