Molecular cloud evolution - IV. Magnetic fields, ambipolar diffusion and the star formation efficiency
Bibliographic record
Abstract
We investigate the formation and evolution of giant molecular clouds (GMCs) by the collision of convergent warm neutral medium (WNM) streams in the interstellar medium, in the presence of magnetic fields and ambipolar diffusion (AD), focusing on the evolution of the star formation rate and efficiency (SFE), as well as of the mass-to-magnetic-flux ratio (M2FR) in the forming clouds. We find that (1) clouds formed by supercritical inflow streams proceed directly to collapse, while clouds formed by subcritical streams first contract and then re-expand, oscillating on the scale of tens of Myr; (2) our suite of simulations with the initial magnetic field strength of 2, 3 and 4 μ G show that only supercritical or marginal critical streams lead to reasonable star forming rates. This result is not altered by the inclusion of AD; (3) the GMC’s M2FR is a generally increasing function of time, whose growth rate depends on the details of how mass is added to the GMC from the WNM; (4) the M2FR is a highly fluctuating function of position in the clouds. This implies that a significant fraction of a cloud’s mass may remain magnetically supported, while SF occurs in the supercritical regions that are not supported; (5) in our simulations, the SFE approaches stationarity, because mass is added to the GMC at a similar rate to which it converts mass to stars. In such an approximately stationary regime, we find that the SFE provides a proxy of the supercritical mass fraction in the cloud; and (6) the low-M2FR regions exhibit buoyancy within the gravitationally contracting GMCs, so that the latter naturally segregate into a high-density, high-M2FR ‘core’ and a low-density, low-M2FR ‘envelope’, without the intervention of AD.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".