Effect of Magnetic Field on the Accretion Phase of Population III Star Formation
Bibliographic record
Abstract
Abstract We examine the impact of the magnetic field on Population III star formation by varying its strength. We perform simulations with magnetic field strengths ranging from 10−20 G to 10−4 G, in addition to a model without a magnetic field. The simulations are run for >1000–1400 yr after the first protostar forms. In weak-field models, the surrounding disk fragments, forming multiple protostars, and the magnetic field is amplified by the orbital motion and rotation of these protostars. In the model without a magnetic field, frequent fragmentation occurs, and the most massive protostar reaches ∼200 M ⊙. However, in models with a magnetic field, once the magnetic field is amplified, the protostars merge to form a single massive protostar, and no further fragmentation occurs except in the model with the strongest magnetic field. Even after the formation of the single protostar, the magnetic field continues to amplify, leading to the formation of a thick disk supported by magnetic pressure and a global spiral pattern. In models with moderate or strong magnetic fields, a rotating disk can form, but fragmentation does not occur, and a strong magnetic field drives an outflow. However, the range of parameters for both disk formation and outflow driving is very narrow, making their appearance under realistic conditions unlikely. Given the weak magnetic field in the early Universe, Population III stars are expected to form as single stars, surrounded by a thick disk with a spiral pattern. Thus, the magnetic field, regardless of its strength, plays a crucial role in Population III star formation.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".