Transport of Magnetic Fields in Convective, Accreting Supernova Cores
Bibliographic record
Abstract
We consider the amplification and transport of a magnetic field in the collapsed core of a massive star, including both the region between the neutrinosphere and the shock, and the central, opaque core. An analytical argument explains why rapid convective overturns persist within a newly formed neutron star for roughly 10 s (>103 overturns), consistent with recent numerical models. A dynamical balance between turbulent and magnetic stresses within this convective layer corresponds to flux densities in excess of 1015 G. Material accreting onto the core is heated by neutrinos and also becomes strongly convective. We compare the expected magnetic stresses in this convective "gain layer" with those deep inside the neutron core. Buoyant motions of magnetized fluid are greatly aided by the intense neutrino flux. We calculate the transport rate through a medium containing free neutrons, protons, and electrons, in the limiting cases of degenerate or nondegenerate nucleons. Fields stronger than ~1013 G are able to rise through the outer degenerate layers of the neutron core during the last stages of Kelvin-Helmholtz cooling (up to 10 s postcollapse), even though these layers have become stable to convection. We also find the equilibrium shape of a thin magnetic flux rope in the dense hydrostatic atmosphere of the neutron star, along with the critical separation of the footpoints above which the rope undergoes unlimited expansion against gravity. The implications of these results for pulsar magnetism are summarized, and applied to the case of late fallback over the first 103-104 s of the life of a neutron star.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".