Bibliographic record
Abstract
We develop a theoretical model that explains the formation of hot coronae around strongly magnetized neutron stars—magnetars. The starquakes of a magnetar shear its external magnetic field, which becomes nonpotential and threaded by an electric current. Once twisted, the magnetosphere cannot untwist immediately because of its self-induction. The self-induction electric field lifts particles from the stellar surface, accelerates them, and initiates avalanches of pair creation in the magnetosphere. The created plasma corona maintains the electric current demanded by ∇ × and regulates the self-induction EMF by screening. This corona persists in dynamic equilibrium: it is continually lost to the stellar surface on the light crossing time ~10 -4 s and replenished with new particles. In essence, the twisted magnetosphere acts as an accelerator that converts the toroidal field energy to particle kinetic energy. Using a direct numerical experiment, we show that the corona self-organizes quickly (on a millisecond timescale) into a quasi-steady state, with voltage 10 8 -10 9 V along the magnetic lines. The voltage is maintained near the threshold for e ± discharge. The heating rate of the corona is ~10 36 ergs s -1 , in agreement with the observed persistent, high-energy output of magnetars. We deduce that a static twist that is suddenly implanted into the magnetosphere will decay on a timescale of 1-10 yr. The particles accelerated in the corona impact the solid crust, knock out protons, and regulate the column density of the hydrostatic atmosphere of the star. The transition layer between the atmosphere and corona may be hot enough to create additional e ± pairs. This layer can be the source of the observed 100 keV emission from magnetars. The corona emits curvature radiation and can supply the observed IR-optical luminosity.
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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 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".