Meissner effect and vortex dynamics in quark stars
Bibliographic record
Abstract
We present a new model for soft gamma-ray repeaters based on a quark star born with temperatures above the critical value (Tc) for the onset of the colour-flavor locked superconductivity. The quark star then quickly cools below Tc, expelling a fraction of the surface magnetic field via the Meissner effect. We show that if a small fraction (≤) of the surface magnetic field () is expelled, it quickly decays via magnetic reconnection and heats up the quark star surface to temperatures >. Created pairs annihilate into gamma rays emitted in a giant burst (the first burst in our model), with a luminosity of ~. Subsequent bursts result from the restructuring of the surface magnetic field following the formation and relaxation of a vortex lattice which confines the internal magnetic field. During this phase, energy is sporadically released as a consequence of magnetic reconnection events in the entangled surface magnetic field as it evolves into a smooth, more stable, configuration. The star eventually enters a quiescent phase in which energy is continuously supplied by vortex annihilation at the surface. As the star spins down, the outermost vortex lines will be pushed to the surface where they annihilate and release their confined magnetic field. We show that the corresponding luminosity is for a typical soft gamma-ray repeater spinning with a period of and a surface magnetic field not exceeding . Our model can be applied to any situation where a quark star is generated. We discuss the connection between anomalous X-ray pulsars and soft gamma-ray repeaters in the context of our model.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".