SGRs and AXPs: Evidence for Delayed Amplification of Magnetic Field after Neutron Star Formation?
Bibliographic record
Abstract
We present new analysis of the birth rate of AXPs and SGRS and their associated SNRs. Using Kolmogorov‐Smirnov statistics together with parametric fits based on a robust estimator, we find a birth rate of ~1/(1000 years) for AXPs/SGRs and their associated SNRs. These high rates suggest that all massive stars (greater than ~(23–32)M⊙) give rise to remnants with magnetar‐like fields. Observations indicate a limited fraction of high magnetic fields in these progenitors; thus our study is suggestive of magnetic field amplification. Dynamo mechanisms during the birth of the neutron stars require spin rates much faster than either observations or theory indicate. We propose that massive stars produce neutron stars with normal (~1012 G) magnetic fields, which are then amplified to 1014‐1015 G after a delay of hundreds of years. The amplification is speculated to be a consequence of color ferromagnetism and to occur with a delay after the neutron star core reaches quark deconfinement density (i.e., the quark‐nova scenario). The delayed amplification allows one to interpret simultaneously the high birth rate and high magnetic fields of AXPs/SGRs and their link to massive stars.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".