Bibliographic record
Abstract
We report on 8.7 and 7.6 yr of Rossi X-Ray Timing Explorer ( RXTE ) observations of the anomalous X-ray pulsars (AXPs) RXS J170849.0–400910 and 1E 1841–045, respectively. These observations have allowed us to study the long-term timing, pulsed flux, and pulse profile evolution of these objects. We report on four new glitches, one from RXS J170849.0–400910 and three from 1E 1841–045. With nearly all known persistent AXPs now seen to glitch, such behavior is clearly generic to this source class. We show that in terms of fractional frequency change, AXPs are among the most actively glitching neutron stars, with glitch amplitudes in general larger than in radio pulsars. However, in terms of absolute glitch amplitude, AXP glitches are unremarkable. Unlike radio pulsar glitches, AXP glitches can sometimes, though not always, be accompanied by radiative events. We show that the largest observed AXP glitches have recoveries that are unusual among those of radio pulsar glitches, with the combination of recovery time scale and fraction yielding changes in spin-down rates following the glitch similar to, or larger than, the long-term average. We also observed a large long-term fractional increase in the magnitude of the spin-down rate of 1E 1841–045, following its largest glitch, with . These observations are challenging to interpret in standard glitch models, as is the frequent occurence of large glitches given AXPs' high measured temperatures. We speculate that the stellar core may be involved in the largest AXP glitches.
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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 | 0.000 | 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".