The NANOGrav 11-year Data Set: Pulse Profile Variability
Bibliographic record
Abstract
Abstract Access to 50 years of data has led to the discovery of pulsar emission and rotation variability on timescales of months and years. Most of this long-term variability has been seen in long-period pulsars, with relatively little focus on recycled millisecond pulsars. We have analyzed a 38-pulsar subset of the 45 millisecond pulsars in the NANOGrav 11-year data set, in order to review their pulse profile stability. The most variability, on any timescale, is seen in PSRs J1713+0747, B1937+21, and J2145−0750. The strongest evidence for long-timescale pulse profile changes is seen in PSRs B1937+21 and J1643−1224. We have focused our analyses on these four pulsars in an attempt to elucidate the causes of their profile variability. Effects of scintillation seem to be responsible for the profile modifications of PSR J2145−0750. We see evidence that imperfect polarization calibration contributes to the profile variability of PSRs J1713+0747 and B1937+21, along with radio frequency interference around 2 GHz, but find that propagation effects also have an influence. The changes seen in PSR J1643−1224 have been reported previously, yet elude explanation beyond their astrophysical nature. Regardless of cause, unmodeled pulse profile changes are detrimental to the accuracy of pulsar timing and must be incorporated into the timing models where possible.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".