Pulsar microstructure and its quasi-periodicities with the S2 VLBI system at a resolution of 62.5 nanoseconds
Bibliographic record
Abstract
The microstructure of PSRs B0950+08, B1133+16, and B1929+10 was investigated for a large number of pulses with a time resolution of 62.5 ns, by far the highest for any such statistical study yet. Using the S2 VLBI system, the pulsars were observed in absentia with the 70-m NASA/DSN radio telescope at Tidbinbilla, Australia, at a frequency of 1650 MHz. The data were continuously recorded at the Nyquist sampling rate with 2-bit sampling in the upper and lower sidebands each 16 MHz wide, and written on magnetic tape. The data were played back via the S2 Tape-to-Computer Interface at CRESTech/York University, dedispersed before detection and analyzed. For PSR B1929+10 we found as yet unreported broad microstructure in the average cross-correlation function (CCF) with a characteristic time scale of 90+-10 mcs. On a finer scale PSRs B1133+16 (component II) and B1929+10 show narrow microstructure with a characteristic time scale in the CCFs of 10+-2 mcs and 8+-2 mcs, respectively, the shortest found in the average CCF or autocorrelation function (ACF) for any pulsar, apart perhaps from the Crab pulsar. Histograms of microstructure widths are skewed heavily toward shorter time scales but display a sharp cutoff. The shortest micropulses have widths between 2 and 7 mcs. The time scales of the broad, narrow, and shortest micropulses are, at least partly, related to the widths of the components of the integrated profiles and the subpulse widths. In general, the micropulse modulation index decreases with the micropulse width. No nanopulses or unresolved pulse spikes were detected.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".