Microstructure of pulsar radio pulses measured with a time resolution of 62.5 ns at 1650 MHz
Bibliographic record
Abstract
We present an analysis of pulsar observations carried out on two frequency channels at 1634 MHz and 1650 MHz with a time resolution of 62.5 ns on the 70-m radio telescope of the NASA Deep Space Network in Tidbinbilla. The data were recorded using the S2 system, intended primarily for VLBI observations. Microstructure with characteristic timescales of 270, 80, and 150 µs was detected in pulsars B0833-45, B1749-28, and B1933 + 16, respectively. The distribution of microstructure timescales for the Vela pulsar (B0833-45) is characterized by a gradual growth with decreasing timescale to 200 µs; the distribution has a maximum at 20–200 µs and falls off sharply for timescales below 20 µs. The statistical relation between the microstructure modulation index m and the corresponding timescale τ µ can be approximated by the power law dependence R∝τ ⊙ 0.5 ; i.e., the intensity is higher for micropulses with longer durations. This contradicts the predictions of nonlinear models for the formation of micropulses by supercompact soliton wave packets. In all the pulsars studied, the time delays of the micropulses between the two frequency channels deviate from the expected dispersion laws for the interstellar plasma. In particular, the micropulses in the low-frequency channel arrive earlier than predicted by the dispersion measures derived previously from the mean pulse profiles. The deviation from the dispersion delay is determined most accurately for B0833-45, and is 4.9±0.2 µs. Such anomalous delays are probably associated with the effects of propagation of the radio emission within the pulsar magnetosphere.
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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) | 0.000 | 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".