A Scintillation Arc Survey of 22 Pulsars with Low to Moderate Dispersion Measures
Bibliographic record
Abstract
Abstract Context. By providing information about the location of scattering material along the line of sight (LoS) to pulsars, scintillation arcs are a powerful tool for exploring the distribution of ionized material in the interstellar medium (ISM). Here, we present observations that probe the ionized ISM on scales of ∼0.001–30 au. Aims. We have surveyed pulsars for scintillation arcs in a relatively unbiased sample with DM < 100 pc cm−3. We present multifrequency observations of 22 low to moderate DM pulsars. Many of the 54 observations were also observed at another frequency within a few days. Methods. For all observations, we present dynamic spectra, autocorrelation functions, and secondary spectra. We analyze these data products to obtain scintillation bandwidths, pulse broadening times, and arc curvatures. Results. We detect definite or probable scintillation arcs in 19 of the 22 pulsars and 34 of the 54 observations, showing that scintillation arcs are a prevalent phenomenon. The arcs are better defined in low DM pulsars. We show that well-defined arcs do not directly imply anisotropy of scattering. Only the presence of reverse arclets and a deep valley along the delay axis, which occurs in about 20% of the pulsars in the sample, indicates substantial anisotropy of scattering. Conclusions. The survey demonstrates substantial patchiness of the ionized ISM on both astronomical-unit-size scales transverse to the LoS and on ∼100 pc scales along it. We see little evidence for distributed scattering along most lines of sight in the survey.
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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 | 0.001 |
| 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) | 0.001 | 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".