Variable scintillation arcs of millisecond pulsars observed with the Large European Array for Pulsars
Bibliographic record
Abstract
ABSTRACT We present the first large sample of scintillation arcs in millisecond pulsars (MSPs), analysing 12 sources observed with the Large European Array for Pulsars (LEAP), and the Effelsberg 100-m telescope. We estimate the delays from multipath propagation, measuring significant correlated changes in scattering time-scales over a 10 yr time span. Many sources show compact concentrations of power in the secondary spectrum, which in PSRs J0613−0200 and J1600−3053 can be tracked between observations, and are consistent with compact scattering at fixed angular positions. Other sources such as PSRs J1643−1224 and J0621+1002 show diffuse, asymmetric arcs which are likely related to phase-gradients across the scattering screen. PSR B1937+21 shows at least three distinct screens which dominate at different times and evidence of varying screen axes or multiscreen interactions. We model annual and orbital arc curvature variations in PSR J0613−0200, providing a measurement of the longitude of ascending node, resolving the sense of the orbital inclination, where our best-fit model is of a screen with variable axis of anisotropy over time, corresponding to changes in the scattering of the source. Unmodelled variations of the screen’s axis of anisotropy are likely to be a limiting factor in determining orbital parameters with scintillation, requiring careful consideration of variable screen properties, or independent very long baseline interferometry (VLBI) measurements. Long-term scintillation studies such as this serve as a complementary tool to pulsar timing, to measure a source of correlated noise for pulsar timing arrays, solve pulsar orbits, and to understand the astrophysical origin of scattering screens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".