Discovery of a Young, Highly Scattered Pulsar PSR J1032-5804 with the Australian Square Kilometre Array Pathfinder
Bibliographic record
Abstract
Abstract We report the discovery of a young, highly scattered pulsar in a search for highly circularly polarized radio sources as part of the Australian Square Kilometre Array Pathfinder Variables and Slow Transients survey. In follow-up observations with the Parkes radio telescope, Murriyang, we identified PSR J1032−5804 and measured a period of 78.7 ms, a dispersion measure of 819 ± 4 pc cm−3, a rotation measure of −2000 ± 1 rad m−2, and a characteristic age of 34.6 kyr. We found a pulse scattering timescale at 3 GHz of ∼22 ms, implying a timescale at 1 GHz of ∼3845 ms, which is the third most scattered pulsar known and explains its nondetection in previous pulsar surveys. We discuss the identification of a possible pulsar wind nebula and supernova remnant in the pulsar’s local environment by analyzing the pulsar spectral energy distribution and the surrounding extended emission from multiwavelength images. Our result highlights the possibility of identifying extremely scattered pulsars from radio continuum images. Ongoing and future large-scale radio continuum surveys will offer us an unprecedented opportunity to find more extreme pulsars (e.g., highly scattered, highly intermittent, and highly accelerated), which will enhance our understanding of the characteristics of pulsars and the interstellar medium.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".