A Population Of Non-Recycled Pulsars Originating In Globular Clusters
Bibliographic record
Abstract
We explore the enigmatic population of long-period, apparently non-recycled pulsars in globular clusters, building on recent work by Boyles et al. This population is difficult to explain if it formed through typical core-collapse supernovae, leading many authors to invoke electron capture supernovae. While Boyles et al. dealt only with non-recycled pulsars in clusters, we focus on the pulsars that originated in clusters but then escaped into the field of the Galaxy due to the kicks they receive at birth. The magnitude of the kick induced by electron capture supernovae is not well known, so we explore various models for the kick velocity distribution and size of the population. The most realistic models are those where the kick velocity is 10 km s–1 and where the number of pulsars scales with the luminosity of the cluster (as a proxy for cluster mass). This is in good agreement with other estimates of the electron capture supernovae kick velocity. We simulate a number of large-area pulsar surveys to determine if a population of pulsars originating in clusters could be identified as being separate from normal disk pulsars. We find that the spatial and kinematical properties of the population could be used, but only if large numbers of pulsars are detected. In fact, even the most optimistic surveys carried out with the future Square Kilometer Array are likely to detect <10% of the total population, so the prospects for identifying these as a separate group of pulsars are presently poor.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".