Study of 72 Pulsars Discovered in the PALFA Survey: Timing Analysis, Glitch Activity, Emission Variability, and a Pulsar in an Eccentric Binary
Bibliographic record
Abstract
Abstract We present new discoveries and results from long-term timing of 72 pulsars discovered in the Pulsar Arecibo L -band Feed Array (PALFA) survey, including precise determination of astrometric and spin parameters, and flux density and scatter broadening measurements at 1.4 GHz. Notable discoveries include two young pulsars (characteristic ages ∼30 kyr) with no apparent supernova remnant associations, three mode-changing, 12 nulling and two intermittent pulsars. We detected eight glitches in five pulsars. Among them is PSR J1939+2609, an apparently old pulsar (characteristic age ∼1 Gy), and PSR J1954+2529, which likely belongs to a newly emerging class of binary pulsars. The latter is the only pulsar among the 72 that is clearly not isolated: a nonrecycled neutron star with a 931 ms spin period in an eccentric ( e = 0.114) wide ( P b = 82.7 days) orbit with a companion of undetermined nature having a minimum mass of ∼0.6 M ⊙ . Since operations at Arecibo ceased in 2020 August, we give a final tally of PALFA sky coverage, and compare its 207 pulsar discoveries to the known population. On average, they are 50% more distant than other Galactic plane radio pulsars; PALFA millisecond pulsars (MSPs) have twice the dispersion measure per unit spin period than the known population of MSP in the plane. The four intermittent pulsars discovered by PALFA more than double the population of such objects, which should help to improve our understanding of pulsar magnetosphere physics. The statistics for these, rotating radio transients, and nulling pulsars suggest that there are many more of these objects in the Galaxy than was previously thought.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".