The High Time Resolution Universe Pulsar Survey – XVI. Discovery and timing of 40 pulsars from the southern Galactic plane
Bibliographic record
Abstract
ABSTRACT We present the results of processing an additional 44 per cent of the High Time Resolution Universe South Low Latitude (HTRU-S LowLat) pulsar survey, the most sensitive blind pulsar survey of the southern Galactic plane to date. Our partially coherent segmented acceleration search pipeline is designed to enable the discovery of pulsars in short, highly accelerated orbits, while our 72-min integration lengths will allow us to discover pulsars at the lower end of the pulsar luminosity distribution. We report the discovery of 40 pulsars, including three millisecond pulsar-white dwarf binary systems (PSRs J1537−5312, J1547−5709, and J1618−4624), a black-widow binary system (PSR J1745−23) and a candidate black-widow binary system (PSR J1727−2951), a glitching pulsar (PSR J1706−4434), an eclipsing binary pulsar with a 1.5-yr orbital period (PSR J1653−45), and a pair of long spin-period binary pulsars which display either nulling or intermittent behaviour (PSRs J1812−15 and J1831−04). We show that the total population of 100 pulsars discovered in the HTRU-S LowLat survey to date represents both an older and lower luminosity population, and indicates that we have yet to reach the bottom of the luminosity distribution function. We present evaluations of the performance of our search technique and of the overall yield of the survey, considering the 94 per cent of the survey which we have processed to date. We show that our pulsar yield falls below earlier predictions by approximately 25 per cent (especially in the case of millisecond pulsars), and discuss explanations for this discrepancy as well as future adaptations in RFI mitigation and searching techniques which may address these shortfalls.
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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 | 0.001 | 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 | 0.000 |
| 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".