The High Time Resolution Universe Pulsar Survey – XVII. PSR J1325−6253, a low eccentricity double neutron star system from an ultra-stripped supernova
Bibliographic record
Abstract
ABSTRACT The observable population of double neutron star (DNS) systems in the Milky Way allow us to understand the nature of supernovae and binary stellar evolution. Until now, all DNS systems in wide orbits (Porb > 1 d) have been found to have orbital eccentricities, e > 0.1. In this paper, we report the discovery of pulsar PSR J1325−6253: a DNS system in a 1.81-d orbit with a surprisingly low eccentricity of just e = 0.064. Through, 1.4 yr of dedicated timing with the Parkes radio telescope we have been able to measure its rate of advance of periastron, $\dot{\omega }=0{_{.}^{\circ}}138\pm 0{_{.}^{\circ}}002\, \mathrm{yr}^{-1}$. If this induced $\dot{\omega }$ is solely due to general relativity then the total mass of the system is, Msys = 2.57 ± 0.06 M⊙. Assuming an edge-on orbit the minimum companion mass is constrained to be Mc, min > 0.98 M⊙ which implies the pulsar mass is Mp, max < 1.59 M⊙. Its location in the P–$\dot{P}$ diagram suggests that, like other DNS systems, PSR J1325−6253 is a recycled pulsar and if its mass is similar to the known examples (>1.3 M⊙), then the companion neutron star is probably less than ∼1.25 M⊙ and the system is inclined at about 50°–60°. The low eccentricity along with the wide orbit of the system strongly favours a formation scenario involving an ultra-stripped supernova explosion.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".