Formation of Double Neutron Star Systems
Bibliographic record
Abstract
Abstract Double neutron star (DNS) systems represent extreme physical objects and the endpoint of an exotic journey of stellar evolution and binary interactions. Large numbers of DNS systems and their mergers are anticipated to be discovered using the Square Kilometre Array searching for radio pulsars, and the high-frequency gravitational wave detectors (LIGO/VIRGO), respectively. Here we discuss all key properties of DNS systems, as well as selection effects, and combine the latest observational data with new theoretical progress on various physical processes with the aim of advancing our knowledge on their formation. We examine key interactions of their progenitor systems and evaluate their accretion history during the high-mass X-ray binary stage, the common envelope phase, and the subsequent Case BB mass transfer, and argue that the first-formed NSs have accreted at most . We investigate DNS masses, spins, and velocities, and in particular correlations between spin period, orbital period, and eccentricity. Numerous Monte Carlo simulations of the second supernova (SN) events are performed to extrapolate pre-SN stellar properties and probe the explosions. All known close-orbit DNS systems are consistent with ultra-stripped exploding stars. Although their resulting NS kicks are often small, we demonstrate a large spread in kick magnitudes that may, in general, depend on the past interaction history of the exploding star and thus correlate with the NS mass. We analyze and discuss NS kick directions based on our SN simulations. Finally, we discuss the terminal evolution of close-orbit DNS systems until they merge and possibly produce a short γ -ray burst.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".