Evolutionary Origins of Binary Neutron Star Mergers: Effects of Common Envelope Efficiency and Metallicity
Bibliographic record
Abstract
Abstract The formation histories of compact binary mergers, especially stellar-mass binary black hole mergers, have recently come under increased scrutiny and revision. We revisit the question of the dominant formation channel and efficiency of forming binary neutron star (BNS) mergers. We use the stellar and binary evolution code MESA and implement a detailed method for common envelope and mass transfer. We perform simulations for donor masses between 7 M ⊙ and 20 M ⊙ with a neutron star (NS) companion of 1.4 M ⊙ and 2.0 M ⊙ at two metallicities, using varying common envelope efficiencies and two different prescriptions to determine if the donor undergoes core collapse or electron capture, given their helium and carbon–oxygen cores. In contrast to the case of binary black hole mergers, for an NS companion of 1.4 M ⊙, all BNS mergers are formed following a common envelope phase. For an NS mass of 2.0 M ⊙, we identify a small subset of mergers following only stable mass transfer if the NS receives a natal kick sampled from a Maxwellian distribution with velocity dispersion σ = 265 km s−1. Regardless of the supernova prescription, we find more BNS mergers at subsolar metallicity compared to solar.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".