LMXB AND IMXB EVOLUTION: I. THE BINARY RADIO PULSAR PSR J1614–2230
Bibliographic record
Abstract
We have computed an extensive grid of binary evolution tracks to represent low- and intermediate-mass X-ray binaries (LMXBs and IMXBs). The grid includes 42,000 models which cover 60 initial donor masses over the range of 1–4 M ☉ and, for each of these, 700 initial orbital periods over the range of 10–250 hr. These results can be applied to understanding LMXBs and IMXBs: those that evolve analogously to cataclysmic variables, that form ultracompact binaries with P orb in the range of 6–50 minutes, and that lead to wide orbits with giant donors. We also investigate the relic binary recycled radio pulsars into which these systems evolve. To evolve the donor stars in this study, we utilized a newly developed stellar evolution code called " MESA " that was designed, among other things, to be able to handle very low mass and degenerate donors. This first application of the results is aimed at an understanding of the newly discovered pulsar PSR J1614−2230 which has a 1.97 M ☉ neutron star, P orb = 8.7 days, and a companion star of 0.5 M ☉ . We show that (1) this system is a cousin to the LMXB Cyg X-2; (2) for neutron stars of canonical birth mass 1.4 M ☉ , the initial donor stars which produce the closest relatives to PSR J1614−2230 have a mass between 3.4 and 3.8 M ☉ ; (3) neutron stars as massive as 1.97 M ☉ are not easy to produce in spite of the initially high mass of the donor star, unless they were already born as relatively massive neutron stars; (4) to successfully produce a system like PSR J1614−2230 requires a minimum initial neutron-star mass of at least 1.6 ± 0.1 M ☉ , as well as initial donor masses and P orb of ∼4.25 ± 0.10 M ☉ and ∼49 ± 2 hr, respectively; and (5) the current companion star is largely composed of CO, but should have a surface H abundance of ∼10%–15%.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".