EVOLUTION OF CATACLYSMIC VARIABLES AND RELATED BINARIES CONTAINING A WHITE DWARF
Bibliographic record
Abstract
ABSTRACT We present a binary evolution study of cataclysmic variables (CVs) and related systems with white dwarf (WD) accretors, including for example, AM CVn systems, classical novae, supersoft X-ray sources (SXSs), and systems with giant donor stars. Our approach intentionally avoids the complications associated with population synthesis algorithms, thereby allowing us to present the first truly comprehensive exploration of all of the subsequent binary evolution pathways that zero-age CVs might follow (assuming fully non-conservative, Roche-lobe overflow onto an accreting WD) using the sophisticated binary stellar evolution code MESA. The grid consists of 56,000 initial models, including 14 WD accretor masses, 43 donor-star masses (0.1–4.7 M ⊙ ), and 100 orbital periods. We explore evolution tracks in the orbital period and donor-mass ( P orb – M don ) plane in terms of evolution dwell times, masses of the WD accretor, accretion rate, and chemical composition of the center and surface of the donor star. We report on the differences among the standard CV tracks, those with giant donor stars, and ultrashort period systems. We show where in parameter space one can expect to find SXSs, present a diagnostic to distinguish among different evolutionary paths to forming AM CVn binaries, quantify how the minimum orbital period in CVs depends on the chemical composition of the donor star, and update the P orb ( M wd ) relation for binaries containing WDs whose progenitors lost their envelopes via stable Roche-lobe overflow. Finally, we indicate where in the P orb – M don the accretion disks will tend to be stable against the thermal-viscous instability, and where gravitational radiation signatures may be found with LISA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".