Cataclysmic Variables: An Empirical Angular Momentum Loss Prescription from Open Cluster Data
Bibliographic record
Abstract
We apply the angular momentum loss rates inferred from open cluster stars to the evolution of cataclysmic variables (CVs). We show that the angular momentum prescriptions used in earlier CV studies are inconsistent with the measured rotation data in open clusters. The timescale for angular momentum loss ( ) above the fully convective boundary is ~2 orders of magnitude longer than inferred from the older model, and the observed angular momentum loss properties show no evidence for a change in behavior at the fully convective boundary. This provides evidence against the hypothesis that the period gap is caused by an abrupt change in the angular momentum loss law when the secondary becomes fully convective. Furthermore, the empirical angular momentum loss law implies a timescale for CV evolution that is comparable to a Hubble time; for the same reason, it will be more difficult to produce CVs from the products of common envelope evolution, and it implies a lower space density of CVs. The predicted loss rate for short-period CVs is consistent with the observed period minimum (1.3 hr). We infer the time-averaged mass accretion rate and derive the mass-period relation for different evolutionary states of the secondary. The steady-state accretion rates are significantly lower than the claimed observational rates; we discuss some possible explanations. The mass-period relationship is more consistent with evolved secondaries than with unevolved secondaries above the period gap. Implications for the CV period gap are discussed, including the possibility that two populations of secondaries could produce the gap.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".