On the Properties of Galactic Novae and Their Orbital Period Distribution
Bibliographic record
Abstract
Using population synthesis techniques, we analyze the orbital period distribution and other ensemble properties of Galactic novae. We find that the frequency of nova outbursts in the Galactic disk should be about 30 events yr -1 (to within a factor of ~5). This frequency is in agreement with previous theoretical estimates and the observationally inferred rates (but we caution that there are many uncertainties inherent in the calculations). We also find that the frequency-averaged mass of degenerate dwarfs in nova systems is in the range of 0.95 ± 0.15 M ☉ , which is in good agreement with the observational estimate of 0.90 M ☉ . If period-dependent observational selection effects are not substantial, we show that any theoretical model (and/or region of parameter space) pertaining to the formation and evolution of Galactic novae can be constrained by comparing the predicted ratio of novae above the period gap to those below the gap (i.e., ν above /ν below ) with the observed one. Using the observationally inferred lower limit and given that the temperature of the accreting degenerate dwarfs has a significant effect on the estimated nova frequencies for cataclysmic variables in the orbital period range of 1-2 hr (i.e., below the period gap), we conclude that (on average) the degenerate dwarfs in systems below the gap are relatively cold (<3 × 10 7 K), and that they may be significantly cooler than the dwarfs found in the high-period systems. We note that this result is in accord with recent observations and underscores the need for theoretical calculations of the thermal evolution of degenerate dwarfs in nova systems.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".