Detailed Spectroscopic and Photometric Analysis of DQ White Dwarfs
Bibliographic record
Abstract
We present an analysis of spectroscopic and photometric observations of cool DQ white dwarfs based on improved model atmosphere calculations. In particular, we revise the atmospheric parameters of the trigonometric parallax sample of Bergeron, Leggett, & Ruiz and discuss the astrophysical implications on the temperature scale and mean mass, as well as the chemical evolution of these stars. We also analyze 40 new DQ stars discovered in the First Data Release of the Sloan Digital Sky Survey (SDSS). Our analysis confirms that effective temperatures ( T eff ) derived from model atmospheres including carbon are significantly lower than the temperatures obtained from pure helium models. Similarly, the mean mass of the trigonometric parallax sample, ⟨ M ⟩ = 0.62 M ☉ , is significantly lower than that obtained from pure helium models, ⟨ M ⟩ = 0.73 M ☉ , and more consistent with the spectroscopic mean mass of DB stars, ⟨ M ⟩ = 0.59 M ☉ , the most likely progenitors of DQ white dwarfs. We find that DQ stars form a remarkably well-defined sequence in a carbon abundance versus effective temperature diagram; below T eff ~ 10,000 K, carbon pollution decreases monotonically with decreasing effective temperature. Improved evolutionary models including diffusion and connecting to the PG 1159 phase are used to infer a typical value for the thickness of the helium layer M He / M ⋆ between 10 -3 and 10 -2 , compatible with the predictions of post-AGB models. Several DQ stars in our sample, however, show larger than average carbon abundances. We argue that these DQ stars are all massive white dwarfs and could represent the high-mass tail of the white dwarf mass distribution, with their hotter counterparts corresponding to the hot DQ stars reported recently by Liebert et al. The number distribution of DQ white dwarfs as a function of effective temperature clearly shows a sudden drop at about T eff ~ 7000 K and an abrupt cutoff at T eff ~ 6000 K. The existence of this cutoff is now statistically more significant with the addition of the SDSS stars. The physical mechanism responsible for this cutoff is still unknown, even though it is believed to be somehow related to the existence of the so-called C 2 H stars at lower temperatures.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".