Re-evaluating Lyman α wing opacities and the low mass-problem in cool white dwarfs
Bibliographic record
Abstract
ABSTRACT Gaia observations have reignited interest in the optical and ultraviolet (UV) opacity problems of cool white dwarfs ($\rm{T_{\mathrm{eff}}}\le 6000$ K), which were thought to be resolved nearly two decades ago through the inclusion of Lyman $\alpha$ red wing opacity arising from H–H$_2$ collisions in atmospheric models. Recent studies have revealed that their masses derived from Gaia optical photometry are 0.1–0.2 $\mathrm{M_\odot }$ lower than expected from single-star evolution. Since the Ly $\alpha$ H–H$_2$ wing opacity significantly affects the blue end of their optical spectra, it may contribute to the mass discrepancy. To investigate this hypothesis, we revisited the Ly $\alpha$ opacity calculations in the quasi-static single and multiperturber approximations by explicitly using the ab initio potential energy data of H$_3$ while fully accounting for the H–H$_2$ collision angle. We find that the opacity is slightly smaller than the standard models at the shortest wavelengths ($\le$5000 Å), but larger at longer wavelengths. Comparing synthetic magnitudes (GALEX, Gaia, WISE) to the observations of the 40 pc white dwarf sample, we note that the revised models tentatively reproduce the observed $NUV-G$ colours for stars cooler than 6000 K, but still fail to match $G_{\rm BP} - G_{\rm RP}$ colours, resulting in similarly low inferred masses ($\le $0.5 $\mathrm{M_\odot }$) as obtained with the standard Ly $\alpha$ opacity. Exploring other dominant opacity sources, we discover that decreasing the strength of the bound–free H$^-$ opacity in existing models better reproduces the optical and infrared colours, while collision-induced absorption opacity is ineffective in resolving the low-mass problem. We highlight the need for improved opacities and multiwavelength observations in future studies.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".