JWST Resolves Collision-induced Absorption Features in White Dwarfs
Bibliographic record
Abstract
Abstract Infrared-faint white dwarfs are cool white dwarfs exhibiting significant infrared flux deficits, most often attributed to collision-induced absorption (CIA) from H 2 –He in mixed hydrogen–helium atmospheres. We present James Webb Space Telescope (JWST) near- and mid-infrared spectra of three such objects using Near-Infrared Spectrograph (0.6–5.3 μ m) and Mid-Infrared Instrument (5–14 μ m): LHS 3250, WD J1922+0233, and LHS 1126. Surprisingly, for LHS 3250, we detect no H 2 –He CIA absorption at 2.4 μ m, instead observing an unexpected small flux bump at this wavelength. WD J1922+0233 exhibits the anticipated strong absorption feature centered at 2.4 μ m, but with an unexpected narrow emission-like feature inside this absorption band. LHS 1126 shows no CIA features and follows a λ −2 power law in the mid-infrared. LHS 1126's lack of CIA features suggests a very low hydrogen abundance, with its infrared flux depletion likely caused by He–He–He CIA. For LHS 3250 and WD J1922+0233, the absence of a 1.2 μ m CIA feature in both stars argues against ultracool temperatures, supporting recent suggestions that infrared-faint (IR-faint) white dwarfs are warmer and more massive than previously thought. This conclusion is further solidified by Keck near-infrared spectroscopy of seven additional objects. We explore possible explanations for the unexpected emission-like features in both stars, and temperature inversions above the photosphere emerge as a promising hypothesis. Such inversions may be common among the IR-faint population, and since they significantly affect the infrared spectral energy distribution, this would impact their photometric fits. Further JWST observations are needed to confirm the prevalence of this phenomenon and guide the development of improved atmospheric models.
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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 | 0.000 |
| 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 | 0.000 | 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".