Disk or Companion: Characterizing Excess Infrared Flux in Seven White Dwarf Systems with Near-infrared Spectroscopy
Bibliographic record
Abstract
Abstract Excess infrared flux from white dwarf stars is likely to arise from a dusty debris disk or a cool companion. In this work, we present near-infrared spectroscopic observations with Keck/MOSFIRE, Gemini/GNIRS, and Gemini/Flamingos-2 of seven white dwarfs with infrared excesses identified in previous studies. We confirmed the presence of dust disks around four white dwarfs (Gaia J0611–6931, Gaia J0006+2858, Gaia J2100+2122, and WD 0145+234) as well as two new white dwarf–brown dwarf pairs (Gaia J0052+4505 and Gaia J0603+4518). In three of the dust disk systems, we detected for the first time near-infrared metal emissions (Mg i, Si I, and possibly Fe I) from a gaseous component of the disk. We developed a new Markov Chain Monte Carlo framework to constrain the geometric properties of each dust disk. In three systems, the dust disk and the gas disk appear to coincide spatially. For the two brown dwarf–white dwarf pairs, we identified broad molecular absorption features typically seen in L dwarfs. The origin of the infrared excess around Gaia J0723+6301 remains a mystery. Our study underlines how near-infrared spectroscopy can be used to determine sources of infrared excess around white dwarfs, which has now been detected photometrically in hundreds of 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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".