Magnetic White Dwarfs in the SDSS 100 pc Sample: Further Evidence of Two Formation Channels
Bibliographic record
Abstract
Abstract We conduct a model atmosphere analysis on all magnetic white dwarfs (MWDs) in the Sloan Digital Sky Survey (SDSS) 100 pc sample. We have 163 magnetic targets in this sample, 87 of which are new discoveries, making this the largest volume-limited survey of MWDs to date. We discuss the distribution of multiple parameters, including mass, cooling age, and field strength. We find strong evidence of two populations of MWDs that form through separate mechanisms based on a cluster analysis of these parameters. The young, high-mass objects typically have high field strengths which indicate a merger origin, while old, average-mass objects have weaker fields that likely originated through a crystallization-induced dynamo or previous evolution stages. When comparing young and old objects, two-sample Kolmogorov–Smirnov tests yield statistically significant differences between the field strengths and masses of the magnetic targets. We use a Gaussian mixture model to identify where these populations lie in parameter space, and we find two groups centered at distinct cooling ages, masses, and field strengths of 2.9 Gyr, 0.71 M ⊙ , 3.7 MG and 1.8 Gyr, 0.96 M ⊙ , 84 MG, respectively. Our results further support the dual formation channel previously reported in the literature. The occurrence of magnetism strongly correlates with the onset of crystallization. However, given the breakout times required for a crystallization dynamo, we find that many of our older, average-mass objects can be better explained with a core-convective dynamo that forms on the main sequence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".