The origin of ultramassive white dwarfs: hints from <i>Gaia</i> EDR3
Bibliographic record
Abstract
ABSTRACT Gaia Data Release 2 revealed a population of ultramassive white dwarfs on the Q branch that are moving anomalously fast for a local disc population with their young photometric ages. As the velocity dispersion of stars in the local disc increases with age, a proposed explanation of these white dwarfs is that they experience a cooling delay that causes current cooling models to infer photometric ages much younger than their true ages. To explore this explanation, we investigate the kinematics of ultramassive white dwarfs within 200 pc of the Sun using the improved Gaia Early Data Release 3 observations. We analyse the transverse motions of 0.95–1.25 M⊙ white dwarfs, subdivided by mass and age, and determine the distributions of the three-dimensional components of the transverse velocities. The results are compared to expectations based on observed kinematics of local main-sequence stars. We find a population of photometrically young (∼0.5–1.5 Gyr) ultramassive (∼1.15–1.25 M⊙) white dwarfs for which the transverse velocity component in the direction of Galactic rotation is more dispersed than for local disc stars of any age; thus, it is too dispersed to be explained by any cooling delay in white dwarfs originating from the local disc. Furthermore, the dispersion ratio of the velocity components in the Galactic plane for this population is also inconsistent with a local disc origin. We discuss some possible explanations of this kinematically anomalous population, such as a halo origin or production through dynamical effects of stellar triple 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".