Bibliographic record
Abstract
Recent studies of low redshift type Ia supernovae (SN Ia) indicate that half explode from less than Chandrasekhar mass white dwarfs, implying ignition must proceed from something besides the canonical criticality of Chandrasekhar mass SN Ia progenitors. We show that 1-100 PeV mass asymmetric dark matter, with imminently detectable nucleon scattering interactions, can accumulate to the point of self-gravitation in a white dwarf and collapse, shedding gravitational potential energy by scattering off nuclei, thereby heating the white dwarf and igniting the flame front that precedes SN Ia. We combine data on SN Ia masses with data on the ages of SN Ia-adjacent stars. This combination reveals a 2.8σ inverse correlation between SN Ia masses and ignition ages, which could result from increased capture of dark matter in 1.4 vs 1.1 solar mass white dwarfs. Future studies of SN Ia in galactic centers will provide additional tests of dark-matter-induced type Ia ignition. Remarkably, both bosonic and fermionic SN Ia-igniting dark matter also resolve the missing pulsar problem by forming black holes in ≳10 Myr old pulsars at the center of the Milky Way.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
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 teacher head, 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".