A little theory of everything, with heavy neutral leptons
Bibliographic record
Abstract
Abstract Recently a new model of “Affleck-Dine inflation” was presented, that produces the baryon asymmetry from a complex inflaton carrying baryon number, while being consistent with constraints from the cosmic microwave background. We adapt this model such that the inflaton carries lepton number, and communicates the lepton asymmetry to the standard model baryons via quasi-Dirac heavy neutral leptons (HNLs) and sphalerons. One of these HNLs, with mass $$ \underset{\sim }{<} $$ < ~ 4.5 GeV, can be (partially) asymmetric dark matter (DM), whose asymmetry is determined by that of the baryons. Its stability is directly related to the vanishing of the lightest neutrino mass. Neutrino masses are generated by integrating out heavy sterile neutrinos whose mass is above the inflation scale. The model provides an economical origin for all of the major ingredients missing from the standard model: inflation, baryogenesis, neutrino masses, and dark matter. The HNLs can be probed in fixed-target experiments like SHiP, possibly manifesting $$ N-\overline{N} $$ N − N ¯ oscillations. A light singlet scalar, needed for depleting the DM symmetric component, can be discovered in beam dump experiments and searches for rare decays, possibly explaining anomalous events recently observed by the KOTO collaboration. The DM HNL is strongly constrained by direct searches, and could have a cosmologically interesting self-interaction cross section.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".