Collisional flavor instability in dense neutrino gases
Bibliographic record
Abstract
Charged-current neutrino processes such as ${\ensuremath{\nu}}_{e}+n\ensuremath{\rightleftharpoons}p+{e}^{\ensuremath{-}}$ and ${\overline{\ensuremath{\nu}}}_{e}+p\ensuremath{\rightleftharpoons}n+{e}^{+}$ destroy the flavor coherence among the weak-interaction states of a single neutrino and thus damp its flavor oscillation. In a dense neutrino gas such as that inside a core-collapse supernova or the black hole accretion disk formed in a compact binary merger, however, these ``collision'' processes can trigger large flavor conversion in cooperation with the strong neutrino-neutrino refraction. We show that there exist two types of collisional flavor instability in a homogeneous and isotropic neutrino gas which are identified by the dependence of their real frequencies on the neutrino density ${n}_{\ensuremath{\nu}}$. The instability transitions from one type to the other and exhibits a resonancelike behavior in the region where the net electron lepton number of the neutrino gas is negligible. In the transition region, the flavor instability grows exponentially at a rate $\ensuremath{\propto}{n}_{\ensuremath{\nu}}^{1/2}$. We find that the neutrino gas in the black hole accretion disk is susceptible to the collision-induced flavor conversion where the neutrino densities are the highest. Further investigations are needed to confirm if the collisional flavor instability will indeed result in the production of large amounts of heavy-lepton flavor neutrinos in this environment which would have important ramifications in its subsequent evolution.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".