The Sun: Light Dark Matter and Sterile Neutrinos
Bibliographic record
Abstract
Next-generation experiments allow for the possibility to testing the neutrino flavor oscillation model to very high levels of accuracy. Here, we explore the possibility that the dark matter in the current universe is made of two particles, a sterile neutrino and a very light dark matter particle. By using a 3+1 neutrino flavor oscillation model, we study how such a type of dark matter imprints the solar neutrino fluxes, spectra, and survival probabilities of electron neutrinos. The current solar neutrino measurements allow us to define an upper limit for the ratio of the mass of a light dark matter particle $m_ϕ$ and the Fermi constant $G_ϕ$, such that $G_ϕ/m_ϕ$ must be smaller than $10^{30}\; G_{\rm F}\; eV^{-1}$ to be in agreement with current solar neutrino data from the Borexino, Sudbury Neutrino Observatory, and Super-Kamiokande detectors. Moreover, for models with a very small Fermi constant, the amplitude of the time variability must be lower than $3\%$ to be consistent with current solar neutrino data. We also found that solar neutrino detectors like Darwin, able to measure neutrino fluxes in the low energy-range with high accuracy, will provide additional constraints to this class of models that complement the ones obtained from the current solar neutrino detectors.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".