Signatures of sub-GeV dark matter beams at neutrino experiments
Bibliographic record
Abstract
We study the high-luminosity fixed-target neutrino experiments at MiniBooNE, MINOS and T2K and analyze their sensitivity to light stable states, focusing on MeV--GeV scale dark matter. Thermal relic dark matter scenarios in the sub-GeV mass range require the presence of light mediators, whose coupling to the Standard Model facilitates annihilation in the early universe and allows for the correct thermal relic abundance. The mediators in turn provide a production channel for dark matter at colliders or fixed targets, and as a consequence the neutrino beams generated at fixed targets may contain an additional beam of light dark matter. The signatures of this beam include elastic scattering off electrons or nucleons in the (near-)detector, which closely mimics the neutral current scattering of neutrinos. We determine the event rate at modern fixed target facilities and the ensuing sensitivity to sub-GeV dark matter.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".