Shedding light on neutrino masses with dark forces
Bibliographic record
Abstract
Heavy right-handed neutrinos, N , provide the simplest explanation for the origin of light neutrino masses and mixings. If M N is at or below the weak scale, direct experimental discovery of these states is possible at accelerator experiments such as the LHC or new dedicated beam dump experiments; in these experiments, N decays after traversing a macroscopic distance from the collision point. The experimental sensitivity to right-handed neutrinos is significantly enhanced if there is a new “dark” gauge force connecting them to the Standard Model (SM), and detection of N can be the primary discovery mode for the new dark force itself. We take the well-motivated example of a B − L gauge symmetry and analyze the sensitivity to displaced decays of N produced via the new gauge interaction in two experiments: the LHC and the proposed SHiP beam dump experiment. In the most favorable case in which the mediator can be produced on-shell and decays to right handed neutrinos (pp → X + V B−L → X + N N ), the sensitivity reach is controlled by the square of the B − L gauge coupling. We demonstrate that these experiments could access neutrino parameters responsible for the observed SM neutrino masses and mixings in the most straightforward implementation of the see-saw mechanism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".