Feasibility of heavy neutrino mass searches in the EC decay of ⁷Be using superconducting tunnel junctions
Bibliographic record
Abstract
The Standard Model (SM) of particle physics has been the benchmark for subatomic studies for more than 50 years.Despite its success in describing nearly all matter, the SM cannot predict some of the fundamental observables in nature, including the masses of the neutrinos.In the SM weak interaction, only "left-handed" neutrinos exist.However, "right-handed" neutrinos which do not take part in the weak interaction -so-called "sterile neutrinos" -may yet exist as extensions to the Standard Model, and have proposed masses significantly heavier than those estimated for the SM neutrinos.Since these sterile neutrinos do not interact with normal matter as they pass through, there is a strong need for new experimental methods and detection paradigms to search for these proposed particles.This Thesis presents a proof-of-concept for a sensitive sterile neutrino search using superconducting tunnel junction (STJ) radiation detectors to accurately reconstruct the momentum profile of the nuclear electron capture (EC) decay of beryllium-7 (7Be).Since EC decay results in a pure two-body final-state, all information on the mass eigenstate of the neutrino is contained in the recoil nucleus kinetic energy, which in this case is on the order of 50 eV.These measurements were performed using harvested 7Be from the TRIUMF-ISAC rare-isotope beam facility in Vancouver, Canada, and the experimental measurements were subsequently performed at Lawrence Livermore National Laboratory in California.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".