Neutrino oscillation physics potential of the T2K experiment
Bibliographic record
Abstract
The observation of the recent electron neutrino appearance in a muon neutrino beam and the high-precision measurement of the mixing angle θ13 have led to a re-evaluation of the physics potential of the T2K long-baseline neutrino oscillation experiment. Sensitivities are explored for CP violation in neutrinos, non-maximal sin22θ23, the octant of θ23, and the mass hierarchy, in addition to the measurements of δCP, sin2θ23, and Δm232, for various combinations of ν-mode and ν¯-mode data-taking. With an exposure of 7.8×1021 protons-on-target, T2K can achieve 1σ resolution of 0.050 (0.054) on sin2θ23 and 0.040 (0.045)×10−3eV2 on Δm232 for 100% (50%) neutrino beam mode running assuming sin2θ23=0.5 and Δm232=2.4×10−3eV2. T2K will have sensitivity to the CP violating phase δCP at 90% C.L. or better over a significant range. For example, if sin22θ23 is maximal (i.e.θ23=45∘) the range is−115∘<δCP<−60∘ for normal hierarchy and +50∘<δCP<+130∘ for inverted hierarchy. When T2K data is combined with data from the NO ν A experiment, the region of oscillation parameter space where there is sensitivity to observe a non-zero δCP is substantially increased compared to if each experiment is analyzed alone.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".