Physics potentials with the second Hyper-Kamiokande detector in Korea
Bibliographic record
Abstract
Hyper-Kamiokande consists of two identical water-Cherenkov detectors of total 520~kt with the first one in Japan at 295~km from the J-PARC neutrino beam with 2.5$^{\textrm{o}}$ Off-Axis Angles (OAAs), and the second one possibly in Korea in a later stage. Having the second detector in Korea would benefit almost all areas of neutrino oscillation physics mainly due to longer baselines. There are several candidate sites in Korea with baselines of 1,000$\sim$1,300~km and OAAs of 1$^{\textrm{o}}$$\sim$3$^{\textrm{o}}$. We conducted sensitivity studies on neutrino oscillation physics for a second detector, either in Japan (JD $\times$ 2) or Korea (JD + KD) and compared the results with a single detector in Japan. Leptonic CP violation sensitivity is improved especially when the CP is non-maximally violated. The larger matter effect at Korean candidate sites significantly enhances sensitivities to non-standard interactions of neutrinos and mass ordering determination. Current studies indicate the best sensitivity is obtained at Mt. Bisul (1,088~km baseline, $1.3^\circ$ OAA). Thanks to a larger (1,000~m) overburden than the first detector site, clear improvements to sensitivities for solar and supernova relic neutrino searches are expected.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".