Diffuse supernova neutrino background search at Super-Kamiokande
Why this work is in the frame
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Bibliographic record
Abstract
We have conducted a new search for the diffuse supernova neutrino background (DSNB) flux at Super-Kamiokande (SK), with a $22.5\ifmmode\times\else\texttimes\fi{}2970\text{\ensuremath{-}}\mathrm{kton}\ifmmode\cdot\else\textperiodcentered\fi{}\mathrm{day}$ exposure from its fourth operational phase IV. With the new analysis we improve on the existing background reduction techniques and systematic uncertainties and take advantage of an improved neutron tagging algorithm to lower the energy threshold compared to the previous phases of SK. This allows for setting the world's most stringent upper limit on the extraterrestrial ${\overline{\ensuremath{\nu}}}_{e}$ flux, for neutrino energies below 31.3 MeV. The SK-IV results are combined with the ones from the first three phases of SK to perform a joint analysis using $22.5\ifmmode\times\else\texttimes\fi{}5823\text{ }\text{ }\mathrm{kton}\ifmmode\cdot\else\textperiodcentered\fi{}\mathrm{days}$ of data. This analysis has the world's best sensitivity to the DSNB ${\overline{\ensuremath{\nu}}}_{e}$ flux, comparable to the predictions from various models. For neutrino energies larger than 17.3 MeV, the new combined 90% CL upper limits on the DSNB ${\overline{\ensuremath{\nu}}}_{e}$ flux lie around $2.7\text{ }\text{ }{\mathrm{cm}}^{\ensuremath{-}2}\ifmmode\cdot\else\textperiodcentered\fi{}{\mathrm{sec}}^{\ensuremath{-}1}$, strongly disfavoring the most optimistic predictions. Finally, potentialities of the gadolinium phase of SK and the future Hyper-Kamiokande experiment are discussed.
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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) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.008 |
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 it