Solar neutrino event spectra: Tuning SNO to equalize Super-Kamiokande
Bibliographic record
Abstract
The Super-Kamiokande (SK) and the Sudbury Neutrino Observatory (SNO) experiments are monitoring the flux of ${}^{8}\mathrm{B}$ solar neutrinos through the electron energy spectrum from the reactions ${\ensuremath{\nu}}_{e,\ensuremath{\mu},\ensuremath{\tau}}{+e}^{\ensuremath{-}}\ensuremath{\rightarrow}{\ensuremath{\nu}}_{e,\ensuremath{\mu},\ensuremath{\tau}}{+e}^{\ensuremath{-}}$ and ${\ensuremath{\nu}}_{e}+\stackrel{\ensuremath{\rightarrow}}{d}{p+p+e}^{\ensuremath{-}},$ respectively. We show that the SK detector response to ${}^{8}\mathrm{B}$ neutrinos in each bin of the electron energy spectrum (above 8 MeV) can be approximated, with good accuracy, by the SNO detector response in an appropriate electron energy range (above 5.1 MeV). For instance, the SK response in the bin $[10,10.5]$ MeV is reproduced (``equalized'') within $\ensuremath{\sim}2%$ by the SNO response in the range $[7.1,11.75]$ MeV. As a consequence, in the presence of active neutrino oscillations, the SK and SNO event rates in the corresponding energy ranges turn out to be linearly related, for any functional form of the oscillation probability. Such equalization is not spoiled by the possible contribution of hep neutrinos (within current phenomenological limits). In perspective, when the SK and the SNO spectra will both be measured with high accuracy, the SK-SNO equalization can be used to determine the absolute ${}^{8}\mathrm{B}$ neutrino flux, and to cross-check the (non)observation of spectral deviations in SK and SNO. At present, as an exercise, we use the equalization to ``predict'' the SNO energy spectrum, on the basis of the current SK data. Finally, we briefly discuss some modifications or limitations of our results in the case of sterile $\ensuremath{\nu}$ oscillations and of relatively large Earth matter effects.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".