The future of high-energy astrophysical neutrino flavor measurements
Bibliographic record
Abstract
Abstract We critically examine the ability of future neutrino telescopes, including Baikal-GVD, KM3NeT, P-ONE, TAMBO, and IceCube-Gen2, to determine the flavor composition of high-energy astrophysical neutrinos in light of data from next-generation of neutrino oscillation experiments including JUNO, DUNE, and Hyper-Kamiokande. By 2040, the region of allowed flavor composition at Earth will shrink ten-fold, and the flavor composition at the astrophysical sources of the neutrinos will be inferred to within 6%, enough to pinpoint the dominant neutrino production mechanism and to identify possible sub-dominant mechanisms. These conclusions hold even in the nonstandard scenario where neutrino mixing is non-unitary, a scenario that will be probed in next-generation experiments such as the IceCube-Upgrade. As an illustration, we show that future experiments are sensitive to decay rates of the heavier neutrinos to below 1.8 × 10 -5 (m/eV) s -1 at 95% credibility by 2040.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".