All-flavor constraints on nonstandard neutrino interactions and generalized matter potential with three years of IceCube DeepCore data
Bibliographic record
Abstract
We report constraints on nonstandard neutrino interactions (NSI) from the observation of atmospheric neutrinos with IceCube, limiting all individual coupling strengths from a single dataset. Furthermore, IceCube is the first experiment to constrain flavor-violating and nonuniversal couplings simultaneously. Hypothetical NSI are generically expected to arise due to the exchange of a new heavy mediator particle. Neutrinos propagating in matter scatter off fermions in the forward direction with negligible momentum transfer. Hence the study of the matter effect on neutrinos propagating in the Earth is sensitive to NSI independently of the energy scale of new physics. We present constraints on NSI obtained with an all-flavor event sample of atmospheric neutrinos based on three years of IceCube DeepCore data. The analysis uses neutrinos arriving from all directions, with reconstructed energies between 5.6 GeV and 100 GeV. We report constraints on the individual NSI coupling strengths considered singly, allowing for complex phases in the case of flavor-violating couplings. This demonstrates that IceCube is sensitive to the full NSI flavor structure at a level competitive with limits from the global analysis of all other experiments. In addition, we investigate a generalized matter potential, whose overall scale and flavor structure are also constrained.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.003 |
| 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".