Search for Astrophysical Sources of Neutrinos Using Cascade Events in IceCube
Bibliographic record
Abstract
Abstract The IceCube neutrino observatory has established the existence of a flux of high-energy astrophysical neutrinos, which is inconsistent with the expectation from atmospheric backgrounds at a significance greater than 5σ. This flux has been observed in analyses of both track events from muon neutrino interactions and cascade events from interactions of all neutrino flavors. Searches for astrophysical neutrino sources have focused on track events due to the significantly better angular resolution of track reconstructions. To date, no such sources have been confirmed. Here we present the first search for astrophysical neutrino sources using cascades interacting in IceCube with deposited energies as small as 1 TeV. No significant clustering was observed in a selection of 263 cascades collected from 2010 May to 2012 May. We show that compared to the classic approach using tracks, this statistically independent search offers improved sensitivity to sources in the southern sky, especially if the emission is spatially extended or follows a soft energy spectrum. This enhancement is due to the low background from atmospheric neutrinos forming cascade events and the additional veto of atmospheric neutrinos at declinations ≲−30°.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".