Search for a light sterile neutrino with 7.5 years of IceCube DeepCore data
Bibliographic record
Abstract
We present a search for an eV-scale sterile neutrino using 7.5 years of data from the IceCube DeepCore detector. The analysis uses a sample of 21,914 events with energies between 5 and 150 GeV to search for sterile neutrinos through atmospheric muon neutrino disappearance. Improvements in event selection and treatment of systematic uncertainties provide greater statistical power compared to previous DeepCore sterile neutrino searches. Our results are compatible with the absence of mixing between active and sterile neutrino states, and we place constraints on the mixing matrix elements <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"><a:mo stretchy="false">|</a:mo><a:msub><a:mi>U</a:mi><a:mrow><a:mi>μ</a:mi><a:mn>4</a:mn></a:mrow></a:msub><a:msup><a:mo stretchy="false">|</a:mo><a:mn>2</a:mn></a:msup><a:mo><</a:mo><a:mn>0.0534</a:mn></a:math> and <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" display="inline"><e:mo stretchy="false">|</e:mo><e:msub><e:mi>U</e:mi><e:mrow><e:mi>τ</e:mi><e:mn>4</e:mn></e:mrow></e:msub><e:msup><e:mo stretchy="false">|</e:mo><e:mn>2</e:mn></e:msup><e:mo><</e:mo><e:mn>0.0574</e:mn></e:math> at 90% CL under the assumption that <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" display="inline"><i:mrow><i:mi mathvariant="normal">Δ</i:mi><i:msubsup><i:mrow><i:mi>m</i:mi></i:mrow><i:mrow><i:mn>41</i:mn></i:mrow><i:mrow><i:mn>2</i:mn></i:mrow></i:msubsup><i:mo>≥</i:mo><i:mn>1</i:mn><i:mtext> </i:mtext><i:mtext> </i:mtext><i:mrow><i:msup><i:mrow><i:mi>eV</i:mi></i:mrow><i:mrow><i:mn>2</i:mn></i:mrow></i:msup></i:mrow></i:mrow></i:math>. These null results add to the growing tension between anomalous appearance results and constraints from disappearance searches in the <l:math xmlns:l="http://www.w3.org/1998/Math/MathML" display="inline"><l:mrow><l:mn>3</l:mn><l:mo>+</l:mo><l:mn>1</l:mn></l:mrow></l:math> sterile neutrino landscape. Published by the American Physical Society 2024
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".