Measurement of Atmospheric Neutrino Oscillation Parameters Using Convolutional Neural Networks with 9.3 Years of Data in IceCube DeepCore
(2025) Physical Review Letters — Vol. 134 (2025)
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- Abstract
- The DeepCore subdetector of the IceCube Neutrino Observatory provides access to neutrinos with energies above approximately 5 GeV. Data taken between 2012 and 2021 (3387 days) are utilized for an atmospheric <math display="inline"><msub><mi>ν</mi><mi>μ</mi></msub></math> disappearance analysis that studied 150 257 neutrino-candidate events with reconstructed energies between 5 and 100 GeV. An advanced reconstruction based on a convolutional neural network is applied, providing increased signal efficiency and background suppression, resulting in a measurement with both significantly increased statistics compared to previous DeepCore oscillation results and high neutrino purity. For the normal neutrino mass ordering, the atmospheric neutrino oscillation parameters and their <math display="inline"><mrow><mn>1</mn><mi>σ</mi></mrow></math> errors are measured to be <math display="inline"><mrow><mi mathvariant="normal">Δ</mi><msubsup><mrow><mi mathvariant="normal">m</mi></mrow><mrow><mn>32</mn></mrow><mrow><mn>2</mn></mrow></msubsup><mo>=</mo><msubsup><mrow><mn>2.40</mn></mrow><mrow><mo>-</mo><mn>0.04</mn></mrow><mrow><mo>+</mo><mn>0.05</mn></mrow></msubsup><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mo>-</mo><mn>3</mn></mrow></msup><mtext> </mtext><mtext> </mtext><msup><mrow><mi>eV</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></math> and <math display="inline"><mrow><msup><mrow><mi>sin</mi></mrow><mrow><mn>2</mn></mrow></msup><msub><mrow><mi>θ</mi></mrow><mrow><mn>23</mn></mrow></msub><mo>=</mo><msubsup><mrow><mn>0.54</mn></mrow><mrow><mo>-</mo><mn>0.03</mn></mrow><mrow><mo>+</mo><mn>0.04</mn></mrow></msubsup></mrow></math>. The results are the most precise to date using atmospheric neutrinos, and are compatible with measurements from other neutrino detectors including long-baseline accelerator experiments.
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Citations
de Wasseige, G., Genton, E., Kruiswijk, K., Lamoureux, M., Lazar, J., Raab, C., Myhr, P., Vereecken, M., IceCube, & et al. (2025). Measurement of Atmospheric Neutrino Oscillation Parameters Using Convolutional Neural Networks with 9.3 Years of Data in IceCube DeepCore. Physical Review Letters, 134. https://doi.org/10.1103/PhysRevLett.134.091801 (Original work published 2025)