Exploring Layered Structure Inside Earth Using Atmospheric Neutrino Oscillation at IceCube DeepCore

The IceCube detector, using its densely instrumented center, called DeepCore, can detect multi-GeV atmospheric neutrinos. The oscillation pattern of neutrinos is altered due to interactions with ambient electrons as they pass through Earth. The changes in these patterns are influenced by the amount of matter and its specific arrangement. As neutrinos propagate, they retain information about the densities they encounter. Our study demonstrates that IceCube DeepCore can utilize the Earth’s matter effects to distinguish between a homogeneous matter density profile and a layered structure density profile of Earth. In this contribution, we present that IceCube DeepCore data equivalent to 9.3 years of observation can reject the homogeneous matter density profile with a confidence level of 1.4$σ$.

💡 Research Summary

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The paper investigates the feasibility of using atmospheric neutrino oscillations measured by the IceCube DeepCore sub‑array to probe the Earth’s internal density structure. Traditional knowledge of Earth’s interior comes from gravimetric and seismic studies, which are indirect and limited by the extreme conditions deep within the planet. Neutrinos, however, traverse the Earth with minimal attenuation and experience coherent forward scattering on electrons (the Mikheyev–Smirnov–Wolfenstein, or MSW, effect). This matter‑induced potential modifies the oscillation probabilities in a way that depends on the integrated electron density along the neutrino path, thereby encoding information about the Earth’s density profile.

The authors focus on multi‑GeV atmospheric neutrinos (3–100 GeV) detected by DeepCore, which provides a dense instrumentation region optimized for low‑energy events. Using convolutional neural networks, the raw photomultiplier data are filtered, and the neutrino energy, zenith angle (cos θₙₑₙ), and particle‑identification (PID) are reconstructed. Events are binned in a three‑dimensional space (energy, cos θₙₑₙ, PID) and classified into cascade‑like, mixed, and track‑like categories.

Two Earth density hypotheses are tested: (1) a uniform density model, and (2) a 12‑layer version of the Preliminary Reference Earth Model (PREM). Monte‑Carlo simulations equivalent to 9.3 years of data are re‑weighted with oscillation probabilities computed for each density model. The fit allows the atmospheric mixing angle θ₂₃ and the atmospheric mass‑splitting Δm²₃₁ to vary freely, while fixing θ₁₂, θ₁₃, Δm²₂₁, and the CP‑violating phase δₙₚ (set to zero). Systematic uncertainties—including flux normalization, cross‑section modeling, detector response, and atmospheric muon background—are incorporated as nuisance parameters.

Sensitivity is evaluated using both the Asimov dataset (expected median outcome) and frequentist pseudo‑experiments. The analysis shows a strong dependence on the assumed true value of sin²θ₂₃, because the ν_μ survival probability and the appearance probability ν_μ→ν_e scale with this factor. For sin²θ₂₃ around 0.5, the ability to discriminate between the two Earth models is maximal, and the trend is similar for both normal and inverted neutrino mass orderings.

The key result is the observed log‑likelihood difference ΔLLH = LLH_PREM – LLH_Uniform. The data yield a p‑value of 0.924 for the uniform hypothesis, corresponding to a confidence level of 92.4 % and a statistical significance of 1.4 σ in favor of the layered PREM model. Although this does not reach the conventional 3 σ discovery threshold, it constitutes the first experimental demonstration that atmospheric neutrino oscillations can be used to distinguish between realistic Earth density profiles.

The authors conclude that the upcoming IceCube Upgrade, with its lower energy threshold and improved calibration, will substantially increase the sensitivity of this technique. Future work could aim at probing finer features of the Earth’s interior, such as variations in the core‑mantle boundary or localized density anomalies, using the same neutrino‑oscillation tomography approach. This study opens a new avenue for geophysical investigations that complements traditional seismic and gravimetric methods.