Concurrence minima in neutrino oscillations identify low-entanglement energy regions that, when aligned with NOνA and T2K data, yield tighter joint constraints on sin²θ₂₃, δ_CP, and Δm²₃₁.
Quantifying the sensitivity of oscillation experiments to the neutrino mass ordering
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abstract
Determining the type of the neutrino mass ordering (normal versus inverted) is one of the most important open questions in neutrino physics. In this paper we clarify the statistical interpretation of sensitivity calculations for this measurement. We employ standard frequentist methods of hypothesis testing in order to precisely define terms like the median sensitivity of an experiment. We consider a test statistic $T$ which in a certain limit will be normal distributed. We show that the median sensitivity in this limit is very close to standard sensitivities based on $\Delta\chi^2$ values from a data set without statistical fluctuations, such as widely used in the literature. Furthermore, we perform an explicit Monte Carlo simulation of the INO, JUNO, LBNE, NOvA, and PINGU experiments in order to verify the validity of the Gaussian limit, and provide a comparison of the expected sensitivities for those experiments.
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JUNO's initial results combined with global data give a 2.2-2.3 sigma preference for normal neutrino mass ordering.
Develops a likelihood ratio framework for assessing highly motivated subdominant new physics signals against experimental residuals that appear consistent with background predictions.
Updated global analysis finds well-determined neutrino mixing parameters with nearly equal preference for normal and inverted mass orderings in the full dataset.
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Lessons from the first JUNO results
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