What question did this study set out to answer?

This research aims to explore how dynamical phase correlations affect the predictivity of the CP-violating phase δCP in the PMNS matrix.

May 3, 2026Open Access

ICC XVIII: Dynamical Phase Correlations and Structural Constraints on Quantitative CP Prediction

Key Points

This research aims to explore how dynamical phase correlations affect the predictivity of the CP-violating phase δCP in the PMNS matrix.
Introduced a targeted effective potential to improve predictivity for δCP.
Analyzed the connections between phase correlations and the eigenvectors of the unitarization map’s Hessian.
Outlined a schematic expression for the targeted potential to suppress specific modes.
Predicted broad distributions for δCP are testable with upcoming experiments like DUNE and Hyper-Kamiokande.
The framework identifies minimal conditions necessary for achieving quantitative precision in predictions.
Achieved > 3σ significance for testing the hypothesis on the uncertainty of δCP.

Abstract

Building on the refined structural constraint identified in ICC XVII, we investigate whether dynamical phase correlations can suppress unitarization-induced scrambling and restore quantitative predictivity for the CP-violating phase δCP in the PMNS matrix. We in troduce a simple effective potential V (θi) ∝ i 3σ significance. This work identifies the minimal conditions for quantitative precision and establishes targeted dynamical correlations as the next necessary ingredient.

ICC XVIII: Dynamical Phase Correlations and Structural Constraints on Quantitative CP Prediction

Key Points

Abstract

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