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arXiv 1609.09402hep-ph
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对最小跷跷板模式和最大大气混合的重整化群修正

Renormalisation Group Corrections to the Littlest Seesaw Model and Maximal Atmospheric Mixing

Stephen F. King, Jue Zhang, Shun Zhou

摘要:

Littlest Seesaw(LS)模型涉及两个右手中微子和一个非常受约束的狄拉克中微子质量矩阵,涉及一个纹理零和两个独立的狄拉克质量,导致一个高度可预测的方案,其中所有中微子质量和整个PMNS矩阵仅用两个实参数成功预测。我们计算的重整化群(RG)的LS预测的修正,有和没有超对称性,也包括阈值效应引起的重马约拉纳中微子的去耦分析和数值。我们发现,中微子混合角和质量比的预测是相当稳定的RG修正下。例如,我们发现,与RG校正的LS模型预测接近最大的大气混合,$θ_{23}=45^\circ \pm 1^\circ$,在大多数情况下,在紧张的最新NOvA的结果。这里使用的技术适用于其他具有强法线质量层次的跷跷板模型。

英文摘要:

The Littlest Seesaw (LS) model involves two right-handed neutrinos and a very constrained Dirac neutrino mass matrix, involving one texture zero and two independent Dirac masses, leading to a highly predictive scheme in which all neutrino masses and the entire PMNS matrix is successfully predicted in terms of just two real parameters. We calculate the renormalisation group (RG) corrections to the LS predictions, with and without supersymmetry, including also the threshold effects induced by the decoupling of heavy Majorana neutrinos both analytically and numerically. We find that the predictions for neutrino mixing angles and mass ratios are rather stable under RG corrections. For example we find that the LS model with RG corrections predicts close to maximal atmospheric mixing, $θ_{23}=45^\circ \pm 1^\circ$, in most considered cases, in tension with the latest NOvA results. The techniques used here apply to other seesaw models with a strong normal mass hierarchy.

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