论文标题
在$ \ mathbf {r} $ - 平等竞选MSSM中分析中微子数据的$ν$方法
A $ν$ Approach to Analyzing Neutrino Data in the $\mathbf{R}$-Parity-Violating MSSM
论文作者
论文摘要
$ r $ - - 竞选最小的超对称标准模型（RPV-MSSM）自然可以根据振荡数据要求容纳大规模的中微子。然而，由于涉及大量未确定参数，研究现象学是复杂的。因此，研究通常仅限于特定的子模型。在这项工作中，我们开发了一种方法，使我们的限制性降低。我们在（几乎）完全一般的RPV-MSSM设置中工作，我们分析了中微子质量基质的结构，并在两个大规模的中微子的情况下（只有四个最小的结构类别可以解决中微子数据；我们称这些最小振荡模型（MOMS）。我们研究每个妈妈类的一般特征，并将数值拟合到振荡数据中。我们的方法使我们能够以统一的方式研究满足中微子数据的所有RPV模型，只要它们满足MOM标准即可。通过几个示例，我们表明这确实适用于许多有趣的场景。
The $R$-parity-violating Minimal Supersymmetric Standard Model (RPV-MSSM) can naturally accommodate massive neutrinos as required by the oscillation data. However, studying the phenomenology is complicated due to the large number of undetermined parameters involved. Thus, studies are usually restricted to specific submodels. In this work, we develop an approach that allows us to be less restrictive. Working in (almost) the completely general RPV-MSSM setting, we analyze the structure of the neutrino mass matrix, and identify -- for the case of two massive neutrinos -- only four minimal classes of structures that can solve the neutrino data; we call these Minimal Oscillation Models (MOMs). We study the general features of each MOM class, and present numerical fits to the oscillation data. Our approach allows us to study all RPV models satisfying the neutrino data in a unified manner, as long as they satisfy the MOM criteria. Through several examples, we show that this indeed holds for many interesting scenarios.
