论文标题

fermion块和$ a_5 $模块化组的双盖和跨度封面混合

Fermion Masses and Mixing from Double Cover and Metaplectic Cover of $A_5$ Modular Group

论文作者

Yao, Chang-Yuan, Liu, Xiang-Gan, Ding, Gui-Jun

论文摘要

我们对同质有限模块化组$ A'_5 $进行全面研究,这是$ a_5 $的双重覆盖。整体重量和5级模块化表格已被构造为重量6,并将其分解为$ a'_5 $的不可还原表示。然后,我们对Lepton Masses和Comping的$ A'_5 $模块模型进行系统分析。出现了具有最小数量的自由参数和拟合结果的现象学上可行的模型。我们发现15个具有9个实际自由参数的模型,可以容纳Lepton部门的实验数据。在包括广义的CP对称性之后,发现9个具有7个自由参数的可行模型。我们将$ A'_5 $模块化对称性应用于夸克部门,并给出了夸克 - 莱普顿统一模型。模块化不变性的框架扩展到包括5级的理性权重模块化形式。级别5的模块化表格可以由两个代数独立的重量$ 1/5 $模块化形式生成,由$ f_1(τ)$和$ f_2(τ)$表示。我们给出5级5级的理性权重模块化形式的表达式$ 3 $,然后将其安排到有限的Metapclect组$ \ wideTildec__5 \ cong a'__5 \ times z_5 $的不可还原多重上。提出了具有$ \widetildeγ_5$模块化对称性的中微子质量模型,并通过数值分析模型的现象学预测。

We perform a comprehensive study of the homogeneous finite modular group $A'_5$ which is the double covering of $A_5$. The integral weight and level 5 modular forms have been constructed up to weight 6 and they are decomposed into the irreducible representations of $A'_5$. Then we perform a systematical analysis of the $A'_5$ modular models for lepton masses and mixing. The phenomenologically viable models with minimal number of free parameters and the results of fit are presented. We find out 15 models with 9 real free parameters which can accommodate the experimental data of lepton sector. After including generalized CP symmetry, 9 viable models with 7 free parameters are found out. We apply $A'_5$ modular symmetry to the quark sector, and a quark-lepton unification model is given. The framework of modular invariance is extended to include the rational weight modular forms of level 5. The ring of modular forms at level 5 can be generated by two algebraically independent weight $1/5$ modular forms denoted by $F_1(τ)$ and $F_2(τ)$. We give the expressions of the rational weight modular forms of level 5 up to weight $3$ and arrange them into the irreducible multiplets of finite metaplectic group $\widetildeΓ_5\cong A'_5\times Z_5$. A neutrino mass model with $\widetildeΓ_5$ modular symmetry is presented, and the phenomenological predictions of the model are analyzed numerically.

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