论文标题
树级的主要中微子质量来自1 $ \ times $ type-2-2 seesaw机制与暗物质
Tree level Majorana neutrino mass from Type-1 $\times$ Type-2 Seesaw mechanism with Dark Matter
论文作者
论文摘要
我们提出了一种混合SEESAW模型，该模型以乘法方式结合了1型和2型Seesaw机制，以生成树级的主要中微子质量，并提供暗物质候选者。该模型通过额外的量规对称$ u（1）_ {d} $扩展标准模型，而隐藏的扇区由手性费米子和其他标量字段组成。自发对称性破裂后，不仅通过将新的重费用作为1型Seesaw交换而产生的轻中微子肿块，而且还通过将新的重型标量型的自然诱导的真空期望值偶联到2型Seesaw。 $ u（1）_ {d} $的不间断残留物可保护隐藏区域中取消异常所要求的最轻的零食费用，从而使其衰败，从而引起暗物质候选者。由于我们的杂交抑制了足够强的SEESAW抑制，因此在此模型中，新的物理量表可能与TEV一样低，并且在不久的将来可能会从LHC数据中发现信号。
We propose a type of hybrid Seesaw model that combines Type-1 and Type-2 Seesaw mechanism in multiplicative way to generate tree level Majorana neutrino mass and provides a Dark Matter candidate. The model extends the Standard Model by extra gauge symmetry $U(1)_{D}$ and hidden sector consisted of chiral fermions and additional scalar fields. After spontaneous symmetry breaking, light neutrino masses are generated not only by exchange of the new heavy fermions as Type-1 Seesaw, but also by coupling to the naturally small induced vacuum expectation value of new heavy scalar as Type-2 Seesaw. An unbroken residue of $U(1)_{D}$ protects the lightest Dirac fermion required by anomaly cancellation in hidden sector from decaying, therefore giving rise to a Dark Matter candidate. Due to strong enough Seesaw suppression from our hybridization, new physics scale can be as low as TeV in this model and discovering signal from LHC data is possible in near future.
