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arXiv 1707.01286hep-ph
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破坏暗物质宇称的最小SO(10)衰变、统一、真空稳定性和可验证的质子衰变

Matter Parity Violating Dark Matter Decay in Minimal SO(10), Unification, Vacuum Stability and Verifiable Proton Decay

Biswonath Sahoo, M. K Parida, Mainak Chakraborty

摘要:

在非超对称SO(10)直接破缺到标准模型的情况下,我们研究了暗物质(DM)通过与右手中微子(RH $ν$)的混合衰变产生I型跷跷板质量的高能冰立方中微子的可能性.而不是一个普遍的混合和一个共同的重RH $ν$质量在最近的标准模型扩展中提出的,我们发现,潜在的夸克轻子对称性导致自然分层RH $ν$质量预测与他们每个人单独的混合。我们确定这些混合从跷跷板预测的DM衰变率到轻中微子的味道。我们进一步表明,这些混合起源于普朗克尺度辅助自发破缺的物质宇称需要解决相关的宇宙畴壁问题。这导致了一个新的大型强子对撞机可访问的物质宇称奇希格斯标量的预测,也完成了真空稳定性的希格斯潜在的质量$M_{χ_S}\simeq 178$ GeV。两个独立的最小SO(10)模型进一步指出,预测这样的暗物质动力学,其中一个单一的标量子多重态从${126}^{\dagger}_H$或${210}_H$的中间质量实现精确规范耦合统一。尽管存在两个大的希格斯表象和费米子暗物质主机,${45}_F$,实验上可访问的质子寿命也预测减少不确定性。

英文摘要:

In direct breaking of non-supersymmetric SO(10) to the standard model, we investigate the possibility that dark matter (DM) decaying through its mixing with right-handed neutrino (RH$ν$) produces high energy IceCube neutrinos having type-I seesaw masses. Instead of one universal mixing and one common heavy RH$ν$ mass proposed in a recent standard model extension, we find that underlying quark-lepton symmetry resulting in naturally hierarchical RH$ν$ masses predict a separate mixing with each of them. We determine these mixings from the seesaw prediction of the DM decay rates into the light neutrino flavors. We further show that these mixings originate from Planck-scale assisted spontaneously broken matter parity needed to resolve the associated cosmological domain wall problem. This leads to the prediction of a new LHC accessible matter-parity odd Higgs scalar which also completes vacuum stability in the Higgs potential for its mass $M_{χ_S}\simeq 178$ GeV. Two separate minimal SO(10) models are further noted to predict such dark matter dynamics where a single scalar submultiplet from ${126}^{\dagger}_H$ or ${210}_H$ of intermediate mass achieves precision gauge coupling unification. Despite the presence of two large Higgs representations and the fermionic dark matter host, ${45}_F$, experimentally accessible proton lifetimes are also predicted with reduced uncertainties.

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