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arXiv 0802.4228hep-phhep-ex
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超对称预测GUT模型中的轻子味破坏

Lepton Flavor Violation in Predictive Supersymmetric GUT Models

Carl H. Albright, Mu-Chun Chen

摘要:

已经建立了许多理论模型来解释中微子的质量和混合模式。虽然许多模型将被淘汰,一旦更准确的确定的混合参数,特别是$\sin^2 2θ_{13}$,获得,带电轻子味破坏(LFV)实验能够区分甚至进一步的模型。本文研究了五个预测超对称SO(10)模型中的各种罕见LFV过程,如$\ell_{i} \to \ell_{j} + γ$和$μ-e$转换,以及它们在约束最小超对称标准模型中的允许软超对称破缺参数空间.利用威尔金森微波各向异性探测器暗物质的限制,我们得到这些罕见的过程的分支比的下限,并发现至少有三个我们认为产生的预测$μ\to e + γ$的五个模型,将在PSI的MEG协作测试。此外,下一代$μ-e$转换实验对所有五个模型的预测都很敏感,这使得它成为测试这些模型的一种更强大的方法。虽然一般的研究强调了反应堆中微子角$θ_{13}$和最重的右手中微子$M_3$的质量上的这些罕见的过程的分支比的依赖,我们发现非常大质量的$M_3$是更显着的比大$θ_{13}$在导致分支比接近目前的上限。

英文摘要:

There have been many theoretical models constructed which aim to explain the neutrino masses and mixing patterns. While many of the models will be eliminated once more accurate determinations of the mixing parameters, especially $\sin^2 2θ_{13}$, are obtained, charged lepton flavor violation (LFV) experiments are able to differentiate even further among the models. In this paper, we investigate various rare LFV processes, such as $\ell_{i} \to \ell_{j} + γ$ and $μ-e$ conversion, in five predictive supersymmetric (SUSY) SO(10) models and their allowed soft-SUSY breaking parameter space in the constrained minimal SUSY standard model. Utilizing the Wilkinson Microwave Anisotropy Probe dark matter constraints, we obtain lower bounds on the branching ratios of these rare processes and find that at least three of the five models we consider give rise to predictions for $μ\to e + γ$ that will be tested by the MEG Collaboration at PSI. In addition, the next generation $μ-e$ conversion experiment has sensitivity to the predictions of all five models, making it an even more robust way to test these models. While generic studies have emphasized the dependence of the branching ratios of these rare processes on the reactor neutrino angle $θ_{13}$ and the mass of the heaviest right-handed neutrino $M_3$, we find very massive $M_3$ is more significant than large $θ_{13}$ in leading to branching ratios near to the present upper limits.

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