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arXiv 0705.1496hep-ph
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具有重标量的MSSM

The MSSM with heavy scalars

Nicolas Bernal, Abdelhak Djouadi, Pietro Slavich

摘要:

我们进行了全面的分析的最小超对称标准模型(MSSM)的情况下,标量合作伙伴的费米子和希格斯粒子(除了标准模型一样的一个)被假定为非常重,并从低能谱。我们首先总结了我们的确定的质谱,其中我们包括一个循环的辐射校正和恢复到所有订单的大标量质量的领先的矩阵,并描述了这些功能的实现中的FORTRAN代码SuSpect计算的质量和耦合的MSSM粒子。然后,我们详细研究了该模型的现象学的情况下,在大统一体尺度上的高更诺质量参数是非普遍的,这导致了非常有趣的功能,不存在于广泛研究的情况下,普遍的高更诺质量参数。我们讨论的约束,从对撞机搜索和高精度测量,宇宙学约束的遗迹丰度的中性伴子候选人在宇宙中的暗物质-中性伴子湮灭出现新的和有趣的渠道-和胶子寿命。然后,我们分析,在非普适的情况下,希格斯玻色子的衰变(特别是衰变为超对称粒子和贡献),电荷和中性伴子(特别是衰变为希格斯玻色子玻色子和光子)和胶子,并强调与普适的情况下的不同之处。

英文摘要:

We perform a comprehensive analysis of the Minimal Supersymmetric Standard Model (MSSM) in the scenario where the scalar partners of the fermions and the Higgs particles (except for the Standard-Model-like one) are assumed to be very heavy and are removed from the low-energy spectrum. We first summarize our determination of the mass spectrum, in which we include the one-loop radiative corrections and resum to all orders the leading logarithms of the large scalar masses, and describe the implementation of these features in the FORTRAN code SuSpect which calculates the masses and couplings of the MSSM particles. We then study in detail the phenomenology of the model in scenarios where the gaugino mass parameters are non-universal at the GUT scale, which leads to very interesting features that are not present in the widely studied case of universal gaugino mass parameters. We discuss the constraints from collider searches and high-precision measurements, the cosmological constraints on the relic abundance of the neutralino candidate for the Dark Matter in the Universe - where new and interesting channels for neutralino annihilation appear - and the gluino lifetime. We then analyze, in the case of non-universal gaugino masses, the decays of the Higgs boson (in particular decays into and contributions of SUSY particles), of charginos and neutralinos (in particular decays into Higgs bosons and photons) and of gluinos, and highlight the differences from the case of universal gaugino masses.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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