MSSM forecast for the LHC
MSSM forecast for the LHC
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MSSM 对 LHC 的预测
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
R. R. Austri
中科院分区：
文献类型：
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作者：
M. E. Cabrera;A. Casas;R. R. Austri
我们进行预测的MSSM与通用软条款（CMSSM）的大型强子对撞机，基于改进的贝叶斯分析。我们不纳入特设的微调措施，以惩罚不自然的可能性：这种惩罚来自贝叶斯分析本身时，MZ的实验值被认为是。这允许扫描整个参数空间，允许任意大的软项。尽管如此，低能量区域在统计学上仍然是有利的（甚至在包括暗物质或g-2约束之前）。与其他研究相反，结果几乎不受改变软项上限的影响。当使用平坦或对数先验时，结果也非常稳定，这是由于在这两种情况下低能区域的统计权重较大。然后，我们将所有重要的实验约束的分析，获得一个映射的概率密度的MSSM参数空间，即预测的MSSM。由于并非所有的实验信息都同样稳健，因此我们根据所使用的可观测值组进行单独分析。当只使用最鲁棒的参数时，参数空间的有利区域包含LHC范围之外的重要部分。如果希格斯粒子的质量不接近目前的实验极限，那么这种效应就会得到加强，当暗物质的约束被包括在内时，这种效应就会消失。只有当考虑g-2约束（基于e+e−数据）时，优选区域（μ > 0）才在LHC范围内。我们还对正μ和负μ的可能性进行了贝叶斯比较。
We perform a forecast of the MSSM with universal soft terms (CMSSM) for the LHC, based on an improved Bayesian analysis. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises from the Bayesian analysis itself when the experimental value of MZ is considered. This allows to scan the whole parameter space, allowing arbitrarily large soft terms. Still the low-energy region is statistically favoured (even before including dark matter or g-2 constraints). Contrary to other studies, the results are almost unaffected by changing the upper limits taken for the soft terms. The results are also remarkable stable when using flat or logarithmic priors, a fact that arises from the larger statistical weight of the low-energy region in both cases. Then we incorporate all the important experimental constrains to the analysis, obtaining a map of the probability density of the MSSM parameter space, i.e. the forecast of the MSSM. Since not all the experimental information is equally robust, we perform separate analyses depending on the group of observables used. When only the most robust ones are used, the favoured region of the parameter space contains a significant portion outside the LHC reach. This effect gets reinforced if the Higgs mass is not close to its present experimental limit and persits when dark matter constraints are included. Only when the g-2 constraint (based on e+e− data) is considered, the preferred region (for μ > 0) is well inside the LHC scope. We also perform a Bayesian comparison of the positive- and negative-μ possibilities.
影响因子：
6.4
作者：
A. Ibarra;D. Tran
通讯作者：
A. Ibarra;D. Tran