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Naturalness, the hyperbolic branch, and prospects for the observation of charged Higgs bosons at high luminosity LHC and 27 TeV LHC

机译:在高亮度LHC和27 TEV LHC下观察Higgs玻色子的自然,双曲线分支和前景

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One of the early criterion proposed for naturalness was a relatively small minimal supersymmetric standard model (MSSM) Higgs mixing parameter μ with μ=MZ of the order of a few. A relatively small μ may lead to heavier Higgs masses (H0, A, H± in MSSM) which are significantly lighter than other scalars such as squarks. Such a situation is realized on the hyperbolic branch of radiative breaking of the electroweak symmetry. In this analysis, we construct supergravity unified models with relatively small μ in the sense described above and discuss the search for the charged Higgs boson H± at HL-LHC and HELHC, where we also carry out a relative comparison of the discovery potential of the two using the decay channel H± → τν. It is shown that an analysis based on the traditional linear cuts on signals and backgrounds is not very successful in extracting the signal, while, in contrast, machine learning techniques such as boosted decision trees prove to be far more effective. Thus, it is shown that models not discoverable with the conventional cut analyses become discoverable with machine learning techniques. Using boosted decision trees, we consider several benchmarks and analyze the potential for their 5σ discovery at the 14 TeV HL-LHC and at 27 TeV HE-LHC. It is shown that while the ten benchmarks considered with the charged Higgs boson mass in the range 373-812 GeVare all discoverable at HE-LHC, only four of the ten with Higgs boson masses in the range 373-470 GeVare discoverable at HL-LHC. Further, while the model points discoverable at both HE-LHC and HL-LHC would require up to seven years of running time at HL-LHC, they could all be discovered in a period of a few months at HE-LHC. The analysis shows that a transition from HL-LHC to HE-LHC when technologically feasible would expedite the discovery of the charged Higgs for the benchmarks considered in this work.We note that the observation of a charged Higgs boson with mass in the range indicated would lend
机译:用于自然所提出的早期标准之一是相对较小的超微性标准模型(MSSM)HIGGS混合参数μ,其μ= MZ的μ=少数。相对较小的μ可能导致较重的HIGG质量(H0,A,H±MSSM),其比诸如划分的其他标量显着轻微。在电挖掘对称性辐射断裂的双曲线分支上实现了这种情况。在该分析中,我们在上述意义上构建具有相对较小的μ的超名度统一模型,并讨论HL-LHC和HELHC的带电HIGGS BOSON H±的搜索,在那里我们还执行了对发现潜力的相对比较两个使用衰减通道H±→τν。结果表明,基于传统线性切割对信号和背景的分析在提取信号方面不是很成功,而相比之下,诸如提升决策树的机器学习技术被证明是更有效的。因此,显示不可发现的型号与传统的剪切分析都可以通过机器学习技术发现。使用提升决策树,我们考虑了几个基准,并分析了14 Tev HL-LHC和27 Tev He-LHC的5σ发现的潜力。结果表明,虽然与收费的HIGGS玻色子群体考虑的十个基准,但在HE-LHC中的所有可被发现的全部发现,虽然在HL-LHC的373-470 GVARE中只有四个带有HGGS玻色子的四个。 。此外,在HE-LHC和HL-LHC中发现的模型点在HL-LHC时需要多达七年的运行时间,而在HL-LHC中可以在几个月内发现它们在HE-LHC的时间内。该分析表明,在技术可行的情况下,从HL-LHC到HE-LHC的过渡将加快发现这项工作中考虑的基准的被指控的HIGGS。我们注意到在所示范围内具有群众的带电的HIGGS玻色子的观察借

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