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arXiv 2207.09602hep-phhep-ex
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由Higgs对通过$b\bar{b}b\bar{b}$末态产生的双Higgs偶态模型的灵敏度

Sensitivity on Two-Higgs-Doublet Models from Higgs-Pair Production via $b\bar{b}b\bar{b}$ Final State

Kingman Cheung, Yi-Lun Chung, Shih-Chieh Hsu

摘要:

众所周知,希格斯玻色子玻色子对的产生可以探测电弱对称破缺扇区的结构。我们说明了使用胶子融合过程$pp \to H \to h h \to (b\bar b) (b\bar b)$的框架中的两个希格斯偶极子模型和机器学习方法(三流卷积神经网络)如何可以大大提高信号背景的歧视,从而提高了相关参数空间的灵敏度覆盖。我们表明,这样的$gg \to hh \to b \bar b b\bar b$过程可以进一步探测目前允许的参数空间的HiggsSignals和HiggsBounds在HL-LHC。显示了I至IV型的结果。

英文摘要:

Higgs boson pair production is well known to probe the structure of the electroweak symmetry breaking sector. We illustrate using the gluon-fusion process $pp \to H \to h h \to (b\bar b) (b\bar b)$ in the framework of two-Higgs-doublet models and how the machine learning approach (three-stream convolutional neural network) can substantially improve the signal-background discrimination and thus improves the sensitivity coverage of the relevant parameter space. We show that such $gg \to hh \to b \bar b b\bar b$ process can further probe the currently allowed parameter space by HiggsSignals and HiggsBounds at the HL-LHC. The results for Types I to IV are shown.

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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