Testing a 95 GeV Scalar at the CEPC with Machine Learning
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866918376755953664 |
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| author | Dong, Yabo Ruan, Manqi Wang, Kun Yang, Haijun Zhu, Jingya |
| author_facet | Dong, Yabo Ruan, Manqi Wang, Kun Yang, Haijun Zhu, Jingya |
| contents | Several possible excesses around 95 GeV hint at an additional light scalar beyond the Standard Model. We examine the capability of the CEPC to test this hypothesis in the Higgsstrahlung channel $e^{+}e^{-} \to ZS$ with $Z \toμ^{+}μ^{-}$ and $S\toτ^{+}τ^{-}$. Full detector simulation shows that the optimal center-of-mass energy to study the 95 GeV light scalar is 210 GeV. A deep neural network classifier reduces the luminosity required for discovery by half. At $L = 20~\mathrm{ab}^{-1}$, the CEPC's $5σ$ sensitivity to the signal strength $μ_{ττ}^{ZS}$ reaches 0.016 and 0.020 for $\sqrt{s} =$ 210 GeV and 240 GeV, respectively. The corresponding thresholds for a 5% precision measurement are $μ_{ττ}^{ZS} > 0.10$ and $>0.12$. At $\sqrt{s}=$ 210 GeV (240 GeV), $5σ$ coverage of all N2HDM-Flipped samples with $χ^2_{h_{95}}<7.82$ requires $L=800\ \mathrm{fb}^{-1}$ (1.22 $\mathrm{ab}^{-1}$). These results establish a 210 GeV run, augmented by machine-learning selection, as the most efficient strategy to confirm or refute the 95 GeV excess at future lepton colliders. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2506_21454 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Testing a 95 GeV Scalar at the CEPC with Machine Learning Dong, Yabo Ruan, Manqi Wang, Kun Yang, Haijun Zhu, Jingya High Energy Physics - Phenomenology High Energy Physics - Experiment Several possible excesses around 95 GeV hint at an additional light scalar beyond the Standard Model. We examine the capability of the CEPC to test this hypothesis in the Higgsstrahlung channel $e^{+}e^{-} \to ZS$ with $Z \toμ^{+}μ^{-}$ and $S\toτ^{+}τ^{-}$. Full detector simulation shows that the optimal center-of-mass energy to study the 95 GeV light scalar is 210 GeV. A deep neural network classifier reduces the luminosity required for discovery by half. At $L = 20~\mathrm{ab}^{-1}$, the CEPC's $5σ$ sensitivity to the signal strength $μ_{ττ}^{ZS}$ reaches 0.016 and 0.020 for $\sqrt{s} =$ 210 GeV and 240 GeV, respectively. The corresponding thresholds for a 5% precision measurement are $μ_{ττ}^{ZS} > 0.10$ and $>0.12$. At $\sqrt{s}=$ 210 GeV (240 GeV), $5σ$ coverage of all N2HDM-Flipped samples with $χ^2_{h_{95}}<7.82$ requires $L=800\ \mathrm{fb}^{-1}$ (1.22 $\mathrm{ab}^{-1}$). These results establish a 210 GeV run, augmented by machine-learning selection, as the most efficient strategy to confirm or refute the 95 GeV excess at future lepton colliders. |
| title | Testing a 95 GeV Scalar at the CEPC with Machine Learning |
| topic | High Energy Physics - Phenomenology High Energy Physics - Experiment |
| url | https://arxiv.org/abs/2506.21454 |