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| CMS-HIG-22-002 ; CERN-EP-2023-061 | ||
| Search for the lepton-flavor violating decay of the Higgs boson and additional Higgs bosons in the e$ \mu $ final state in proton-proton collisions at $ \sqrt{s} = $ 13 TeV | ||
| CMS Collaboration | ||
| 29 May 2023 | ||
| Phys. Rev. D 108 (2023) 072004 | ||
| Abstract: A search for the lepton-flavor violating decay of the Higgs boson and potential additional Higgs bosons with a mass in the range 110-160 GeV to an $ \mathrm{e}^{\pm}\mu^{\mp} $ pair is presented. The search is performed with a proton-proton collision dataset at a center-of-mass energy of 13 TeV collected by the CMS experiment at the LHC, corresponding to an integrated luminosity of 138 fb$ ^{-1} $. No excess is observed for the Higgs boson. The observed (expected) upper limit on the $ \mathrm{e}^{\pm}\mu^{\mp} $ branching fraction for it is determined to be 4.4 (4.7) $\times$ 10$^{-5} $ at 95% confidence level, the most stringent limit set thus far from direct searches. The largest excess of events over the expected background in the full mass range of the search is observed at an $ \mathrm{e}^{\pm}\mu^{\mp} $ invariant mass of approximately 146 GeV with a local (global) significance of 3.8 (2.8) standard deviations. | ||
| Links: e-print arXiv:2305.18106 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; HepData record ; CADI line (restricted) ; | ||
| Figures & Tables | Summary | Additional Figures & Tables | References | CMS Publications |
|---|
| Figures | |
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Figure 1:
The $ {m_{\mathrm{e}\mu}} $ distributions of the data, simulated backgrounds and signals of $ {\mathrm{H}\to\mathrm{e}\mu} $ in the ggH (left) and the VBF categories (right). A $ {\mathcal{B}(\mathrm{H}\to\mathrm{e}\mu)}= $ 0.2% is assumed for the signal for illustration. The lower panel in each plot shows the ratio of the data to the total estimated background. The uncertainty band corresponds to the background uncertainties, adding in quadrature the statistical and the SM cross section uncertainties. |
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Figure 1-a:
The $ {m_{\mathrm{e}\mu}} $ distributions of the data, simulated backgrounds and signals of $ {\mathrm{H}\to\mathrm{e}\mu} $ in the ggH category. A $ {\mathcal{B}(\mathrm{H}\to\mathrm{e}\mu)}= $ 0.2% is assumed for the signal for illustration. The lower panel in each plot shows the ratio of the data to the total estimated background. The uncertainty band corresponds to the background uncertainties, adding in quadrature the statistical and the SM cross section uncertainties. |
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Figure 1-b:
The $ {m_{\mathrm{e}\mu}} $ distributions of the data, simulated backgrounds and signals of $ {\mathrm{H}\to\mathrm{e}\mu} $ in the VBF category. A $ {\mathcal{B}(\mathrm{H}\to\mathrm{e}\mu)}= $ 0.2% is assumed for the signal for illustration. The lower panel in each plot shows the ratio of the data to the total estimated background. The uncertainty band corresponds to the background uncertainties, adding in quadrature the statistical and the SM cross section uncertainties. |
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Figure 2:
The ggH and VBF BDT discriminant distributions of the data, simulated backgrounds and signals of $ {\mathrm{H}\to\mathrm{e}\mu} $ for each BDT trained in the ggH (left) and the VBF categories (right). A $ \mathcal{B}(\mathrm{H}\to\mathrm{e}\mu) =$ 1.0% is assumed for the signal for illustration. The lower panel in each plot shows the ratio of the data to the total estimated background. The uncertainty band corresponds to the background uncertainties, adding in quadrature the statistical and the SM cross section uncertainties. Vertical lines in the plots illustrate boundaries of the subcategories: ggH cat 0-3 and VBF cat 0-1, as defined in Section 6.2. Events in the shaded region of the VBF category with a VBF BDT discriminant less than 0.78 are discarded since their sensitivity is an order of magnitude lower than other subcategories. |
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Figure 2-a:
The BDT discriminant distribution of the data, simulated backgrounds and signals of $ {\mathrm{H}\to\mathrm{e}\mu} $ for each BDT trained in the ggH category. A $ \mathcal{B}(\mathrm{H}\to\mathrm{e}\mu) =$ 1.0% is assumed for the signal for illustration. The lower panel shows the ratio of the data to the total estimated background. The uncertainty band corresponds to the background uncertainties, adding in quadrature the statistical and the SM cross section uncertainties. The vertical lines in the plot illustrate boundaries of the subcategories: ggH cat 0-3, as defined in Section 6.2. |
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Figure 2-b:
The BDT discriminant distribution of the data, simulated backgrounds and signals of $ {\mathrm{H}\to\mathrm{e}\mu} $ for each BDT trained in the VBF category. A $ \mathcal{B}(\mathrm{H}\to\mathrm{e}\mu) =$ 1.0% is assumed for the signal for illustration. The lower panel shows the ratio of the data to the total estimated background. The uncertainty band corresponds to the background uncertainties, adding in quadrature the statistical and the SM cross section uncertainties. The vertical lines in the plot illustrate boundaries of the subcategories: VBF cat 0-1, as defined in Section 6.2. Events in the shaded region of the VBF category with a VBF BDT discriminant less than 0.78 are discarded since their sensitivity is an order of magnitude lower than other subcategories. |
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Figure 3:
The $ p_{\mathrm{T}}^\text{miss} $ distributions of the data, simulated backgrounds and signals of $ {\mathrm{H}\to\mathrm{e}\mu} $ in the ggH (left) and the VBF categories (right). A $ \mathcal{B}(\mathrm{H}\to\mathrm{e}\mu)= $ 1.0% is assumed for the signal for illustration. The lower panel in each plot shows the ratio of the data to the total estimated background. The uncertainty band corresponds to the background uncertainties, adding in quadrature the statistical and the SM cross section uncertainties. |
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Figure 3-a:
The $ p_{\mathrm{T}}^\text{miss} $ distributions of the data, simulated backgrounds and signals of $ {\mathrm{H}\to\mathrm{e}\mu} $ in the ggH category. A $ \mathcal{B}(\mathrm{H}\to\mathrm{e}\mu)= $ 1.0% is assumed for the signal for illustration. The lower panel shows the ratio of the data to the total estimated background. The uncertainty band corresponds to the background uncertainties, adding in quadrature the statistical and the SM cross section uncertainties. |
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Figure 3-b:
The $ p_{\mathrm{T}}^\text{miss} $ distributions of the data, simulated backgrounds and signals of $ {\mathrm{H}\to\mathrm{e}\mu} $ in the VBF category. A $ \mathcal{B}(\mathrm{H}\to\mathrm{e}\mu)= $ 1.0% is assumed for the signal for illustration. The lower panel shows the ratio of the data to the total estimated background. The uncertainty band corresponds to the background uncertainties, adding in quadrature the statistical and the SM cross section uncertainties. |
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Figure 4:
Example fits of the signal models to the simulated $ {{\mathrm{H}\to\mathrm{e}\mu}} $ signal in the analysis categories ggH cat 0 and ggH cat 3 (left), as well as VBF cat 0 and VBF cat 1 (right), summing events from both the ggH and VBF production modes. Half of the smallest symmetric $ {m_{\mathrm{e}\mu}} $ interval that contains 68% of the signal events, $ {\sigma_{\text{eff}}} $, is shown in the legends for each signal as an illustration of the signal resolution. The signal resolution in general improves with the signal purity of the analysis categories. |
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Figure 4-a:
Example fits of the signal models to the simulated $ {{\mathrm{H}\to\mathrm{e}\mu}} $ signal in the analysis categories ggH cat 0 and ggH cat 3, summing events from both the ggH and VBF production modes. Half of the smallest symmetric $ {m_{\mathrm{e}\mu}} $ interval that contains 68% of the signal events, $ {\sigma_{\text{eff}}} $, is shown in the legends for each signal as an illustration of the signal resolution. The signal resolution in general improves with the signal purity of the analysis categories. |
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Figure 4-b:
Example fits of the signal models to the simulated $ {{\mathrm{H}\to\mathrm{e}\mu}} $ signal in the analysis categories VBF cat 0 and VBF cat 1, summing events from both the ggH and VBF production modes. Half of the smallest symmetric $ {m_{\mathrm{e}\mu}} $ interval that contains 68% of the signal events, $ {\sigma_{\text{eff}}} $, is shown in the legends for each signal as an illustration of the signal resolution. The signal resolution in general improves with the signal purity of the analysis categories. |
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Figure 5:
Observed (expected) 95% CL upper limits on $ {\mathcal{B}(\mathrm{H}\to\mathrm{e}\mu)} $ for each individual analysis category (as shown in the left axis label) and for the combination of all analysis categories. |
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Figure 6:
Constraints on the lepton-flavor violating Yukawa couplings, $ {|Y_{\mathrm{e}\mu}|} $ and $ {|Y_{\mu\mathrm{e}}|} $. The observed (expected) limit in black (red) line is derived from the limit on $ {\mathcal{B}(\mathrm{H}\to\mathrm{e}\mu)} $ in this analysis. The green (yellow) band indicates the one (two) standard deviation uncertainty in the expected limit. The hashed region is excluded by this direct search. Other shaded regions represent indirect constraints derived from the null searches for $ {\mu\to3\mathrm{e}} $ (gray) [89], $ {\mu\to\mathrm{e}} $ conversion (light blue) [90], and $ {\mu\to\mathrm{e}\gamma} $ (dark green) [31]. The flavor-diagonal Yukawa couplings, $ {|Y_{\mathrm{e}\mathrm{e}}|} $ and $ {|Y_{\mu\mu}|} $, are assumed to be at their SM values in the calculation of these indirect limits. The purple line is the theoretical naturalness limit of $ {|Y_{\mathrm{e}\mu}Y_{\mu\mathrm{e}}|\leq{m_{\mathrm{e}}}m_{\mu}/v^2} $, where $ {v} $ is the vacuum expectation value of the Higgs field. Dotted lines represent the corresponding constraints on $ {|Y_{\mathrm{e}\mu}|} $ and $ {|Y_{\mu\mathrm{e}}|} $ at upper limits on $ {{\mathcal{B}(\mathrm{H}\to\mathrm{e}\mu)}} $ at 10$^{-5}$, 10$^{-6}$, 10$^{-7}$, and 10$^{-8} $, respectively. |
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Figure 7:
Left: the observed (expected) 95% CL upper limits on $ {\sigma(\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu)} $ as a function of the hypothesised $ {m_{\mathrm{X}}} $ assuming the relative SM-like production cross sections of the ggH and VBF production modes. Right: the observed local $ p $-values against the background-only hypothesis are shown as a function of the hypothesised $ {m_{\mathrm{X}}} $. |
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Figure 7-a:
The observed (expected) 95% CL upper limits on $ {\sigma(\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu)} $ as a function of the hypothesised $ {m_{\mathrm{X}}} $ assuming the relative SM-like production cross sections of the ggH and VBF production modes. |
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Figure 7-b:
The observed local $ p $-values against the background-only hypothesis are shown as a function of the hypothesised $ {m_{\mathrm{X}}} $. |
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Figure 8:
The $ {m_{\mathrm{e}\mu}} $ distribution of the observed data is shown, with the $ S{+}B $ fit at $ m_{\mathrm{X}}= $ 146 GeV in red solid line, and the background component of the fit in red dotted line. Events and fit in each category are weighted by $ {S/(S+B)} $. The one and two standard deviation uncertainty bands of the background component are shown in green and yellow. The lower panel shows the residuals after subtracting the background component of the fit from data. |
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Figure 9:
Observed (expected) 95% CL upper limits on $ {\sigma(\mathrm{p}\mathrm{p} \to \mathrm{X}(146) \to \mathrm{e} \mu)} $ for each individual analysis category (as shown in the left axis label) and for the combination of all analysis categories assuming the relative SM-like production cross sections of the ggH and VBF production modes. |
| Tables | |
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Table 1:
Range of the ggH (VBF) BDT discriminant to define the ggH (VBF) subcategories, and the corresponding expected background ($ {B} $), and signal yield of $ \mathrm{H}\to\mathrm{e}\mu $ at $ \mathcal{B}= $ 10$^{-4} $ ($ {S} $) at an integrated luminosity of 138 fb$ ^{-1} $. The yields are estimated by the number of MC events within a $ {m_{\mathrm{e}\mu}} $ interval of 125 GeV $\pm\sigma_\text{eff} $, where $ {\sigma_\text{eff}} $ is half of the smallest symmetric interval that contains 68% of the signal events in each category. The fraction contributions of the expected signal yields from the ggH and VBF production mode are listed. An estimate of the expected significance in each category by $ {S/\sqrt{B}} $ is also listed. |
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Table 2:
Systematic uncertainties in the expected signal yields from different sources for the ggH and VBF production modes. All the uncertainties are treated as correlated among categories. |
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Table 3:
Observed and expected 95% CL upper limits on $ {\mathcal{B}(\mathrm{H}\to\mathrm{e}\mu)} $ at for each individual analysis category and for the combination of all analysis categories. |
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Table 4:
Observed (expected) 95% CL upper limits, best fit, and local significance in unit of standard deviation ($ {\sigma} $) of $ {\sigma(\mathrm{p}\mathrm{p} \to \mathrm{X}(146) \to \mathrm{e} \mu)} $ for each individual analysis category and for the combination of all analysis categories. |
| Summary |
| Searches for the lepton-flavor violation decay of H and X with a $ {m_{\mathrm{X}}} $ in the range 110-160 GeV have been performed in the $ \mathrm{e} \mu $ final state in data collected by the CMS experiment. The data correspond to an integrated luminosity of 138 fb$ ^{-1} $ of pp collisions at a center-of-mass energy of 13 TeV. The observed (expected) upper limit on the branching fraction of the H decay $ {\mathcal{B}(\mathrm{H}\to\mathrm{e}\mu)} $ is found to be 4.4 (4.7) $\times$ 10$^{-5} $ at 95% confidence level, which is the most stringent direct limit set thus far. Upper limits on the cross sections of $ {\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu} $ are set in the $ {m_{\mathrm{X}}} $ range 110-160 GeV at 95% confidence level. This is the first result of a direct search for $ {\mathrm{X}\to\mathrm{e}\mu} $, with $ {m_{\mathrm{X}}} $ below twice the W boson mass. The largest excess of events over the expected background is observed with a local (global) significance of 3.8 (2.8) standard deviations at an invariant mass of the $ \mathrm{e} \mu $ final state of around 146 GeV. The observed significance of this excess is insufficient to draw any conclusions. More data will be needed to clarify the nature of the excess. |
| Additional Figures | |
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Additional Figure 1:
To investigate whether there is sculpting of the $ m_{\mathrm{e}\mu} $ spectrum near the $ m_{\mathrm{H}} $ or $ m_{\mathrm{X}} $ of the signal samples, we look at the $ m_{\mathrm{e}\mu} $ distributions in different ranges of the $ {\mathrm{g}\mathrm{g}\mathrm{H}} $ BDT discriminant in the $ {\mathrm{g}\mathrm{g}\mathrm{H}} $ category. The upper panel shows the $ m_{\mathrm{e}\mu} $ density distributions of the MC background samples in quantiles of the $ {\mathrm{g}\mathrm{g}\mathrm{H}} $ BDT discriminant with the same expected yield. The total $ m_{\mathrm{e}\mu} $ density distribution is also plotted. The lower panel shows the ratio of each quantile to the total density distribution. No localized patterns at $ {m_{\mathrm{e}\mu}=} $ 110, 120, 125, 130, 140, 150, 160 GeV, corresponding to the $ m_{\mathrm{H}} $ or $ m_{\mathrm{X}} $ of the signal samples used in the BDT trainings, is observed for events with high or low BDT discriminants. This demonstrates that the BDTs do not preferentially identify events near $ m_{\mathrm{H}} $ or $ m_{\mathrm{X}} $ as signal. |
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Additional Figure 2:
To investigate whether there is sculpting of the $ m_{\mathrm{e}\mu} $ spectrum near the $ m_{\mathrm{H}} $ or $ m_{\mathrm{X}} $ of the signal samples, we look at the $ m_{\mathrm{e}\mu} $ distributions in different ranges of the VBF BDT discriminant in the VBF category. The upper panel shows the $ m_{\mathrm{e}\mu} $ density distributions of the MC background samples in quantiles of the VBF BDT discriminant with the same expected yield. The total $ m_{\mathrm{e}\mu} $ density distribution is also plotted. The lower panel shows the ratio of each quantile to the total density distribution. No localized patterns at $ {m_{\mathrm{e}\mu}=} $ 110, 120, 125, 130, 140, 150, 160 GeV, corresponding to the $ m_{\mathrm{H}} $ or $ m_{\mathrm{X}} $ of the signal samples used in the BDT trainings, is observed for events with high or low BDT discriminants. This demonstrates that the BDTs do not preferentially identify events near $ m_{\mathrm{H}} $ or $ m_{\mathrm{X}} $ as signal. |
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Additional Figure 3:
The $ {\mathrm{g}\mathrm{g}\mathrm{H}} $ discriminant density distributions of the MC signal samples in the $ {\mathrm{g}\mathrm{g}\mathrm{H}} $ category are shown. The lower panel shows the ratios of the $ {{\mathrm{X}\to\mathrm{e}\mu}} $ samples to the $ {{\mathrm{H}\to\mathrm{e}\mu}} $ samples. The uncertainty band corresponds to the statistical uncertainties of the $ {{\mathrm{H}\to\mathrm{e}\mu}} $ samples. |
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Additional Figure 4:
The VBF discriminant density distributions of the MC signal samples in the VBF category are shown. The lower panel shows the ratios of the $ {{\mathrm{X}\to\mathrm{e}\mu}} $ samples to the $ {{\mathrm{H}\to\mathrm{e}\mu}} $ samples. The uncertainty band corresponds to the statistical uncertainties of the $ {{\mathrm{H}\to\mathrm{e}\mu}} $ samples. |
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Additional Figure 5:
The $ m_{\mathrm{e}\mu} $ distribution of the observed data in the category $ {\mathrm{g}\mathrm{g}\mathrm{H}} $ cat 0 is shown, with the $ S{+}B $ fit at $ m_{\mathrm{X}}= $ 146 GeV in solid red line, and the background component of the fit in dotted red line. The green and yellow bands represent the one and two standard deviations of the background component. The lower panel shows the residuals after subtracting the background component of the fit from data. |
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Additional Figure 6:
The $ m_{\mathrm{e}\mu} $ distribution of the observed data in the category $ {\mathrm{g}\mathrm{g}\mathrm{H}} $ cat 1 is shown, with the $ S{+}B $ fit at $ m_{\mathrm{X}}= $ 146 GeV in solid red line, and the background component of the fit in dotted red line. The green and yellow bands represent the one and two standard deviations of the background component. The lower panel shows the residuals after subtracting the background component of the fit from data. |
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Additional Figure 7:
The $ m_{\mathrm{e}\mu} $ distribution of the observed data in the category $ {\mathrm{g}\mathrm{g}\mathrm{H}} $ cat 2 is shown, with the $ S{+}B $ fit at $ m_{\mathrm{X}}= $ 146 GeV in solid red line, and the background component of the fit in dotted red line. The green and yellow bands represent the one and two standard deviations of the background component. The lower panel shows the residuals after subtracting the background component of the fit from data. |
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Additional Figure 8:
The $ m_{\mathrm{e}\mu} $ distribution of the observed data in the category $ {\mathrm{g}\mathrm{g}\mathrm{H}} $ cat 3 is shown, with the $ S{+}B $ fit at $ m_{\mathrm{X}}= $ 146 GeV in solid red line, and the background component of the fit in dotted red line. The green and yellow bands represent the one and two standard deviations of the background component. The lower panel shows the residuals after subtracting the background component of the fit from data. |
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Additional Figure 9:
The $ m_{\mathrm{e}\mu} $ distribution of the observed data in the category VBF cat 0 is shown, with the $ S{+}B $ fit at $ m_{\mathrm{X}}= $ 146 GeV in solid red line, and the background component of the fit in dotted red line. The green and yellow bands represent the one and two standard deviations of the background component. The lower panel shows the residuals after subtracting the background component of the fit from data. |
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Additional Figure 10:
The $ m_{\mathrm{e}\mu} $ distribution of the observed data in the category VBF cat 1 is shown, with the $ S{+}B $ fit at $ m_{\mathrm{X}}= $ 146 GeV in solid red line, and the background component of the fit in dotted red line. The green and yellow bands represent the one and two standard deviations of the background component. The lower panel shows the residuals after subtracting the background component of the fit from data. |
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Additional Figure 11:
Best fit of $ {\sigma(\mathrm{p}\mathrm{p} \to \mathrm{X}(146) \to \mathrm{e} \mu)} $ for each analysis category (black point) compared to the best fit for the combination of all analysis categories (blue line). The one standard deviation uncertainty of the per-category best fit is shown in red line and the one standard deviation uncertainty of the combined best fit is shown in green band. |
| Additional Tables | |
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Additional Table 1:
The efficiency times acceptance of the signal rate for each analysis category and $ m_{\mathrm{X}} $ hypothesised. |
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Additional Table 2:
The observed and expected 95% CL upper limits on $ {\sigma_{{\mathrm{g}\mathrm{g}\mathrm{H}},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ and $ {\sigma_{\mathrm{VBF},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ with $ {f_{\mathrm{VBF}}=} $ 0.0. |
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Additional Table 3:
The observed and expected 95% CL upper limits on $ {\sigma_{{\mathrm{g}\mathrm{g}\mathrm{H}},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ and $ {\sigma_{\mathrm{VBF},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ with $ {f_{\mathrm{VBF}}=} $ 0.1. |
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Additional Table 4:
The observed and expected 95% CL upper limits on $ {\sigma_{{\mathrm{g}\mathrm{g}\mathrm{H}},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ and $ {\sigma_{\mathrm{VBF},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ with $ {f_{\mathrm{VBF}}=} $ 0.2. |
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Additional Table 5:
The observed and expected 95% CL upper limits on $ {\sigma_{{\mathrm{g}\mathrm{g}\mathrm{H}},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ and $ {\sigma_{\mathrm{VBF},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ with $ {f_{\mathrm{VBF}}=} $ 0.3. |
png pdf |
Additional Table 6:
The observed and expected 95% CL upper limits on $ {\sigma_{{\mathrm{g}\mathrm{g}\mathrm{H}},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ and $ {\sigma_{\mathrm{VBF},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ with $ {f_{\mathrm{VBF}}=} $ 0.4. |
png pdf |
Additional Table 7:
The observed and expected 95% CL upper limits on $ {\sigma_{{\mathrm{g}\mathrm{g}\mathrm{H}},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ and $ {\sigma_{\mathrm{VBF},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ with $ {f_{\mathrm{VBF}}=} $ 0.5. |
png pdf |
Additional Table 8:
The observed and expected 95% CL upper limits on $ {\sigma_{{\mathrm{g}\mathrm{g}\mathrm{H}},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ and $ {\sigma_{\mathrm{VBF},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ with $ {f_{\mathrm{VBF}}=} $ 0.6. |
png pdf |
Additional Table 9:
The observed and expected 95% CL upper limits on $ {\sigma_{{\mathrm{g}\mathrm{g}\mathrm{H}},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ and $ {\sigma_{\mathrm{VBF},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ with $ {f_{\mathrm{VBF}}=} $ 0.7. |
png pdf |
Additional Table 10:
The observed and expected 95% CL upper limits on $ {\sigma_{{\mathrm{g}\mathrm{g}\mathrm{H}},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ and $ {\sigma_{\mathrm{VBF},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ with $ {f_{\mathrm{VBF}}=} $ 0.8. |
png pdf |
Additional Table 11:
The observed and expected 95% CL upper limits on $ {\sigma_{{\mathrm{g}\mathrm{g}\mathrm{H}},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ and $ {\sigma_{\mathrm{VBF},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ with $ {f_{\mathrm{VBF}}=} $ 0.9. |
png pdf |
Additional Table 12:
The observed and expected 95% CL upper limits on $ {\sigma_{{\mathrm{g}\mathrm{g}\mathrm{H}},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ and $ {\sigma_{\mathrm{VBF},f_{\mathrm{VBF}}}({\mathrm{p}\mathrm{p} \to \mathrm{X} \to \mathrm{e} \mu})} $ with $ {f_{\mathrm{VBF}}=} $ 1.0. |
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