CMSPASHIG16040  
Measurements of properties of the Higgs boson in the diphoton decay channel with the full 2016 data set  
CMS Collaboration  
May 2017  
Abstract: Measurements of properties of the Higgs boson SM(125) in the $\mathrm{H}\rightarrow\gamma\gamma$ decay channel are reported. The analysis uses the data collected by the CMS experiment in protonproton collisions during the 2016 LHC running period. The data sample corresponds to an integrated luminosity of 35.9 fb$^{1}$. The measured signal strength relative to the standard model prediction is 1.16 $^{+0.15}_{0.14} $ =1.16 $^{+0.11}_{0.10}$ (stat.) $^{+0.09}_{0.08}$ (syst.) $^{+0.06}_{0.05}$ (theo.). Signal strengths associated with the different Higgs boson production mechanisms, coupling modifiers to bosons and fermions, and effective couplings to photons and gluons are also measured.  
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These preliminary results are superseded in this paper, JHEP 11 (2018) 185. The superseded preliminary plots can be found here. 
Figures & Tables  Summary  Additional Figures  References  CMS Publications 

Figures  
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Figure 1 :
Comparison of the dielectron invariant mass distributions in data and simulation (after energy smearing) for ${\mathrm{ Z } } \to {\mathrm{ e }^{+} \mathrm{ e }^{} } $ events where electrons are reconstructed as photons. The comparison is shown requiring $ {R_\mathrm {9}}> $ 0.94 for both photons and for (left) events with both showers in the barrel, and (right) the remaining events. The simulated distribution is normalized to the integral of the data distribution in the range 87 $ < m_{e^{+}e^{}} < $ 93 GeV. 
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Figure 1a:
Comparison of the dielectron invariant mass distributions in data and simulation (after energy smearing) for ${\mathrm{ Z } } \to {\mathrm{ e }^{+} \mathrm{ e }^{} } $ events where electrons are reconstructed as photons. The comparison is shown requiring $ {R_\mathrm {9}}> $ 0.94 for both photons and for events with both showers in the barrel. The simulated distribution is normalized to the integral of the data distribution in the range 87 $ < m_{e^{+}e^{}} < $ 93 GeV. 
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Figure 1b:
Comparison of the dielectron invariant mass distributions in data and simulation (after energy smearing) for ${\mathrm{ Z } } \to {\mathrm{ e }^{+} \mathrm{ e }^{} } $ events where electrons are reconstructed as photons. The comparison is shown requiring $ {R_\mathrm {9}}> $ 0.94 for both photons and for events with at least one shower in the endcap region. The simulated distribution is normalized to the integral of the data distribution in the range 87 $ < m_{e^{+}e^{}} < $ 93 GeV. 
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Figure 2:
(Left) Photon identification BDT score of the lowerscoring photon of diphoton pairs with an invariant mass in the range 100 $ < m_{\gamma \gamma } < $ 180 GeV, for events passing the preselection in the 13 TeV data set (points), and for simulated background events (blue histogram). Histograms are also shown for different components of the simulated background. The sum of all background distributions is scaled up to data. The red histogram corresponds to simulated Higgs boson signal events. (Right) Photon identification BDT score for ${\mathrm{ Z } } \to {\mathrm{ e }^{+} \mathrm{ e }^{} } $ events in data and simulation, where the electrons are reconstructed as photons. The systematic uncertainty applied to the shape from simulation (hashed region) is also shown. 
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Figure 2a:
Photon identification BDT score of the lowerscoring photon of diphoton pairs with an invariant mass in the range 100 $ < m_{\gamma \gamma } < $ 180 GeV, for events passing the preselection in the 13 TeV data set (points), and for simulated background events (blue histogram). Histograms are also shown for different components of the simulated background. The sum of all background distributions is scaled up to data. The red histogram corresponds to simulated Higgs boson signal events. 
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Figure 2b:
Photon identification BDT score for ${\mathrm{ Z } } \to {\mathrm{ e }^{+} \mathrm{ e }^{} } $ events in data and simulation, where the electrons are reconstructed as photons. The systematic uncertainty applied to the shape from simulation (hashed region) is also shown. 
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Figure 3:
Validation of the $ {\mathrm{ H } \to \gamma \gamma }$ vertex identification algorithm on $\mathrm{ Z } \to {\mu^{+} \mu^{} } $ events omitting the muon tracks. Simulated events are weighted to match the distributions of pileup and location of primary vertices in data. 
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Figure 4:
Comparison of the true vertex identification efficiency and the average estimated vertex probability as a function of the reconstructed diphoton ${p_{\mathrm {T}}}$ (left) and of the number of primary vertices (right) in simulated $ {\mathrm{ H } \to \gamma \gamma }$ events with $m_{\mathrm{ H } } = $ 125 GeV. Events are weighted according to the cross sections of the different production modes and to match the distributions of pileup and location of primary vertices in data. 
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Figure 4a:
Comparison of the true vertex identification efficiency and the average estimated vertex probability as a function of the reconstructed diphoton ${p_{\mathrm {T}}}$ in simulated $ {\mathrm{ H } \to \gamma \gamma }$ events with $m_{\mathrm{ H } } = $ 125 GeV. Events are weighted according to the cross sections of the different production modes and to match the distributions of pileup and location of primary vertices in data. 
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Figure 4b:
Comparison of the true vertex identification efficiency and the average estimated vertex probability as a function of the number of primary vertices in simulated $ {\mathrm{ H } \to \gamma \gamma }$ events with $m_{\mathrm{ H } } = $ 125 GeV. Events are weighted according to the cross sections of the different production modes and to match the distributions of pileup and location of primary vertices in data. 
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Figure 5:
(Left) Transformed score of the diphoton multivariate classifier for events with two photons satisfying the preselection requirements in data (points), simulated signal (red shades), and simulated background (coloured histograms). Both signal and background are stacked together. The vertical dashed lines show the boundaries of the untagged categories, the grey shade indicates events discarded from the analysis. (Right) Score of the diphoton multivariate classifier in $\mathrm{ Z } \to {\mathrm{ e }^{+} \mathrm{ e }^{} } $ events where the electrons are reconstructed as photons. The points show the score for data, the histogram shows the score for simulated DrellYan events. The pink band indicates the statistical and systematic uncertainties on the simulation. 
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Figure 5a:
Transformed score of the diphoton multivariate classifier for events with two photons satisfying the preselection requirements in data (points), simulated signal (red shades), and simulated background (coloured histograms). Both signal and background are stacked together. The vertical dashed lines show the boundaries of the untagged categories, the grey shade indicates events discarded from the analysis. 
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Figure 5b:
Score of the diphoton multivariate classifier in $\mathrm{ Z } \to {\mathrm{ e }^{+} \mathrm{ e }^{} } $ events where the electrons are reconstructed as photons. The points show the score for data, the histogram shows the score for simulated DrellYan events. The pink band indicates the statistical and systematic uncertainties on the simulation. 
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Figure 6:
Score of the jet multivariate discriminant used to enhance jet tagging in the ttHHadronic category. The points show the score for data in the signal region sidebands, $\text {m}_{\gamma \gamma } < $ 115 GeV or $\text {m}_{\gamma \gamma } > $ 135 GeV; the histogram shows the score for events in the data control sample; the filled histogram shows the score for simulated signal events. The distributions in the simulated and control samples are scaled as to match the integral of that from the data sidebands. 
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Figure 7:
Score of the combined VBF multivariate classifier in (left) ggH and VBF signal distributions, compared to background taken from data in the mass sideband region, and (right) $\mathrm{ Z } \to {\mathrm{ e }^{+} \mathrm{ e }^{} } $ + jets events. At left, the signal region selection is applied to the expected simulated ggH and VBF events; these are compared to points representing the background, as determined from data using the signal region selection in mass sidebands. At right, the signal selection is applied with electrons reconstructed as photons, with points showing the score for data and the histogram showing the score for simulated DrellYan events, including statistical and systematic uncertainties (pink band). Dotted lines indicate the three VBF categories, while the grey region is discarded from the analysis. 
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Figure 7a:
Score of the combined VBF multivariate classifier in ggH and VBF signal distributions, compared to background taken from data in the mass sideband region. The signal region selection is applied to the expected simulated ggH and VBF events; these are compared to points representing the background, as determined from data using the signal region selection in mass sidebands. Dotted lines indicate the three VBF categories, while the grey region is discarded from the analysis. 
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Figure 7b:
Score of the combined VBF multivariate classifier in $\mathrm{ Z } \to {\mathrm{ e }^{+} \mathrm{ e }^{} } $ + jets events. The signal selection is applied with electrons reconstructed as photons, with points showing the score for data and the histogram showing the score for simulated DrellYan events, including statistical and systematic uncertainties (pink band). Dotted lines indicate the three VBF categories, while the grey region is discarded from the analysis. 
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Figure 8:
Parametrized signal shape for the best resolution category (left) and for all categories combined together and weighted by the ratio $S/(S+B)$ (right) for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $\text {m}_{\mathrm{ H } } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Figure 8a:
Parametrized signal shape for the best resolution category for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $\text {m}_{\mathrm{ H } } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Figure 8b:
Parametrized signal shape for for all categories combined together and weighted by the ratio $S/(S+B)$ for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $\text {m}_{\mathrm{ H } } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Figure 9:
The efficiency$\times $acceptance of the signal model as a function of $\text {m}_{\mathrm{ H } } $ for all categories combined. The black line represents the yields from the signal model. The yellow band indicates the effect of the systematic uncertainties for trigger, photon identification and selection, photon energy scale and modelling of the photon energy resolution, vertex identification (see Section 9). 
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Figure 10:
Data points (black) and signal plus background model fits in the four untagged categories are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 10a:
Data points (black) and signal plus background model fits in the untagged 0 category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 10b:
Data points (black) and signal plus background model fits in the untagged 1 category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 10c:
Data points (black) and signal plus background model fits in the untagged 2 category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 10d:
Data points (black) and signal plus background model fits in the untagged 3 category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 11:
Data points (black) and signal plus background model fits in VBF and $\mathrm {t\bar{t}H}$ categories are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 11a:
Data points (black) and signal plus background model fits in the VBF 0 category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 11b:
Data points (black) and signal plus background model fits in the VBF 1 category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 11c:
Data points (black) and signal plus background model fits in the VBF 2 category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 11d:
Data points (black) and signal plus background model fits in the $\mathrm {t\bar{t}H}$ Leptonic category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 11e:
Data points (black) and signal plus background model fits in the $\mathrm {t\bar{t}H}$ Hadronic category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 12:
Data points (black) and signal plus background model fits in VH categories are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 12a:
Data points (black) and signal plus background model fits in ZH Leptonic category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 12b:
Data points (black) and signal plus background model fits in WH Leptonic category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 12c:
Data points (black) and signal plus background model fits in VH Leptonic Loose category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 12d:
Data points (black) and signal plus background model fits in VH Met category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 12e:
Data points (black) and signal plus background model fits in VH Hadronic category are shown. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 13:
Data points (black) and signal plus background model fits for all categories summed (left) and where the categories are summed weighted by their sensitivity (right). The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 13a:
Data points (black) and signal plus background model fits for all categories summed. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 13b:
Data points (black) and signal plus background model fits where the categories are summed weighted by their sensitivity. The one standard deviation (green) and two standard deviation bands (yellow) include the uncertainties in the background component of the fit. The bottom plot shows the residuals after background subtraction. 
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Figure 14:
Expected fraction of signal events per production mode in the different categories. For each category, the $\sigma _{eff}$ and $\sigma _{HM}$ of the signal model are given, as described in the text. The ratio of the number of signal events (S) to the number of signal plus background events (S+B) is shown on the right hand side. 
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Figure 15:
The likelihood scan for the signal strength where the value of the standard model Higgs boson mass is profiled in the fit. 
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Figure 16:
Signal strength modifiers measured for each process (black points) for profiled $m_{H}$, compared to the overall signal strength (green band) and to the SM expectation (dashed red line). 
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Figure 17:
Cross section ratios measured for each process (black points) in the Higgs Simplified Template Cross Section framework, for profiled $m_{H}$, compared to the SM expectation and its uncertainties (green band). The signal strength modifiers are constrained to be nonnegative, as indicated by the vertical line and hashed pattern at zero. 
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Figure 18:
The twodimensional bestfit (black cross) of the signal strengths for fermionic (ggH, $\mathrm {t\bar{t}H}$) and bosonic (VBF, ZH, WH) production modes compared to the SM expectations (red diamond). The Higgs boson mass is profiled in the fit. The solid (dashed) line represents the 1 (2) standard deviation confidence region. 
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Figure 19:
Twodimensional likelihood scans of $\kappa _{f}$ versus $\kappa _{V}$ (left) and $\kappa _{g}$ versus $\kappa _{\gamma }$ (right). All four variables are expressed relative to the SM expectations. The mass of the Higgs boson is profiled in the fits. The crosses indicate the bestfit values, the diamonds indicate the Standard Model expectations. The color maps indicate the value of the test statistic q as described in the text. 
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Figure 19a:
Twodimensional likelihood scans of $\kappa _{f}$ versus $\kappa _{V}$. All four variables are expressed relative to the SM expectations. The mass of the Higgs boson is profiled in the fits. The crosses indicate the bestfit values, the diamonds indicate the Standard Model expectations. The color maps indicate the value of the test statistic q as described in the text. 
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Figure 19b:
Twodimensional likelihood scans of $\kappa _{g}$ versus $\kappa _{\gamma }$. All four variables are expressed relative to the SM expectations. The mass of the Higgs boson is profiled in the fits. The crosses indicate the bestfit values, the diamonds indicate the Standard Model expectations. The color maps indicate the value of the test statistic q as described in the text. 
Tables  
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Table 1:
Schema of the photon preselection requirements. 
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Table 2:
Photon preselection efficiencies as measured in four photon categories, obtained with tag and probe techniques using $\mathrm{ Z } \to {\mathrm{ e }^{+} \mathrm{ e }^{} } $ and $\mathrm{ Z } \to {\mu^{+} \mu^{} } \gamma $. The quoted uncertainties include statistical and systematic terms. 
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Table 3:
The expected number of signal events per category and the percentage breakdown per production mode in that category. The $\sigma _{eff}$, computed as the smallest interval containing 68.3% of the invariant mass distribution, and $\sigma _{HM}$, computed as the width of the distribution at half of its highest point divided by 2.35 are also shown as an estimate of the $\text {m}_{\gamma \gamma } $ resolution in that category. The expected number of background events per GeV around 125 GeV is also listed. 
Summary 
We report the measurements of several of the properties of the standard model Higgs boson using its diphoton decay: the overall signal strength, the signal strength for each production mode separately, the rates for signal strengths $\mu_{\text{VBF, VH}}$ and $\mu_{\text{ggH, ttH}}$ for the model with these two parameters allowed to vary, cross section ratios for the Stage 0 STXS process definitions, and the bestfit coupling modifiers in the $\kappa_{f}$$\kappa_{V}$ and $\kappa_{\gamma}$$\kappa_{g}$ planes. The analysis uses 35.9 fb$^{1}$ of protonproton collision data collected at $ \sqrt{s} = $ 13 TeV by the CMS experiment at the LHC in 2016. The best fit signal strength obtained profiling $m_{\mathrm{H}}$ is reported to be $\hat{\mu} = $ 1.16 $^{+0.15}_{0.14} $ =1.16 $^{+0.11}_{0.10}$ (stat.) $^{+0.09}_{0.08}$ (syst.) $^{+0.06}_{0.05}$ (theo.). The bestfit values for the signal strength modifiers associated with the ggH and ttH production mechanisms, and with the VBF and VH production processes are measured; the best fit values for each modifier are $\mu_{\text{ggH, ttH}} = $ 1.19 $^{+0.20}_{0.18}$ and $\mu_{\text{VBF, VH}}= $ 1.01 $^{+0.57}_{0.51}$. When $\mu_{\text{ttH}}$ is considered separately, the bestfit value is $\mu_{\text{ttH}} = $ 2.2 $^{+0.9}_{0.8}$, corresponding to a 3.3$\sigma$ excess with respect to the absence of $\mu_{\text{ttH}}$ production, and compatible within 1.6$\sigma$ with the SM $\mu_{\text{ttH}}$ prediction. 
Additional Figures  
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Additional Figure 1:
Signal strength modifiers measured for each analysis category (black points) for profiled $m_\mathrm{ H } $, compared to the overall signal strength (green band) and to the SM expectation (dashed red line). The signal strength modifiers are constrained to be nonnegative, as indicated by the vertical line and hashed pattern at zero. 
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Additional Figure 2:
Parametrized signal shape for the untagged category with secondhighest signaltobackground for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Additional Figure 3:
Parametrized signal shape for the untagged category with thirdhighest signaltobackground for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Additional Figure 4:
Parametrized signal shape for the untagged category with lowest signaltobackground for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Additional Figure 5:
Parametrized signal shape for the VBF category with highest signaltobackground for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Additional Figure 6:
Parametrized signal shape for the VBF category with secondhighest signaltobackground for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Additional Figure 7:
Parametrized signal shape for the VBF category with lowest signaltobackground for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Additional Figure 8:
Parametrized signal shape for the hadronic $\mathrm {t\bar{t}}$H category for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Additional Figure 9:
Parametrized signal shape for the leptonic $\mathrm {t\bar{t}}$H category for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Additional Figure 10:
Parametrized signal shape for the leptonic WH category for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Additional Figure 11:
Parametrized signal shape for the leptonic ZH category for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Additional Figure 12:
Parametrized signal shape for the loose leptonic VH category for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Additional Figure 13:
Parametrized signal shape for the hadronic VH category for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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Additional Figure 14:
Parametrized signal shape for the VH missing transverse momentum (MET) category for a simulated $\mathrm{ H } \to \gamma \gamma $ signal sample with $m_\mathrm{ H } = $ 125 GeV. The black points represent weighted simulation events and the blue lines are the corresponding models. Also shown are the $\sigma _{\text {eff}}$ value (half the width of the narrowest interval containing 68.3% of the invariant mass distribution), FWHM and the corresponding interval. 
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