Observed and expected 95% CL upper limits on the product of the production cross section ($\sigma$) and the branching fraction, obtained after combining all categories with 138 $\mathrm{fb}^{−1}$ of data at $\sqrt{s}$ = 13 TeV for $\mathrm{V'}$ to $VV$ + $VH$ signal in HVT model C.

Total signal efficiency including all event categories as a function of the resonance mass $M_X$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).

Total signal efficiency including all event categories as a function of the resonance mass $M_X$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).

Comparison between data and MC simulation for kinematic distributions based on events in the signal candidate sample for \Delta|y|. The vertical bars on the points show the statistical uncertainty in the data. The shaded bands represent the total uncertainty in the MC predictions. The lower panels give the ratio of the data to the sum of the MC

Comparison between data and MC simulation for \Delta|y| for each of the 12 analysis channels for the low mass region prior to maximum likelihood fit. The vertical bars on the points show the statistical uncertainty in the data. The shaded bands represent the total uncertainty in the MC predictions. The lower panels give the ratio of the data to the sum of the MC

Comparison between data and MC simulation for \Delta|y| for each of the 12 analysis channels for the low mass region after the maximum likelihood fit. The vertical bars on the points show the statistical uncertainty in the data. The shaded bands represent the total uncertainty in the MC predictions. The lower panels give the ratio of the data to the sum of the MC

Comparison between data and MC simulation for \Delta|y| for each of the 12 analysis channels for the high mass region prior to the maximum likelihood fit. The vertical bars on the points show the statistical uncertainty in the data. The shaded bands represent the total uncertainty in the MC predictions. The lower panels give the ratio of the data to the sum of the MC

Comparison between data and MC simulation for \Delta|y| for each of the 12 analysis channels for the high mass region after the maximum likelihood fit. The vertical bars on the points show the statistical uncertainty in the data. The shaded bands represent the total uncertainty in the MC predictions. The lower panels give the ratio of the data to the sum of the MC

Negative log-likelihood difference in $\text{c}_{\varphi\text{Q}}^{3}$ where the other Wilson coefficients are fixed to 0.

Negative log-likelihood difference in $\text{c}_{\varphi\text{t}}$ where the other Wilson coefficients are fixed to 0.

Negative log-likelihood difference in $\text{c}_{\varphi\text{tb}}$ where the other Wilson coefficients are fixed to 0.

Negative log-likelihood difference in $\text{c}_{\text{tW}}$ where the other Wilson coefficients are fixed to 0.

Negative log-likelihood difference in $\text{c}_{\text{bW}}$ where the other Wilson coefficients are fixed to 0.

Negative log-likelihood difference in $\text{c}_{\text{tZ}}$ where the other Wilson coefficients are fixed to 0.

Negative log-likelihood difference in $\text{c}_{\text{t}\varphi}$ where the other Wilson coefficients are simultaneously fit.

Negative log-likelihood difference in $\text{c}_{\varphi\text{Q}}^{-}$ where the other Wilson coefficients are simultaneously fit.

Negative log-likelihood difference in $\text{c}_{\varphi\text{Q}}^{3}$ where the other Wilson coefficients are simultaneously fit.

Negative log-likelihood difference in $\text{c}_{\varphi\text{t}}$ where the other Wilson coefficients are simultaneously fit.

Negative log-likelihood difference in $\text{c}_{\varphi\text{tb}}$ where the other Wilson coefficients are simultaneously fit.

Negative log-likelihood difference in $\text{c}_{\text{tW}}$ where the other Wilson coefficients are simultaneously fit.

Negative log-likelihood difference in $\text{c}_{\text{bW}}$ where the other Wilson coefficients are simultaneously fit.

Negative log-likelihood difference in $\text{c}_{\text{tZ}}$ where the other Wilson coefficients are simultaneously fit.

Negative log-likelihood difference in $\text{c}_{\varphi\text{t}}, \text{c}_{\varphi\text{Q}}^{-}$ where the other Wilson coefficients are fixed to 0.

Negative log-likelihood difference in $\text{c}_{\varphi\text{Q}}^{3}, \text{c}_{\varphi\text{Q}}^{-}$ where the other Wilson coefficients are fixed to 0.

Negative log-likelihood difference in $\text{c}_{\text{tW}}, \text{c}_{\text{tZ}}$ where the other Wilson coefficients are fixed to 0.

Comparison of the $m_{miss}$ shapes for the simulated signal events within the fiducial region and those outside it, after including the effect of PU protons as describe in the text, for a generated $m_{X}$ mass of 1000 GeV. The distributions are shown for single(+z)-single(−z) proton reconstruction categories.

Product of the acceptance times the combined reconstruction and identification efficiency, as a function of $m_{X}$ , for events generated inside the fiducial volume defined in Table 1. The curves shown panel display the different final states. The definition of the fiducial region and signal model used to estimate the acceptance is provided in the text.

Product of the acceptance times the combined reconstruction and identification efficiency, as a function of $m_{X}$ , for different proton reconstruction categories in the $Z \rightarrow \mu\mu $ analysis, and for events generated inside the fiducial volume defined in Table 1. The curves shown panel display the different final states. The definition of the fiducial region and signal model used to estimate the acceptance is provided in the text.

Distributions of the reconstructed proton $\xi$ in the negative arm from the proton mixing procedure with simulated MC events, are compared to data. The ee final states are shown.The ee events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the positive arm from the proton mixing procedure with simulated MC events, are compared to data. The ee final states are shown.The ee events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed di-proton rapidity from the proton mixing procedure with simulated MC events, are compared to data. The ee final states are shown.The ee events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the negative arm from the proton mixing procedure with simulated MC events, are compared to data. The $\mu\mu$ final states are shown.The $\mu\mu$ events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the positive arm from the proton mixing procedure with simulated MC events, are compared to data. The $\mu\mu$ final states are shown.The $\mu\mu$ events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed di-proton rapidity from the proton mixing procedure with simulated MC events, are compared to data. The $\mu\mu$ final states are shown.The $\mu\mu$ events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the negative arm from the proton mixing procedure with simulated MC events, are compared to data. The $\gamma$ final states are shown.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the positive arm from the proton mixing procedure with simulated MC events, are compared to data. The $\gamma$ final states are shown.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed di-proton rapidity from the proton mixing procedure with simulated MC events, are compared to data. The $\gamma$ final states are shown.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The proton $\xi$ distribution for the positive CT-PPS arm is shown.

Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The proton $\xi$ distribution for the negative CT-PPS arm is shown.

Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The di-proton invariant mass is shown.

Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The $m_{miss}$ is shown.

$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the multi(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the multi(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the single(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the single(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the multi(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the multi(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the single(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the single(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the multi(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.

$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the multi(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.

$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the single(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.

$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the single(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.

Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $Z\rightarrow ee$ analysis.

Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $Z\rightarrow \mu\mu$ analysis.

Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $Z$ analysis.

Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $\gamma$ analysis.

The profile likelihood scan as a function of Bs to mu+mu- and B0 to mu+mu- decay branching fractions in 2D.

Jet shape ratios ($\rho(\Delta r)_{\mathrm{PbPb}}/\rho(\Delta r)_{\mathrm{pp}}$) for inclusive and b jets as function of $\Delta r$ at $\sqrt{s_{NN}} = 5.02$ TeV.

Jet shape ratios ($\rho(\Delta r)_{\mathrm{PbPb}}/\rho(\Delta r)_{\mathrm{pp}}$) for inclusive and b jets as function of $\Delta r$ at $\sqrt{s_{NN}} = 5.02$ TeV.

Jet shape ratios ($\rho(\Delta r)_{\mathrm{PbPb}}/\rho(\Delta r)_{\mathrm{pp}}$) for inclusive and b jets as function of $\Delta r$ at $\sqrt{s_{NN}} = 5.02$ TeV.

Transverse momentum profile difference $P(\Delta r)_{\mathrm{PbPb}}-P(\Delta r)_{\mathrm{pp}}$ vs. $\Delta r$ for inclusive and b jets at $\sqrt{s_{NN}} = 5.02$ TeV.

Transverse momentum profile difference $P(\Delta r)_{\mathrm{PbPb}}-P(\Delta r)_{\mathrm{pp}}$ vs. $\Delta r$ for inclusive and b jets at $\sqrt{s_{NN}} = 5.02$ TeV.

Transverse momentum profile difference $P(\Delta r)_{\mathrm{PbPb}}-P(\Delta r)_{\mathrm{pp}}$ vs. $\Delta r$ for inclusive and b jets at $\sqrt{s_{NN}} = 5.02$ TeV.

Jet shape ratios ($\rho(\Delta r)_{\mathrm{b}}/\rho(\Delta r)_{\mathrm{incl.}}$) as function of $\Delta r$ from pp and PbPb collisions at $\sqrt{s_{NN}}= 5.02$ TeV.

Jet shape ratios ($\rho(\Delta r)_{\mathrm{b}}/\rho(\Delta r)_{\mathrm{incl.}}$) as function of $\Delta r$ from pp and PbPb collisions at $\sqrt{s_{NN}} = 5.02$ TeV.

Jet shape ratios ($\rho(\Delta r)_{\mathrm{b}}/\rho(\Delta r)_{\mathrm{incl.}}$) as function of $\Delta r$ from pp and PbPb collisions at $\sqrt{s_{NN}} = 5.02$ TeV.

Number of data events and the number of background events in the best-fit signal-plus-background model for the ggH Tag 2 category, in bins of $m_{ee}$. The number of signal events in the SM and at the observed limit are also provided in the same bins.

Number of data events and the number of background events in the best-fit signal-plus-background model for the ggH Tag 3 category, in bins of $m_{ee}$. The number of signal events in the SM and at the observed limit are also provided in the same bins.

Number of data events and the number of background events in the best-fit signal-plus-background model for the VBF Tag 0 category, in bins of $m_{ee}$. The number of signal events in the SM and at the observed limit are also provided in the same bins.

Number of data events and the number of background events in the best-fit signal-plus-background model for the VBF Tag 1 category, in bins of $m_{ee}$. The number of signal events in the SM and at the observed limit are also provided in the same bins.

Expected and observed limits at the 95%% C.L. on the branching fraction to an electron pair ($e^{+}e^{-}$) for a Higgs boson mass between 120 and 130 GeV.

Expected and observed limits at the 95%% C.L. on the branching fraction to an electron pair ($e^{+}e^{-}$) for each analysis category, and all categories combined. The results here are computed for $m_{H}=125.38$ GeV.