Ratio of the Z'NU to Z'SSM acceptance times efficiency (ACC*EFF) in the lep-had channel as a function of sin^2phi and the Z' mass.

Z' SSM acceptance (ACC) and product of acceptance and efficiency (ACC*EFF) for the had-had and lep-had selections as a function of the Z' mass.

Number of expected Z'SSM signal (NS), background (NB) and observed (N) events passing the total transverse mass ($m_{\rm T}^{\rm tot}$) threshold in the had-had and lep-had channels.

Median expected and observed 95% CL upper limits on the cross-section times branching fraction to tau+tau- for Z'SSM production for the exclusive had-had and lep-had channels, and for both channels combined.

Observed 95% CL upper limits on the cross-section times branching fraction to tau+tau- for Z'L and Z'R production for the combination of the had-had and lep-had channels.

Observed 95% CL lower limit on the Z'NU mass as a function of sin^2(phi).

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.

Definition of the fiducial phase space.

The seven input variables to the NN ordered by their discriminating power. The jet that is not $b$-tagged is referred to as $\textit{untagged}~$jet.

The seven input variables to the NN ordered by their discriminating power. The jet that is not $b$-tagged is referred to as $\textit{untagged}~$jet.

Event yields for the different processes estimated with the fit to the $O_\mathrm{NN}$ distribution compared to the numbers of observed events. Only the statistical uncertainties are quoted. The $Z,VV+\mathrm{jets}$ contributions and the multijet background are fixed in the fit; therefore no uncertainty is quoted for these processes.

Event yields for the different processes estimated with the fit to the $O_\mathrm{NN}$ distribution compared to the numbers of observed events. Only the statistical uncertainties are quoted. The $Z,VV+\mathrm{jets}$ contributions and the multijet background are fixed in the fit; therefore no uncertainty is quoted for these processes.

Detailed list of the contribution from each source of uncertainty to the total uncertainty in the measured values of $\sigma_{\mathrm{fid}}(tq)$ and $\sigma_{\mathrm{fid}}(\bar tq)$. The estimation of the systematic uncertainties has a statistical uncertainty of $0.3\%$. Uncertainties contributing less than $0.5\%$ are marked with ‘<0.5’.

Detailed list of the contribution from each source of uncertainty to the total uncertainty in the measured values of $\sigma_{\mathrm{fid}}(tq)$ and $\sigma_{\mathrm{fid}}(\bar tq)$. The estimation of the systematic uncertainties has a statistical uncertainty of $0.3\%$. Uncertainties contributing less than $0.5\%$ are marked with ‘<0.5’.

Significant contributions to the total relative uncertainty in the measured value of $R_{t}$. The estimation of the systematic uncertainties has a statistical uncertainty of $0.3~\%$. Uncertainties contributing less than $0.5~\%$ are not shown.

Significant contributions to the total relative uncertainty in the measured value of $R_{t}$. The estimation of the systematic uncertainties has a statistical uncertainty of $0.3~\%$. Uncertainties contributing less than $0.5~\%$ are not shown.

Slopes $a$ of the mass dependence of the measured cross$-$sections.

Slopes $a$ of the mass dependence of the measured cross$-$sections.

Predicted (post-fit) and observed event yields for the signal region (SR), after the requirement on the neural network discriminant, $O_{\mathrm{NN}}~>~0.8$. The multijet background prediction is obtained from the fit to the $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution described in Section 6, while all the other predictions and uncertainties are derived from the total cross$-$section measurement. In some cases there is no uncertainty quoted. In these cases the uncertainty is < 0.5.

Predicted (post-fit) and observed event yields for the signal region (SR), after the requirement on the neural network discriminant, $O_{\mathrm{NN}}~>~0.8$. The multijet background prediction is obtained from the fit to the $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution described in Section 6, while all the other predictions and uncertainties are derived from the total cross$-$section measurement. In some cases there is no uncertainty quoted. In these cases the uncertainty is < 0.5.

Predicted (post-fit) and observed event yields for the signal region (SR), after the requirement on the second neural network discriminant, $O_{\mathrm{NN2}}~>~0.8$. The multijet background prediction is obtained from the fit to the $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution described in Section 6, while all the other predictions and uncertainties are derived from the total cross$-$section measurement. In some cases there is no uncertainty quoted. In these cases the uncertainty is < 0.5.

Predicted (post-fit) and observed event yields for the signal region (SR), after the requirement on the second neural network discriminant, $O_{\mathrm{NN2}}~>~0.8$. The multijet background prediction is obtained from the fit to the $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution described in Section 6, while all the other predictions and uncertainties are derived from the total cross$-$section measurement. In some cases there is no uncertainty quoted. In these cases the uncertainty is < 0.5.

Migration matrix for $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at the particle level. The pseudo top quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.

Migration matrix for $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at the particle level. The pseudo top quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.

Migration matrix for $p_{\mathrm{T}}(t)$ at the parton level. The parton-level quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.

Migration matrix for $p_{\mathrm{T}}(t)$ at the parton level. The parton-level quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.

Migration matrix for $|y(\hat{t\hspace{-0.2mm}})|$ at the particle level. The pseudo top quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.

Migration matrix for $|y(\hat{t\hspace{-0.2mm}})|$ at the particle level. The pseudo top quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.

Migration matrix for $|y(t)|$ at the parton level. The parton-level quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.

Migration matrix for $|y(t)|$ at the parton level. The parton-level quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.

Uncertainties in the normalisations of the different backgrounds for all processes, as derived from the total cross-section measurement.

Uncertainties in the normalisations of the different backgrounds for all processes, as derived from the total cross-section measurement.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(t)$ at parton level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(t)$ at parton level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(t)$ at parton level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(t)$ at parton level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(t)|$ at parton level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(t)|$ at parton level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(t)|$ at parton level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(t)|$ at parton level.

Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ for $tq$ events(at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ for $ \bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ for $ \bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(t)$ for $tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(t)$ for $ \bar tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(t)$ for $tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(t)$ for $ \bar tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $|y(t)|$ for $tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $|y(t)|$ for $\bar tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $|y(t)|$ for $tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $|y(t)|$ for $\bar tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Fiducial acceptance $A_{\mathrm{fid}}$ for different $t$-channel single top-quark MC samples. $^{\mathrm{(a)}}$ Calculation taken from AcerMC $+$ $\mathrm{P{\scriptsize YTHIA}6}$. $^{\mathrm{(b)}}$ Calculation taken from $\mathrm{P{\scriptsize OWHEG}}$-$\mathrm{B{\scriptsize OX}}$ $+$ $\mathrm{P{\scriptsize YTHIA}6}$.

Fiducial acceptance $A_{\mathrm{fid}}$ for different $t$-channel single top-antiquark MC samples. $^{\mathrm{(a)}}$ Calculation taken from AcerMC $+$ $\mathrm{P{\scriptsize YTHIA}6}$. $^{\mathrm{(b)}}$ Calculation taken from $\mathrm{P{\scriptsize OWHEG}}$-$\mathrm{B{\scriptsize OX}}$ $+$ $\mathrm{P{\scriptsize YTHIA}6}$.

Uncertainties for the absolute differential $tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level per bin ([0,35,50,75,100,150,200,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level per bin ([0,35,50,75,100,150,200,300] GeV) in percent of $\left( \dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $\bar tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level per bin ([0,35,50,75,100,150,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})}$.

Uncertainties for the normalised differential $\bar tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level per bin ([0,35,50,75,100,150,300] GeV) in percent of $\left( \dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})}$.

Uncertainties for the absolute differential $tq$ cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level per bin ([0,0.15,0.3,0.45,0.7,1.0,1.3,2.2]) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(\hat{t\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $tq$ cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level per bin ([0,0.15,0.3,0.45,0.7,1.0,1.3,2.2]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(\hat{t\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $\bar tq$ cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level per bin ([0,0.15,0.3,0.45,0.7,1.0,1.3,2.2]) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(\hat{t\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $\bar tq$ cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level per bin ([0,0.15,0.3,0.45,0.7,1.0,1.3,2.2]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(\hat{t\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level per bin ([30,45,60,75,100,150,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level per bin ([30,45,60,75,100,150,300] GeV) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $\bar tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level per bin ([30,45,60,75,100,150,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $\bar tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level per bin ([30,45,60,75,100,150,300] GeV) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $tq$ cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level per bin ([0.0, 1.2, 1.7, 2.2, 2.7, 3.3, 4.5]) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(\hat{j\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $tq$ cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level per bin ([0.0, 1.2, 1.7, 2.2, 2.7, 3.3, 4.5]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(\hat{j\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $\bar tq$ cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level per bin ([0.0, 1.2, 1.7, 2.2, 2.7, 3.3, 4.5]) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(\hat{j\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $\bar tq$ cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level per bin ([0.0, 1.2, 1.7, 2.2, 2.7, 3.3, 4.5]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(\hat{j\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $tq$ cross-section as a function of $p_{\mathrm{T}}(t)$ at parton level per bin ([0,50,100,150,200,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(t)}$.

Uncertainties for the normalised differential $tq$ cross-section as a function of $p_{\mathrm{T}}(t)$ at parton level per bin ([0,50,100,150,200,300] GeV) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(t)}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $\bar tq $ cross-section as a function of $p_{\mathrm{T}}(t)$ at parton level per bin ([0,50,100,150,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(t)}$.

Uncertainties for the normalised differential $\bar tq $ cross-section as a function of $p_{\mathrm{T}}(t)$ at parton level per bin ([0,50,100,150,300] GeV) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(t)}$.

Uncertainties for the absolute differential $ tq $ cross-section as a function of $|y(t)|$ at parton level per bin ([0,0.3,0.7,1.3,2.2]) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(t)|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $ tq $ cross-section as a function of $|y(t)|$ at parton level per bin ([0,0.3,0.7,1.3,2.2]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(t)|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $ \bar tq $ cross-section as a function of $|y(t)|$ at parton level per bin ([0,0.3,0.7,1.3,2.2]) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(t)|}$.

Uncertainties for the normalised differential $ \bar tq $ cross-section as a function of $|y(t)|$ at parton level per bin ([0,0.3,0.7,1.3,2.2]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(t)|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Pre-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except for the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor which is not defined pre-fit. The last bin includes the overflow.

Pre-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except for the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor which is not defined pre-fit. The last bin includes the overflow.

Pre-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except for the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor which is not defined pre-fit. The last bin includes the overflow.

Comparison of predicted and observed event yields in each of the control and signal regions in the dilepton channel after the fit to the data. The uncertainty band includes all uncertainties and their correlations.

Comparison of predicted and observed event yields in each of the control and signal regions in the single-lepton channels after the fit to the data. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $120\le p_T^H<200$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $200\le p_T^H<300$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $p_{{T}}^{H}\ge 300$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $120\le p_T^H<200$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $200\le p_T^H<300$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $p_{{T}}^{H}\ge 450$ GeV (yield only). The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton boosted SRs after the inclusive fit to the data for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton boosted SRs after the inclusive fit to the data for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for ${\Delta R^{{avg}}_{bb}}$ after the inclusive fit to the data in the single-lepton $CR^{5j}_{{\geq}4b\ lo}$ control region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Comparison between data and prediction for ${\Delta R^{{avg}}_{bb}}$ after the inclusive fit to the data in the single-lepton $CR^{5j}_{{\geq}4b\ hi}$ control region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Post-fit yields of signal ($S$) and total background ($B$) as a function of $\log (S/B)$, compared with data. Final-discriminant bins in all dilepton and single-lepton analysis regions are combined into bins of $\log (S/B)$, with the signal normalised to the SM prediction used for the computation of $\log (S/B)$. The signal is then shown normalised to the best-fit value and the SM prediction. The lower frame reports the ratio of data to background, and this is compared with the expected ${t\bar {t}H}$-signal-plus-background yield divided by the background-only yield for the best-fit signal strength (solid red line) and the SM prediction (dashed orange line).

Comparison between data and prediction for the reconstruction BDT score for the Higgs boson candidate identified using Higgs boson information, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the average $\Delta \eta $ between $b$-tagged jets, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the likelihood discriminant, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the average $\Delta R$ for all possible combinations of $b$-tagged jet pairs, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the DNN $P(H)$ output for the Higgs boson candidate after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the DNN $P(H)$ output for the Higgs boson candidate after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Post-fit distribution of the reconstructed Higgs boson candidate mass for the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Post-fit distribution of the reconstructed Higgs boson candidate mass for the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Post-fit distribution of the reconstructed Higgs boson candidate mass for the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Fitted values of the ${t\bar {t}H}$ signal strength parameter in the individual channels and in the inclusive signal-strength measurement.

Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the fit. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.

Pre-fit distribution of the number of jets in the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the Standard Model expectation. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor that is not defined pre-fit.

Pre-fit distribution of the number of jets in the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the Standard Model expectation. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor that is not defined pre-fit.

Pre-fit distribution of the number of jets in the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the Standard Model expectation. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor that is not defined pre-fit.

Post-fit distribution of the number of jets in the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Post-fit distribution of the number of jets in the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Post-fit distribution of the number of jets in the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Post-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The last bin includes the overflow.

Post-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The last bin includes the overflow.

Post-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The last bin includes the overflow.

Signal-strength measurements in the individual STXS ${\hat{p}_{{T}}^{H}}$ bins, as well as the inclusive signal strength.

95% CL simplified template cross-section upper limits in the individual STXS ${\hat{p}_{{T}}^{H}}$ bins, as well as the inclusive limit. The observed limits are shown (solid black lines), together with the expected limits both in the background-only hypothesis (dotted black lines) and in the SM hypothesis (dotted red lines). In the case of the expected limits in the background-only hypothesis, one- and two-standard-deviation uncertainty bands are also shown. The hatched uncertainty bands correspond to the theory uncertainty in the fiducial cross-section prediction in each bin.

The ratios $S/B$ (black solid line, referring to the vertical axis on the left) and $S/\sqrt{B}$ (red dashed line, referring to the vertical axis on the right) for each category in the inclusive analysis in the dilepton channel (left) and in the single-lepton channels (right), where $S$ ($B$) is the number of selected signal (background) events predicted by the simulation and normalised to a luminosity of 139 fb$^{-1}$ .

Comparison between data and prediction for the $\Delta R$ between the Higgs candidate and the ${t\bar {t}}$ candidate system, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the number of $b$-tagged jet pairs with an invariant mass within 30 GeV of 125 GeV, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the reconstruction BDT score for the Higgs boson candidate identified using Higgs boson information, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the $\Delta R$ between the two highest ${p_{{T}}}$ $b$-tagged jets, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the sum of $b$-tagging discriminants of jets from Higgs, hadronic top and leptonic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Comparison between data and prediction for the sum of $b$-tagging discriminants of jets from Higgs, hadronic top and leptonic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Comparison between data and prediction for the hadronic top candidate invariant mass, after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Comparison between data and prediction for the hadronic top candidate invariant mass, after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Comparison between data and prediction for the fraction of the sum of $b$-tagging discriminants of all jets not associated to the Higgs or hadronic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Comparison between data and prediction for the fraction of the sum of $b$-tagging discriminants of all jets not associated to the Higgs or hadronic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $0\le {\hat{p}_{{T}}^{H}}<120$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.

Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $120\le {\hat{p}_{{T}}^{H}}<200$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.

Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $200\le {\hat{p}_{{T}}^{H}}<300$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.

Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $300\le {\hat{p}_{{T}}^{H}}<450$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.

Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for ${\hat{p}_{{T}}^{H}}\ge 450$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.

95% confidence level upper limits on signal-strength measurements in the individual STXS ${\hat{p}_{{T}}^{H}}$ bins, as well as the inclusive signal-strength limit, after the fit used to extract multiple signal-strength parameters. The observed limits are shown (solid black lines), together with the expected limits both in the background-only hypothesis (dotted black lines) and in the SM hypothesis (dotted red lines). In the case of the expected limits in the background-only hypothesis, one- and two-standard-deviation uncertainty bands are also shown.

Post-fit correlation matrix (in percentages) between the $\mu $ values obtained in the STXS bins.

Performance of the Higgs boson reconstruction algorithms. For each row of `truth' ${\hat{p}_{{T}}^{H}}$, the matrix shows (in percentages) the fraction of Higgs boson candidates which are truth-matched to ${b\bar {b}}$ decays, with reconstructed $p_T^H$ in the various bins of the dilepton (left), single lepton resolved (middle) and boosted (right) channels.

Pre-fit event yields in the dilepton signal regions and control regions. All uncertainties are included except the $k({t\bar {t}+{\geq }1b})$ uncertainty that is not defined pre-fit. For the ${t\bar {t}H}$ signal, the pre-fit yield values correspond to the theoretical prediction and corresponding uncertainties. `Other sources' refers to s-channel, t-channel, $tW$, $tWZ$, $tZq$, $Z+$ jets and diboson events.

Post-fit event yields in the dilepton signal regions and control regions, after the inclusive fit in all channels. All uncertainties are included, taking into account correlations. For the ${t\bar {t}H}$ signal, the post-fit yield and uncertainties correspond to those in the inclusive signal-strength measurement. `Other sources' refers to s-channel, t-channel, $tW$, $tWZ$, $tZq$, $Z+$ jets and diboson events.

Pre-fit event yields in the single-lepton resolved and boosted signal regions and control regions. All uncertainties are included except the $k({t\bar {t}+{\geq }1b})$ uncertainty that is not defined pre-fit. For the ${t\bar {t}H}$ signal, the pre-fit yield values correspond to the theoretical prediction and corresponding uncertainties. `Other top sources' refers to s-channel, t-channel, $tWZ$ and $tZq$ events.

Post-fit event yields in the single-lepton resolved and boosted signal regions and control regions, after the inclusive fit in all channels. All uncertainties are included, taking into account correlations. For the ${t\bar {t}H}$ signal, the post-fit yield and uncertainties correspond to those in the inclusive signal-strength measurement. `Other top sources' refers to s-channel, t-channel, $tWZ$ and $tZq$ events.

Breakdown of the contributions to the uncertainties in $\mu$. The contributions from the different sources of uncertainty are evaluated after the fit. The $\Delta \mu $ values are obtained by repeating the fit after having fixed a certain set of nuisance parameters corresponding to a group of systematic uncertainties, and then evaluating $(\Delta \mu)^2$ by subtracting the resulting squared uncertainty of $\mu $ from its squared uncertainty found in the full fit. The same procedure is followed when quoting the effect of the ${t\bar {t}+{\geq }1b}$ normalisation. The total uncertainty is different from the sum in quadrature of the different components due to correlations between nuisance parameters existing in the fit.

Fraction (in percentages) of signal events, after SR and CR selections, originating from $b\bar {b}$, $WW$ and other remaining Higgs boson decay modes in the dilepton channel.

Fraction (in percentages) of signal events, after SR and CR selections, originating from $b\bar {b}$, $WW$ and other remaining Higgs boson decay modes in the single-lepton channels.

Predicted SM ${t\bar {t}H}$ cross-section in each of the five STXS ${\hat{p}_{{T}}^{H}}$ bins and signal acceptance times efficiency (including all event selection criteria) in each STXS bin as well as for the inclusive ${\hat{p}_{{T}}^{H}}$ range.

Number of expected signal events before the fit, after each selection requirement applied to enter the dilepton channel $SR^{\geq 4j}_{\geq 4b}$ region. All ${t\bar {t}H}$ signal events are included, regardless of the $H$ or ${t\bar {t}H}$ decay mode. All object corrections are applied, except for the initial number of events which is calculated using the NLO QCD+EW theoretical prediction. All quoted numbers are rounded to unity. More details on the selection criteria can be found in the text.

Number of expected signal events before the fit, after each selection requirement applied to enter the single-lepton channel resolved $SR^{\geq 6j}_{\geq 4b}$ region. All ${t\bar {t}H}$ signal events are included, regardless of the $H$ or ${t\bar {t}H}$ decay mode. All object corrections are applied, except for the initial number of events which is calculated using the NLO QCD+EW theoretical prediction. All quoted numbers are rounded to unity. More details on the selection criteria can be found in the text.

Number of expected signal events before the fit, after each selection requirement applied to enter the single-lepton channel boosted $SR_{boosted}$ region. All ${t\bar {t}H}$ signal events are included, regardless of the $H$ or ${t\bar {t}H}$ decay mode. All object corrections are applied, except for the initial number of events which is calculated using the NLO QCD+EW theoretical prediction. All quoted numbers are rounded to unity. More details on the selection criteria can be found in the text.

Measured ratio of $\mathcal{B}_{4\mu}/\mathcal{B}_{2\mu}$

Measured branching fraction $\mathcal{B}_{4\mu}$

Measured branching fraction $\mathcal{B}_{4\mu}$

Distribution of $m^{vis}_{HH}$ after applying all the event selection that define the $HH$ SR, except the requirement on $m^{vis}_{HH}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. The $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$ signal is overlaid for two resonance mass hypotheses with a cross-section set to the expected limit, while all backgrounds are pre-fit. The first and the last bins contains the under-flow and over-flow bin entries, respectively. The hatched bands represent combined statistical and systematic uncertainties.

Event yields of the various estimated backgrounds and data, computed in the signal region of the search for $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. Statistical and systematic uncertainties are quoted. The background yields and uncertainties are pre-fit and are found to be similar to those post-fit.

Event yields of the various estimated backgrounds and data, computed in the signal region of the search for $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. Statistical and systematic uncertainties are quoted. The background yields and uncertainties are pre-fit and are found to be similar to those post-fit.

Expected and observed 95% CL upper limits on the production of a heavy, narrow-width, scalar resonance decaying to a pair of Higgs bosons ($X\rightarrow HH$). The final state used in the search consists of a boosted $b\bar{b}$ pair and a boosted hadronically decaying $\tau^{+}\tau^{-}$ pair, and the SM braching ratio of the Higgs boson are assumed. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit are indicated by the error bands. Two different requirements are applied on the visible mass of the two boosted Higgs boson candidates for the resonance mass hypotheses of 1.6 TeV and 2.5 TeV, leading to discontinuities in the limits (at 1.6 TeV, the difference between imposing no requirement and $m^{vis}_{HH}>900$ GeV is less than 1% though).

Expected and observed 95% CL upper limits on the production of a heavy, narrow-width, scalar resonance decaying to a pair of Higgs bosons ($X\rightarrow HH$). The final state used in the search consists of a boosted $b\bar{b}$ pair and a boosted hadronically decaying $\tau^{+}\tau^{-}$ pair, and the SM braching ratio of the Higgs boson are assumed. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit are indicated by the error bands. Two different requirements are applied on the visible mass of the two boosted Higgs boson candidates for the resonance mass hypotheses of 1.6 TeV and 2.5 TeV, leading to discontinuities in the limits (at 1.6 TeV, the difference between imposing no requirement and $m^{vis}_{HH}>900$ GeV is less than 1% though).

Selection acceptance times efficiency as a function of WPRIME mass at truth level for left- and right-handed WPRIME MC. The total efficiency curves correspond to the sum of the efficiencies of the one b-tag and two b-tag categories.

Cutflow (efficiency with respect to total number of events in %) for several WPRIME masses in the left-handed and in the right-handed model for hadronic top-quark decays.

Overview of the signal acceptance times efficiency (A x Eff) for the hadronic top-quark decay for both categories, the predicted cross section times branching ratio to TOP BOTTOM, as well as the observed 95% CL limit on the cross section times branching ratio for several WPRIME masses in the left-handed and in the right-handed model. The expected signal event yields in the two categories for 20.3 fb-1 of 8 TeV data are also shown.

Summary of the 95% C.L. upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$ for the dilepton channel in the resolved analysis. The observed limits are shown, together with the expected limits (dotted black lines). In the case of the expected limits, one- and two-standard-deviation uncertainty bands are also displayed. The data was published in JHEP 10 (2018) 031.

Efficiency and acceptance for simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ samples in two signal regions (SR) of the analysis, one with two $a\to b\bar{b}$ candidates in the High Purity Category (HPC), and the other with one $a\to b\bar{b}$ candidate in the High Purity Category (HPC) and one in the Low Purity Category (LPC).

Efficiency and acceptance for simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ samples in two signal regions (SR) of the analysis, one with two $a\to b\bar{b}$ candidates in the High Purity Category (HPC), and the other with one $a\to b\bar{b}$ candidate in the High Purity Category (HPC) and one in the Low Purity Category (LPC).

Event yields for a simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ sample with $m_a = 17.5\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. Cut 0 corresponds to the initial number of events. Cut 1 requires the single lepton trigger. Cut 2 requires 2 identified leptons. Cut 3 requires the Z-boson mass window. Cut 4 requires 2 reconstructed $a\to b\bar{b}$ candidates. Cut 5a requires 2 identified $a\to b\bar{b}$ candidates in the 1HPC1LPC region. Cut 6a requires the 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region to be inside the Higgs mass window. Cut 5b requires 2 identified $a\to b\bar{b}$ candidates in the 2HPC region. Cut 6b requires the 2 $a\to b\bar{b}$ candidates in the 2HPC region to be inside the Higgs mass window.

Event yields for a simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ sample with $m_a = 17.5\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. Cut 0 corresponds to the initial number of events. Cut 1 requires the single lepton trigger. Cut 2 requires 2 identified leptons. Cut 3 requires the Z-boson mass window. Cut 4 requires 2 reconstructed $a\to b\bar{b}$ candidates. Cut 5a requires 2 identified $a\to b\bar{b}$ candidates in the 1HPC1LPC region. Cut 6a requires the 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region to be inside the Higgs mass window. Cut 5b requires 2 identified $a\to b\bar{b}$ candidates in the 2HPC region. Cut 6b requires the 2 $a\to b\bar{b}$ candidates in the 2HPC region to be inside the Higgs mass window.

Background yield table for Z+jets, $t\bar{t}$, and rare sources. Observed data yield. Signal $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ yield with $m_a = 20\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$, with a branching ratio set to 1 for the $H \rightarrow aa$ decay, whereas the ATLAS figure attached to this entry instead uses the upper-limit branching ratio (smaller than 1). The table includes the yields in two signal regions with leptons consistent with an on-shell Z-boson decay, one with 2 $a\to b\bar{b}$ candidates in the 2HPC region and one with 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region. The table also includes the yields in four control regions, one with leptons consistent with an on-shell Z-boson decay and 2 $a\to b\bar{b}$ candidates in the Low Purity Category (LPC), and three others where the leptons are not consistent an on-shell Z-boson decay.

Background yield table for Z+jets, $t\bar{t}$, and rare sources. Observed data yield. Signal $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ yield with $m_a = 20\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. The table includes the yields in two signal regions with leptons consistent with an on-shell Z-boson decay, one with 2 $a\to b\bar{b}$ candidates in the 2HPC region and one with 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region. The table also includes the yields in four control regions, one with leptons consistent with an on-shell Z-boson decay and 2 $a\to b\bar{b}$ candidates in the Low Purity Category (LPC), and three others where the leptons are not consistent an on-shell Z-boson decay.

Upper limits at the 95% CL on the cross section for SSM $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.

Combined (electron and muon channels) upper limits at the 95% CL on the cross section for SSM $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.

Observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the electron+neutrino channel as a function of the $W^\prime$ pole mass.

Observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.

Combined (electron and muon channels) observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.

Observed upper limits at the 95% CL on the visible cross section in the electron+neutrino channel as a function of the transverse mass threshold.

Observed upper limits at the 95% CL on the visible cross section in the muon+neutrino channel as a function of the transverse mass threshold.

Product of acceptance and efficiency for the electron and muon selections as a function of the $W^\prime$ pole mass.

Expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the electron+neutrino channel as a function of the $W^\prime$ pole mass.

Expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.

Combined (electron and muon channels) expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.

(1) Number of generated MC events for the spin 1/2 top partner signal grid (2) Relative Cross section uncertainties for the spin 1/2 top partner signal grid.

(1) Acceptance of the same flavour selection for the spin 1/2 top partner signal grid (2) Selection efficiency of the same flavour selection for the spin 1/2 top partner signal grid (3) Product of the acceptance and efficiency of the same flavour selection for the spin 1/2 top partner signal grid (4) Relative experimental uncertainties on the acceptance times efficiency of the same flavour selection for the spin 1/2 top partner signal grid.

(1) Acceptance of the different flavour selection for the spin 1/2 top partner signal grid (2) Selection efficiency of the different flavour selection for the spin 1/2 top partner signal grid (3) Product of the acceptance and efficiency of the different flavour selection for the spin 1/2 top partner signal grid (4) Relative experimental uncertainties on the acceptance times efficiency of the different flavour selection for the spin 1/2 top partner signal grid.

(1) Observed CLs values for the scalar top signal grid (2) Expected CLs values for the scalar top signal grid.

(1) Observed CLs values for the spin 1/2 top partner signal grid (2) Expected CLs values for the spin 1/2 top partner signal grid.

Cross section limits [pb] for the scalar top signal grid.

Cross section limits [pb] for the spin 1/2 top partner signal grid.

Observed 95% CL limit for stop grid as a function of the scalar top and neutralino masses.

Observed 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying signal cross section of +1sigma.

Observed 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying signal cross section of -1sigma.

Expected 95% CL limit for stop grid as a function of the scalar top and neutralino masses.

Expected 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying the uncertainty of +1sigma.

Expected 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying the uncertainty of -1sigma.

Observed 95% CL limit for top partner grid as a function of the top partner and neutralino masses.

Observed 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying signal cross section of +1sigma.

Observed 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying signal cross section of -1sigma.

Expected 95% CL limit for top partner grid as a function of the top partner and neutralino masses.

Expected 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying the uncertainty of +1sigma.

Expected 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying the uncertainty of -1sigma.