Covariance matrix for the extrapolation uncertainty for the measurement of the absolute differential cross section as a function of the rho observable at parton level.

Normalized differential cross section as a function of the rho observable at parton level.

Covariance matrix for the total uncertainty (i.e. fit including stat., not extrapolation) for the measurement of the normalized differential cross section as a function of the rho observable at parton level.

Covariance matrix for the statistical uncertainty for the measurement of the normalized differential cross section as a function of the rho observable at parton level.

Covariance matrix for the extrapolation uncertainty for the measurement of the normalized differential cross section as a function of the rho observable at parton level.

Correlation matrix for all nuisance parameters and parameters of interest of the Likelihood fit.

This table is a numerical representation of Fig. 8 for all nuisance parameters.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{add.}}_{1})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}^{\mathrm{add.}}_{2})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{add.}}_{2})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}\mathrm{b}^{\mathrm{add.}})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $\Delta\mathrm{R}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $\mathrm{m}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $\Delta\mathrm{R}_{\mathrm{b}\mathrm{b}}^{\mathrm{avg}}$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}_{3})|$ in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}_{3})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}_{3})$ in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}_{3})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}_{4})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}_{4})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $H^{\mathrm{b}}_{\mathrm{T}}$ in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space.

Normalized differential cross section of $H^{\mathrm{b}}_{\mathrm{T}}$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\Delta\phi(\mathrm{lj}^{\mathrm{extra}}_{1},\mathrm{b}_{\mathrm{soft}})|$ in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space.

Normalized differential cross section of $|\Delta\phi(\mathrm{lj}^{\mathrm{extra}}_{1},\mathrm{b}_{\mathrm{soft}})|$ in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space.

Normalized differential cross section of $|\eta(\mathrm{b}^{\mathrm{extra}}_{1})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{extra}}_{1})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}^{\mathrm{extra}}_{2})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{extra}}_{2})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}\mathrm{b}^{\mathrm{extra}})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $\Delta\mathrm{R}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $\mathrm{m}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{lj}^{\mathrm{extra}}_{1})$ in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{lj}^{\mathrm{extra}}_{1})$ in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space.

Normalized differential cross section of $H^{\mathrm{j}}_{\mathrm{T}}$ in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space.

Normalized differential cross section of $H^{\mathrm{j}}_{\mathrm{T}}$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $\mathrm{m}_{\mathrm{b}\mathrm{b}}^{\mathrm{max}}$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $H^{\mathrm{light}}_{\mathrm{T}}$ in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space.

Normalized differential cross section of $H^{\mathrm{light}}_{\mathrm{T}}$ in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space.

Normalized differential cross section of $N_{\mathrm{jets}}$ in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space.

Normalized differential cross section of $N_{\mathrm{jets}}$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $N_{\mathrm{b}}$ in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space.

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}^{\mathrm{add.}}_{1})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{add.}}_{1})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}^{\mathrm{add.}}_{2})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{add.}}_{2})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}\mathrm{b}^{\mathrm{add.}})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $\Delta\mathrm{R}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $\mathrm{m}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $\Delta\mathrm{R}_{\mathrm{b}\mathrm{b}}^{\mathrm{avg}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}_{3})|$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}_{3})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}_{3})$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}_{3})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}_{4})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}_{4})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $H^{\mathrm{b}}_{\mathrm{T}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $H^{\mathrm{b}}_{\mathrm{T}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\Delta\phi(\mathrm{lj}^{\mathrm{extra}}_{1},\mathrm{b}_{\mathrm{soft}})|$ observable in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space

Correlation of parameters of interest in fit of $|\Delta\phi(\mathrm{lj}^{\mathrm{extra}}_{1},\mathrm{b}_{\mathrm{soft}})|$ observable in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}^{\mathrm{extra}}_{1})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{extra}}_{1})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}^{\mathrm{extra}}_{2})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{extra}}_{2})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}\mathrm{b}^{\mathrm{extra}})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $\Delta\mathrm{R}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $\mathrm{m}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{lj}^{\mathrm{extra}}_{1})$ observable in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{lj}^{\mathrm{extra}}_{1})$ observable in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space

Correlation of parameters of interest in fit of $H^{\mathrm{j}}_{\mathrm{T}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $H^{\mathrm{j}}_{\mathrm{T}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $\mathrm{m}_{\mathrm{b}\mathrm{b}}^{\mathrm{max}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $H^{\mathrm{light}}_{\mathrm{T}}$ observable in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space

Correlation of parameters of interest in fit of $H^{\mathrm{light}}_{\mathrm{T}}$ observable in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space

Correlation of parameters of interest in fit of $N_{\mathrm{jets}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $N_{\mathrm{jets}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $N_{\mathrm{b}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}^{\mathrm{add.}}_{1})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{add.}}_{1})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}^{\mathrm{add.}}_{2})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{add.}}_{2})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}\mathrm{b}^{\mathrm{add.}})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $\Delta\mathrm{R}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $\mathrm{m}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $\Delta\mathrm{R}_{\mathrm{b}\mathrm{b}}^{\mathrm{avg}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}_{3})|$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}_{3})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}_{3})$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}_{3})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}_{4})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}_{4})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $H^{\mathrm{b}}_{\mathrm{T}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $H^{\mathrm{b}}_{\mathrm{T}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\Delta\phi(\mathrm{lj}^{\mathrm{extra}}_{1},\mathrm{b}_{\mathrm{soft}})|$ observable in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space

Covariances of all nuisance parameters and POIs in fit of $|\Delta\phi(\mathrm{lj}^{\mathrm{extra}}_{1},\mathrm{b}_{\mathrm{soft}})|$ observable in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}^{\mathrm{extra}}_{1})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{extra}}_{1})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}^{\mathrm{extra}}_{2})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{extra}}_{2})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}\mathrm{b}^{\mathrm{extra}})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $\Delta\mathrm{R}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $\mathrm{m}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{lj}^{\mathrm{extra}}_{1})$ observable in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{lj}^{\mathrm{extra}}_{1})$ observable in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space

Covariances of all nuisance parameters and POIs in fit of $H^{\mathrm{j}}_{\mathrm{T}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $H^{\mathrm{j}}_{\mathrm{T}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $\mathrm{m}_{\mathrm{b}\mathrm{b}}^{\mathrm{max}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $H^{\mathrm{light}}_{\mathrm{T}}$ observable in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space

Covariances of all nuisance parameters and POIs in fit of $H^{\mathrm{light}}_{\mathrm{T}}$ observable in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space

Covariances of all nuisance parameters and POIs in fit of $N_{\mathrm{jets}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $N_{\mathrm{jets}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $N_{\mathrm{b}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Fiducial cross sections from the measurements of all observables, compared to predictions from different ttbb simulation approaches. For each of the normalized differential measurements the fiducial cross section in the respective phase space is also determined. In the paper only one representative observable is quoted for each fiducial phase space, while here the measured cross section with the uncertainties from the fit to the respective observable is summarized.

Comparison between data and background prediction before the fit (Pre-Fit) for the mass of the FCNC top-quark candidate in SR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The four FCNC LH signals are also shown separately, normalized to five times the cross-section corresponding to the most stringent observed branching ratio limits. The first (last) bin in all distributions includes the underflow (overflow). The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction before the fit (Pre-Fit) for the mass of the SM top-quark candidate in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The four FCNC LH signals are also shown separately, normalized to five times the cross-section corresponding to the most stringent observed branching ratio limits. The first (last) bin in all distributions includes the underflow (overflow). The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction before the fit (Pre-Fit) for the transverse momentum of the Z boson candidate in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The four FCNC LH signals are also shown separately, normalized to five times the cross-section corresponding to the most stringent observed branching ratio limits. The first (last) bin in all distributions includes the underflow (overflow). The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{1}$ discriminant in the mass sideband CR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{2}^{u}$ discriminant in the mass sideband CR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{1}$ discriminant in SR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{2}^{u}$ discriminant in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{1}$ discriminant in the mass sideband CR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{2}^{c}$ discriminant in the mass sideband CR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{1}$ discriminant in SR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{2}^{c}$ discriminant in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the leading lepton $p_{T}$ in the $t\bar{t}$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The last bin includes the overflow. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the third lepton $p_{T}$ in the $t\bar{t}$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The last bin includes the overflow. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the leading lepton $p_{T}$ in the $t\bar{t}Z$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The last bin includes the overflow. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{1}$ discriminant in the $t\bar{t}Z$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $t\bar{t}$ 3-jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $t\bar{t}$ 4-jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the signal region, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $W$+jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $t\bar{t}$ 3-jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $t\bar{t}$ 4-jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Expected distributions of the MEM discriminant $P(S|X)$ in the SR, for the s-channel single-top signal, and for the $t\bar{t}$ and $W$+jets backgrounds, for MEM discriminant values larger than $2.0\times10^{-4}$. Each distribution is normalised to unity. The binning is the same as the optimised binning used in the signal extraction fit, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the $W$+jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty band indicates the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the $t\bar{t}$ 3-jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty band indicates the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the $t\bar{t}$ 4-jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty bands indicate the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the SR before the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$. The lower panel of the figure shows the ratio of the data to the prediction, with different vertical axis ranges. The uncertainty band indicates the total uncertainties and their correlations in each bin. The uncertainties in the $t\bar{t}$ and $W$+jets normalisation factors, as well as in the s-channel signal cross-section, are not defined pre-fit and therefore not included. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the SR after the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$. The lower panel of the figure shows the ratio of the data to the prediction, with different vertical axis ranges. The uncertainty band indicates the total uncertainties and their correlations in each bin. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the SR after the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$, after subtraction of all backgrounds. The fitted distribution for the simulation of the signal is shown together with the post-fit uncertainty in the backgrounds. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.

Pre-fit and post-fit event yields in the SR, for MEM discriminant values larger than $2.0\times10^{-4}$. The central value of the event yield for each process is calculated by summing the values of the discriminant bin contents, using the nominal expected yield for the pre-fit value, and the best-fit estimate for the post-fit value. The error includes statistical and systematic uncertainties summed in quadrature. All sources of systematic uncertainties are included, taking into account correlations and anti-correlations in the post-fit case. The uncertainties in the $t\bar{t}$ and $W$+jets normalisation factors, as well as in the s-channel signal cross-section, are not defined pre-fit and therefore only included in the post-fit uncertainties.

Observed impact of the different sources of uncertainty on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. The 'Systematic uncertainties' category combines all sources of systematic uncertainties. The statistical uncertainty is obtained by repeating the fit after having fixed all nuisance parameters, including the $t\bar{t}$ and $W$+jets normalisation factors. 'Total' gives the total uncertainty on the measurement.

Observed impact of the different sources of $t\bar{t}$ modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, and 'ME/PS matching' to the matching of the ME to the parton shower.

Observed impact of the different sources of s-channel modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, as described in Section 7 in the paper.

Observed impact of the different sources of t-channel modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, as described in Section 7 in the paper.

Observed impact of the different sources of $tW$ modelling uncertainty on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, and '$t\bar{t}$ overlap' to the algorithm removing the overlap between $tW$ and $t\bar{t}$ production at NLO, as described in Section 7 in the paper.

Observed impact of the different sources of PDF uncertainties on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root.

Comparison between data and prediction after the fit to data in the signal region for the leading-jet $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the leading-jet $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the subleading-jet $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the subleading-jet $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the lepton $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the lepton $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the ${E}_{T}^{miss}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the $m_{T}^{W}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Nuisance parameters ranked according to their post-fit impacts on the best-fit value of the ratio $\mu$ of the measured cross-section to the predicted cross-section. In the figure, only the 20 nuisance parameters with the largest post-fit impacts are shown. The empty (solid) blue rectangles illustrate the pre-fit (post-fit) impact on $\mu$, corresponding to the upper axis. The pre-fit (post-fit) impact of each nuisance parameter, $\Delta\mu$, is calculated as the difference in the fitted value of $\mu$ between the nominal fit and the fit when fixing the corresponding nuisance parameter to $\hat{\theta}\pm\Delta\theta$ ($\hat{\theta}\pm\Delta\hat{\theta}$), where $\hat{\theta}$ is the best-fit value of the nuisance parameter and $\Delta\theta$ ($\Delta\hat{\theta}$) is its pre-fit (post-fit) uncertainty. Several systematic uncertainties are split into different nuisance parameters, which are indicated by NP. JES (JER) indicates jet energy scale (resolution), and $\gamma$ indicates a nuisance parameter associated to the MC statistics in one of the 18 bins numbered from 0 to 17. The black points show the best-fit values of the nuisance parameters, with the error bars representing the post-fit uncertainties. Each nuisance parameter is shown wrt. its nominal value, $\theta_0$, and in units of its pre-fit uncertainty, except the free-floating normalisation factors of the $t\bar{t}$ and $W$+jets backgrounds, and the parameters associated to the MC statistics in each bin, for which the post-fit values and uncertainties are shown.

Correlation matrix of the nuisance parameters and of the ratio $\mu$ of the measured cross-section to the predicted cross-section. The correlations are given after the fit to data. In the figure, only the parameters which have a correlation of at least 0.2 with any other parameter are shown.

Distribution of the MEM discriminant $P(S|X)$ in the SR for MEM discriminant values larger than $2.0\times10^{-4}$, for the collision data used for the measurement, and for 1000 pseudo-data replicas, generated using a bootstrapping technique, in order to assess the statistical correlations between this measurement and others, for the purpose of combinations. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the <a href="https://zenodo.org/record/5361038">BootstrapGenerator</a> software package , which implements a technique described in <a href="https://cds.cern.ch/record/2759945/">ATL-PHYS-PUB-2021-011</a>. The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. Each pseudo-data replica is assigned an index, ranging from 0 to 999, corresponding to the random number index used consistently for each observed data event.

Measured values of the signal cross-section and of the $t\bar{t}$ and $W$+jets normalisation factors, obtained by statistical-only fits to the collision data used for the measurement, and to 1000 pseudo-data replicas, generated using a bootstrapping technique, in order to assess the statistical correlations between this measurement and others, for the purpose of combinations. The central values and their statistical uncertainties are obtained by repeating the fit after having fixed all nuisance parameters, except the $t\bar{t}$ and $W$+jets normalisation factors, which are let free-floating (unlike for the statistical uncertainty on the cross-section quoted in the paper). The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the <a href="https://zenodo.org/record/5361038">BootstrapGenerator</a> software package , which implements a technique described in <a href="https://cds.cern.ch/record/2759945/">ATL-PHYS-PUB-2021-011</a>. The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. Each pseudo-data replica is assigned an index, ranging from 0 to 999, corresponding to the random number index used consistently for each observed data event.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and a $\tilde{\chi}_1^\pm$ that decays to $W^\pm\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction to $q_i\bar{q}_j W\pm\tilde{\chi}_1^0$.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to bottom quarks ($\tilde{g}\to b\bar{b}\tilde{\chi}_1^0$). Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to top quarks ($\tilde{g}\to t\bar{t}\tilde{\chi}_1^0$). Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for light-flavor squark pair production, where the squarks decay to $q\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay and 1-fold degeneracy in the light-flavor squarks (corresponding to the inner set of curves in the limit plot). To get the theory cross section for other N-fold degeneracy assumptions (e.g. 8-fold for the outer curves in the limit plot), just multiply by N.

Exclusion limits at 95% CL for bottom squark pair production, where the squarks decay to $b\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for top squark pair production, where the squarks decay to $t\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for top squark pair production, where the squarks decay to $b\tilde{\chi}_1^\pm$ and the $\tilde{\chi}_1^0$ decay to $W^\pm\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for top squark pair production, where the squarks decay either to $b\tilde{\chi}_1^\pm\to bW^\pm\tilde{\chi}_1^0$ or to $t\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for top squark pair production, where the squarks decay to $c\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for the mono-$\phi$ model, in which a resonantly-produced colored scalar decays to a massive Dirac fermion and a quark. Signal cross sections are calculated at leading order in $\alpha_S$, assuming unity branching fraction for the given decay.

Cross section limits for $\mathrm{LQ}\to\mathrm{q}\nu$, where $q=u,\,d,\,s,\,\mathrm{or}\,c$. Limits are at the 95% confidence level. Theory cross sections are LO for vector LQ, and NLO for scalar LQ. Branching ratio is assumed to be 100% to $\mathrm{q}\nu$.

Cross section limits for $\mathrm{LQ}\to\mathrm{b}\nu$. Limits are at the 95% confidence level. Theory cross sections are LO for vector LQ, and NLO for scalar LQ. Branching ratio is assumed to be 100% to $\mathrm{b}\nu$.

Cross section limits for $\mathrm{LQ}\to\mathrm{t}\nu$. Limits are at the 95% confidence level. Theory cross sections are LO for vector LQ, and NLO for scalar LQ. Branching ratios are assumed to be $\mathcal{B}(\mathrm{LQ}\to\mathrm{t}\nu)=1-\beta$, and $\mathcal{B}(\mathrm{LQ}\to\mathrm{b}\tau)=\beta$.

Predictions and observations for monojet signal regions

Predictions and observations for signal regions with $250 \leq H_\mathrm{T} < 450$ GeV

Predictions and observations for signal regions with $450 \leq H_\mathrm{T} < 575$ GeV and $N_\mathrm{j}<7$

Predictions and observations for signal regions with $450 \leq H_\mathrm{T} < 575$ GeV and $N_\mathrm{j}\geq7$

Predictions and observations for signal regions with $575 \leq H_\mathrm{T} < 1200$ GeV and $N_\mathrm{j}^\mathrm{hi}<4$

Predictions and observations for signal regions with $575 \leq H_\mathrm{T} < 1200$ GeV and $4\leq N_\mathrm{j}^\mathrm{hi}<7$

Predictions and observations for signal regions with $575 \leq H_\mathrm{T} < 1200$ GeV and $N_\mathrm{j}\geq7$

Predictions and observations for signal regions with $1200 \leq H_\mathrm{T} < 1500$ GeV and $N_\mathrm{j}^\mathrm{hi}<4$

Predictions and observations for signal regions with $1200 \leq H_\mathrm{T} < 1500$ GeV and $4\leq N_\mathrm{j}^\mathrm{hi}<7$

Predictions and observations for signal regions with $1200 \leq H_\mathrm{T} < 1500$ GeV and $N_\mathrm{j}\geq7$

Predictions and observations for signal regions with $H_\mathrm{T} \geq 1500$ GeV and $N_\mathrm{j}<7$

Predictions and observations for signal regions with $H_\mathrm{T} \geq 1500$ GeV and $N_\mathrm{j}\geq7$

Covariance matrix for the 282 signal regions of the inclusive $M_\mathrm{T2}$ search

Correlation matrix for the 282 signal regions of the inclusive $M_\mathrm{T2}$ search

Bin number definitions for the $M_\mathrm{T2}$ covariance and correlation matrices

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 10$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 50$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 200$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct light squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 10$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, for a single light squark.

Exclusion limits at 95% CL for direct light squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 50$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, for a single light squark.

Exclusion limits at 95% CL for direct light squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 200$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, for a single light squark.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino is long-lived with $c\tau_0 = 10$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino is long-lived with $c\tau_0 = 50$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino is long-lived with $c\tau_0 = 200$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

The maximum chargino mass excluded at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 1$ to 2000 cm while the gluino mass is fixed to 1900 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$. If all kinematically allowed chargino masses are excluded, the curves, including 68 and 95% expected, tend to overlap. At short decay lengths, horizontal exclusion lines are obtained from the inclusive analysis, as this is not affected by track reconstruction inefficiencies, which may arise when the chargino decays before the CMS tracker, and therefore shows better sensitivity to scenarios with very small lifetime compared to the disappearing track search, based on median expected limits.

The maximum chargino mass excluded at 95% CL for direct squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 1$ to 2000 cm while the squark mass is fixed to 900 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, for a single light squark. If all kinematically allowed chargino masses are excluded, the curves, including 68 and 95% expected, tend to overlap. At short decay lengths, horizontal exclusion lines are obtained from the inclusive analysis, as this is not affected by track reconstruction inefficiencies, which may arise when the chargino decays before the CMS tracker, and therefore shows better sensitivity to scenarios with very small lifetime compared to the disappearing track search, based on median expected limits.

The maximum chargino mass excluded at 95% CL for direct squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 1$ to 2000 cm while the squark mass is fixed to 1500 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, and the eight light squarks' masses are assumed to be degenerate. If all kinematically allowed chargino masses are excluded, the curves, including 68 and 95% expected, tend to overlap. At short decay lengths, horizontal exclusion lines are obtained from the inclusive analysis, as this is not affected by track reconstruction inefficiencies, which may arise when the chargino decays before the CMS tracker, and therefore shows better sensitivity to scenarios with very small lifetime compared to the disappearing track search, based on median expected limits.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 1$ to 2000 cm while the stop mass is fixed to 1000 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$. If all kinematically allowed chargino masses are excluded, the curves, including 68 and 95% expected, tend to overlap. At short decay lengths, horizontal exclusion lines are obtained from the inclusive analysis, as this is not affected by track reconstruction inefficiencies, which may arise when the chargino decays before the CMS tracker, and therefore shows better sensitivity to scenarios with very small lifetime compared to the disappearing track search, based on median expected limits.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 5$ to 1000 cm while the gluino mass is fixed to 1600 GeV and the neutralino's mass is fixed to 1575 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 5$ to 1000 cm while the squark mass is fixed to 2000 GeV and the neutralino's mass is fixed to 1000 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, and the eight light squarks' masses are assumed to be degenerate.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 5$ to 1000 cm while the stop mass is fixed to 1100 GeV and the neutralino's mass is fixed to 1000 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Predictions and observations for 2016 disappearing track signal regions

Predictions and observations for 2017-2018 pixel track signal regions

Predictions and observations for 2017-2018 medium (M) and long (L) length track signal regions

Covariance matrix for the 68 signal regions of the disappearing tracks $M_\mathrm{T2}$ search

Correlation matrix for the 68 signal regions of the disappearing tracks $M_\mathrm{T2}$ search

Covariance matrix of the Absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{t,h}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $p_T^{t,l}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{t,l}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $m^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $m^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $y^{t,h}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $y^{t,h}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $y^{t,l}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $y^{t,l}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $y^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $y^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $H_T^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $H_T^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $p_T^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $N^j$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $N^j$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $N^j$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $p_T^{j,1}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{j,1}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $m(j_1, t_h)$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $m(j_1, t_h)$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $m(j_1, t_h)$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $p_T^{j,2}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{j,2}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{j,2}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 1. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 2. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ $\geq$ 3. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 1. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 2. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ $\geq$ 3. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 1 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 2 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 2 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 2 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 2 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ $\geq$ 3 at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ at particle level in the boosted topology in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ at particle level in the boosted topology in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ at particle level in the boosted topology in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ at particle level in the boosted topology in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ at particle level in the boosted topology in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ at particle level in the boosted topology in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 1. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 2. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ at particle level in the boosted topology in $N^j$ $\geq$ 3. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 1. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 2. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ at particle level in the boosted topology in $N^j$ $\geq$ 3. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 1 and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 2 and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 2 and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 2 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 2 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ $\geq$ 3 at particle level in the boosted topology, accounting for the statistical uncertainties.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t,h}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t,l}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t,l}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m^{t\bar{t}}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,h}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,h}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,h}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,h}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,l}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,l}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,l}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,l}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,l}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t\bar{t}}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t\bar{t}}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $N^j$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $N^j$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $N^j$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $m(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $N^j$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $m(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $N^j$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $m(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $N^j$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $m(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ at particle level in the boosted topology.

Distribution of the NN output in the $\geq$1fj$\,$SR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.

Distribution of the NN output in the $t\bar{t}\gamma\,$CR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.

Total event yield in the $W\gamma\,$CR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.

Distribution of the scalar sum of the jet transverse momenta in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the $\eta$ of the $b$-tagged jet in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.

Distribution of the reconstructed top-quark mass in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the $p_{\mathrm{T}}$ of the top-quark+photon system in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the photon $p_{\mathrm{T}}$ in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the photon $\eta$ in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.

Distribution of the scalar sum of the jet transverse momenta in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the invariant mass of the $b$-tagged jet and the highest-$p_{\mathrm{T}}$ forward jet in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of $p_{\mathrm{T}}$ of the highest-$p_{\mathrm{T}}$ forward jet in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the difference in $\eta$ between the highest-$p_{\mathrm{T}}$ forward jet and the photon in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the energy of the system formed by the highest-$p_{\mathrm{T}}$ forward jet and the photon in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the $\eta$ of the $b$-tagged jet in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.

Distribution of the reconstructed top-quark mass in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the $p_{\mathrm{T}}$ of the top-quark and photon system in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the photon $p_{\mathrm{T}}$ in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the photon $\eta$ in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.

Ordered list of the 30 systematic uncertainties with the largest impact on the measured signal normalisation in the fit to data in the parton-level measurement considered as nuisance parameters (NPs) in the profile-likelihood fit. The column "NP value, error" corresponds to the nominal best-fit values and the corresponding uncertainties. The impact of each NP, $\Delta\sigma$/$\sigma_{\mathrm{pred}}$, is computed by comparing the nominal best-fit value of the POI ($\sigma$/$\sigma_{\mathrm{pred}}$) with the result of the fits when fixing the considered NP to its best-fit value shifted by its pre-fit and post-fit uncertainties. The corresponding impacts are listed in the "POI impact prefit high/low" and "POI impact high/low" columns, respectively. The "MC stat." NPs represent the MC statistical uncertainty and they enter the likelihood with a Poisson term, while all the other NPs enter the likelihood via a Gaussian term.

Ordered list of the 30 systematic uncertainties with the largest impact on the measured signal normalisation in the fit to data in the particle-level measurement considered as nuisance parameters (NPs) in the profile-likelihood fit. The column "NP value, error" corresponds to the nominal best-fit values and the corresponding uncertainties. The impact of each NP, $\Delta\sigma$/$\sigma_{\mathrm{pred}}$, is computed by comparing the nominal best-fit value of the POI ($\sigma$/$\sigma_{\mathrm{pred}}$) with the result of the fits when fixing the considered NP to its best-fit value shifted by its pre-fit and post-fit uncertainties. The corresponding impacts are listed in the "POI impact prefit high/low" and "POI impact high/low" columns, respectively. The "MC stat." NPs represent the MC statistical uncertainty and they enter the likelihood with a Poisson term, while all the other NPs enter the likelihood via a Gaussian term.

This table lists the kinematic requirements on parton-level objects used to define of the fiducial phase space for the parton-level measurement. Frixione isolation ($\href{https://arxiv.org/abs/hep-ph/9801442}{\text{hep-ph/9801442}}$) with a chosen radius of $\Delta R = 0.2$ is applied to photons ($\gamma$). The measured fiducial parton-level cross section is $\sigma_{tq\gamma}\times\mathcal{B}(t\rightarrow l\nu b) = 688\pm 23(\text{stat.})^{+75}_{-71}(\text{syst.})\,$fb.

This table lists the kinematic requirements on particle-level objects used to define of the fiducial phase space for the particle-level measurement. The particle level objects are photons ($\gamma$) not from a hadron decay, neutrinos not from a hadron decay ($\nu$), prompt electrons and muons ($\ell$) "dressed" by adding close-by ($\Delta R < 0.1$) photons, and anti-$k_t$ $R = 0.4$ jets built from stable particles ($\tau > 30\,$ps) and tau leptons excluding neutrinos and prompt dressed muons. Jets are $b$-tagged ($b$-jet) using ghost-matched $b$-hadrons with $p_{\text{T}} > 5\,$GeV. Apart from the kinematic requirements, isolation and overlap removal criteria are applied. Jets within $\Delta R = 0.4$ of a photon are removed if the $p_{\text{T}}$ of charged particles within $\Delta R = 0.3$ of the photon is smaller than $10\,\%$ of its $p_{\text{T}}$. Jets within $\Delta R = 0.4$ of a lepton are removed. Events are removed where a photon is close ($\Delta R < 0.4$) to a lepton or a surviving jet. The measured fiducial particle-level cross section is $\sigma_{tq\gamma}\times\mathcal{B}(t\rightarrow l\nu b)+\sigma_{t(\rightarrow l\nu b\gamma)q} = 303\pm 9(\text{stat.})^{+33}_{-32}(\text{syst.})\,$fb.

The covariance matrix containing the experimental uncertainties of the particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section as a function of the XCone-jet mass.

The covariance matrix containing the model uncertainties of the particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section as a function of the XCone-jet mass.

The normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section in the fiducial region as a function of the XCone-jet mass.

Correlations between bins in the normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section as a function of the XCone-jet mass.

The covariance matrix containing the statistical uncertainties of the normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section as a function of the XCone-jet mass.

The covariance matrix containing the experimental uncertainties of the normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section as a function of the XCone-jet mass.

The covariance matrix containing the model uncertainties of the normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section as a function of the XCone-jet mass.

Relative experimental uncertainties of the particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section in the fiducial region as a function of the XCone-jet mass.

Relative model uncertainties of the particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section in the fiducial region as a function of the XCone-jet mass.

Relative experimental uncertainties of the normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section in the fiducial region as a function of the XCone-jet mass.

Relative model uncertainties of the normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section in the fiducial region as a function of the XCone-jet mass.