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

Observed and expected distributions of the $WZ$ invariant mass in the q$\bar{\mathrm q}$ category after applying all selection cuts. Background contributions are obtained from background-only likelihood fit to the data.

Observed and expected distributions of the $WZ$ invariant mass in the $VBF$ category after applying all selection cuts. Background contributions are obtained from background-only likelihood fit to the data.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($W'\to W^\pm Z$) for the q$\bar{\mathrm q}$ production of a $W'$ boson in the HVT model as a function of its mass. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty in the expected limits are given. Limits are calculated in the asymptotic approximation below 900 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($W'\to W^\pm Z$) for the $VBF$ production of a $W'$ boson in the HVT model as a function of its mass. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty are given in the expected limits. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($H_5^\pm\to W^\pm Z$) of the Georgi-Machacek Model as a function of $m_{H_5^\pm}$. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty in the expected limits are given. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on the parameter $\sin(\theta_H)$ of the Georgi-Machacek Model as a function of $m_{H_5^\pm}$. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty are given in the expected limits. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Absolute differential cross-section as a function of $\Delta R^{extra1}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta R^{extra1}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $|y^{t,1}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $|y^{t,1}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $|y^{t,1}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|y^{t,1}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $|y^{t,2}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $|y^{t,2}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $|y^{t,2}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|y^{t,2}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $|y^{t\bar{t}}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $|y^{t\bar{t}}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $|y^{t\bar{t}}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $p_{T}^{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $p_{T}^{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $p_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $p_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $N_{jets}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $N_{jets}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $N_{jets}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $N_{jets}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $\Delta\phi^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $\Delta\phi^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $\Delta\phi^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta\phi^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $|P_{out}^{t,1}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $|P_{out}^{t,1}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $|P_{out}^{t,1}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{out}^{t,1}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $|P_{cross}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $|P_{cross}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $|P_{cross}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{cross}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $Z^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $Z^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $Z^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $Z^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $H_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $H_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $H_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $|y_{boost}^{t\bar{t}}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $|y_{boost}^{t\bar{t}}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $|y_{boost}^{t\bar{t}}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|y_{boost}^{t\bar{t}}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $\chi^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $\chi^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $\chi^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\chi^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R_{Wt}^{leading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R_{Wt}^{leading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R_{Wt}^{leading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R_{Wt}^{leading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R_{Wt}^{subleading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R_{Wt}^{subleading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R_{Wt}^{subleading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R_{Wt}^{subleading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R_{Wb}^{leading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R_{Wb}^{leading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R_{Wb}^{leading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R_{Wb}^{leading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R_{Wb}^{subleading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R_{Wb}^{subleading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R_{Wb}^{subleading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R_{Wb}^{subleading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $\Delta R^{extra1}_{t,close}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $\Delta R^{extra1}_{t,close}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $\Delta R^{extra1}_{t,close}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta R^{extra1}_{t,close}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $\Delta R^{extra2}_{t,close}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $\Delta R^{extra2}_{t,close}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $\Delta R^{extra2}_{t,close}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta R^{extra2}_{t,close}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $\Delta R^{extra3}_{t,close}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $\Delta R^{extra3}_{t,close}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $\Delta R^{extra3}_{t,close}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta R^{extra3}_{t,close}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R^{pT, extra1}_{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R^{pT, extra1}_{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R^{pT, extra1}_{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R^{pT, extra1}_{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R^{pT, extra2}_{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R^{pT, extra2}_{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R^{pT, extra2}_{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R^{pT, extra2}_{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R^{pT, extra3}_{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R^{pT, extra3}_{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R^{pT, extra3}_{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R^{pT, extra3}_{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R^{pT, t\bar{t}}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R^{pT, t\bar{t}}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R^{pT, t\bar{t}}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R^{pT, t\bar{t}}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R^{pT, extra1}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R^{pT, extra1}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R^{pT, extra1}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R^{pT, extra1}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R^{pT, extra2}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R^{pT, extra2}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R^{pT, extra2}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R^{pT, extra2}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R^{pT, extra3}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R^{pT, extra3}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R^{pT, extra3}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R^{pT, extra3}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $\Delta R^{extra2}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $\Delta R^{extra2}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $\Delta R^{extra2}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta R^{extra2}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $\Delta R^{extra3}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $\Delta R^{extra3}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $\Delta R^{extra3}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta R^{extra3}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R^{pT, extra2}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R^{pT, extra2}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R^{pT, extra2}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R^{pT, extra2}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $R^{pT, extra3}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $R^{pT, extra3}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $R^{pT, extra3}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $R^{pT, extra3}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Total cross-section at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute double-differential cross-section as a function of $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative double-differential cross-section as a function of $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute double-differential cross-section as a function of $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative double-differential cross-section as a function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute double-differential cross-section as a function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative double-differential cross-section as a function of $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute double-differential cross-section as a function of $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative double-differential cross-section as a function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute double-differential cross-section as a function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative double-differential cross-section as a function of $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute double-differential cross-section as a function of $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative double-differential cross-section as a function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute double-differential cross-section as a function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute double-differential cross-section as a function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix of the relative differential cross-section as function of $\chi^{t\bar{t}}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $|y^{t\bar{t}}|$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative double-differential cross-section as a function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.5 < $|y^{t,1}|$ < 2.5 and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.0 < $|y^{t,1}|$ < 0.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.5 < $|y^{t,1}|$ < 2.5 and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.0 < $|y^{t,1}|$ < 0.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute double-differential cross-section as a function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute double-differential cross-section as a function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Post-fit $m_{T}$ distribution in the SR 2J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{T}$ distribution in the SR 4J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{T}$ distribution in the SR 4J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{T}$ distribution in the SR 4J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{T}$ distribution in the SR 4J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{T}$ distribution in the SR 6J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{T}$ distribution in the SR 6J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{T}$ distribution in the SR 6J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{T}$ distribution in the SR 6J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Pre-fit $m_{eff}$ distribution in the TR6J control region. Uncertainties include statistical and systematic uncertainties (added in quadrature). The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 2J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Pre-fit $m_{eff}$ distribution in the WR6J control region. Uncertainties include statistical and systematic uncertainties (added in quadrature). The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 2J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the TR6J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J low-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the WR6J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J low-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 2J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J high-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 2J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J high-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J low-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 6J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J low-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 6J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J high-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.

Post-fit $m_{eff}$ distribution in the 4J high-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model. space.

Post-fit $m_{eff}$ distribution in the 6J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Observed 95% CL exclusion contours for the gluino one-step variable-x

Post-fit $m_{eff}$ distribution in the 6J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Expected 95% CL exclusion contours for the gluino one-step variable-x

Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.

Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.

Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model. space.

Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.

Observed 95% CL exclusion contours for the gluino one-step variable-x

Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.

Expected 95% CL exclusion contours for the gluino one-step variable-x

Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.

Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.

Expected 95% CL exclusion contours for the squark one-step variable-x

Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.

Expected 95% CL exclusion contours for the squark one-step variable-x

Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.

Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x

Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.

Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x

Expected 95% CL exclusion contours for the squark one-step variable-x

Upper limits on the signal cross section for simplified model gluino one-step x = 1/2

Expected 95% CL exclusion contours for the squark one-step variable-x

Upper limits on the signal cross section for simplified model gluino one-step variable-x

Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x

Upper limits on the signal cross section for simplified model squark one-step x = 1/2

Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x

Upper limits on the signal cross section for simplified model squark one-step variable-x

Upper limits on the signal cross section for simplified model gluino one-step x = 1/2

Upper limits on the signal cross section for simplified model squark one-step x=1/2 in one-flavour schemes

Upper limits on the signal cross section for simplified model gluino one-step variable-x

Upper limits on the signal cross section for simplified model squark one-step variable-x in one-flavour schemes

Upper limits on the signal cross section for simplified model squark one-step x = 1/2

Post-fit $m_{eff}$ distribution in the 2J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Upper limits on the signal cross section for simplified model squark one-step variable-x

Post-fit $m_{eff}$ distribution in the 2J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Upper limits on the signal cross section for simplified model squark one-step x=1/2 in one-flavour schemes

Post-fit $m_{eff}$ distribution in the 4J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Upper limits on the signal cross section for simplified model squark one-step variable-x in one-flavour schemes

Post-fit $m_{eff}$ distribution in the 4J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the TR2J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 6J b-tag validation region. Uncertainties include statistical and systematic uncertainties.

Post-fit $m_{eff}$ distribution in the WR2J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 6J b-veto validation region. Uncertainties include statistical and systematic uncertainties.

Post-fit $m_{eff}$ distribution in the TR4J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Event selection cutflow for two representative signal samples for the SR2JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Post-fit $m_{eff}$ distribution in the WR4J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Event selection cutflow for two representative signal samples for the SR2JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Post-fit $m_{eff}$ distribution in the 2J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Event selection cutflow for two representative signal samples for the SR4JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Post-fit $m_{eff}$ distribution in the 2J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Event selection cutflow for two representative signal samples for the SR4JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Post-fit $m_{eff}$ distribution in the 4J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Event selection cutflow for two representative signal samples for the SR6JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Post-fit $m_{eff}$ distribution in the 4J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Event selection cutflow for two representative signal samples for the SR6JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Post-fit $m_{eff}$ distribution in the 6J b-tag validation region. Uncertainties include statistical and systematic uncertainties.

Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models

Post-fit $m_{eff}$ distribution in the 6J b-veto validation region. Uncertainties include statistical and systematic uncertainties.

Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models

Event selection cutflow for two representative signal samples for the SR2JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models

Event selection cutflow for two representative signal samples for the SR2JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models

Event selection cutflow for two representative signal samples for the SR4JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models

Event selection cutflow for two representative signal samples for the SR4JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models

Event selection cutflow for two representative signal samples for the SR6JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Signal acceptance in SR2J discovery high region for gluino production one-step x = 1/2 simplified models

Event selection cutflow for two representative signal samples for the SR6JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Signal acceptance in SR2J discovery low region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J discovery high region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J discovery low region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J discovery high region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J discovery low region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J discovery high region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J discovery high region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J discovery low region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J discovery low region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx discovery region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J discovery high region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J discovery low region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx discovery region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx discovery region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx discovery region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J discovery high region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J discovery low region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J discovery high region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J discovery high region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J discovery low region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J discovery low region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J discovery high region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J discovery low region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J discovery high region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J discovery low region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J discovery high region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J discovery high region for squark production one-step variable-x simplified models

Signal acceptance in SR6J discovery low region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J discovery low region for squark production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx discovery region for squark production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR2J discovery high region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR2J discovery low region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx discovery region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx discovery region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx discovery region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J discovery high region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J discovery low region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models

Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal acceptance in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models

Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal acceptance in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models

Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal acceptance in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models

Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal acceptance in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models

Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal acceptance in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models

Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal acceptance in SR6J discovery high region for squark production one-step variable-x simplified models

Signal efficiency in SR2J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal acceptance in SR6J discovery low region for squark production one-step variable-x simplified models

Signal efficiency in SR2J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Expected and observed limits computed using asymptotic formulas as a function of the signal mass m_{G*} and k/Mpl for the spin-2 resonance search.

The expected and observed upper limits at 95\% CL on the fiducial cross-section times branching ratio to two photons of a spin-0 resonance as a function of its mass m_X. The decay width of the resonance is equal to 2% of m_X. For masses greater than 1000 GeV, pseudo-experiments are used to verify the expected and observed limits, and used in place of the asymptotic limit when differences are observed.

The expected and observed upper limits at 95\% CL on the fiducial cross-section times branching ratio to two photons of a spin-0 resonance as a function of its mass m_X. The decay width of the resonance is equal to 6% of m_X. For masses greater than 1000 GeV, pseudo-experiments are used to verify the expected and observed limits, and used in place of the asymptotic limit when differences are observed.

The expected and observed upper limits at 95\% CL on the fiducial cross-section times branching ratio to two photons of a spin-0 resonance as a function of its mass m_X. The decay width of the resonance is equal to 10% of m_X. For masses greater than 1000 GeV, pseudo-experiments are used to verify the expected and observed limits, and used in place of the asymptotic limit when differences are observed.

The expected and observed upper limits at 95\% CL on the production cross-section times branching ratio to two photons of the lightest KK graviton as a function of its mass for k/Mpl=0.01. For masses greater than 1000 GeV, pseudo-experiments are used to verify the expected and observed limits, and used in place of the asymptotic limit when differences are observed.

The expected and observed upper limits at 95\% CL on the production cross-section times branching ratio to two photons of the lightest KK graviton as a function of its mass for k/Mpl=0.05. For masses greater than 1000 GeV, pseudo-experiments are used to verify the expected and observed limits, and used in place of the asymptotic limit when differences are observed.

Diphoton invariant mass in the signal region using a binning based on the invariant mass resolution.

Diphoton invariant mass in the signal region binned in 1 GeV bins..

Effect of event selections on a NWA spin-0 and a spin-2 ($k/Mpl=0.01$) MC samples generated for m_X = 1 TeV and on the data. For the MC samples, the event yield is shown after applying event weights; for the data, the absolute yields are shown. The initial yields for data include a trigger preselection that is the OR of a list of single photon and diphoton triggers. The "2 $loose$ photons" step includes the kinematic acceptance cuts. The cross-section times branching ratio for the spin-0 sample is normalized to the MadGraph NLO prediction of 112~fb and the cross-section times branching ratio for the graviton corresponds to the Pythia8 prediction of 12~fb.

Parameterization for the CX and AX factors as function of mX for a scalar particle, as obtained from the narrow-width MC signal samples.

Parameterization for the $C_{X}\cdot A_{X}$ factor as function of $m_{G^*}$ for the RS graviton, as obtained from k/MPl = 0.05 MC signal samples.

Parameterization of the Double Sided Crystal Ball function parameters describing the scalar mass resolution model as a function of m_{X} [GeV].

Parameterization of the Double Sided Crystal Ball function parameters describing the graviton mass resolution model as a function of m_{X} [GeV].

Cutflow of the preselection requirements (see Section 5) for $\mathrm{LQ}_{3}^{\mathrm{d}}$ signals with $m_{\mathrm{LQ}_{3}^{\mathrm{d}}}$=0.9, 1.1, and 1.3 TeV, assuming B=1. The yields correspond to an integrated luminosity of 139 fb$^{-1}$.

Cutflow of the signal region requirements in 1$\ell+\geq 1\tau$ channel (see Table 3) for $\mathrm{LQ}_{3}^{\mathrm{d}}$ signals with $m_{\mathrm{LQ}_{3}^{\mathrm{d}}}$=0.9, 1.1, and 1.3 TeV, assuming B=1. Events that satisfy the preselection requirements are considered. The yields correspond to an integrated luminosity of 139 fb$^{-1}$.

Cutflow of the signal region requirements in the 2$\ell$OS+$\geq 1\tau$ channel (see Table 4) for $\mathrm{LQ}_{3}^{\mathrm{d}}$ signals with $m_{\mathrm{LQ}_{3}^{\mathrm{d}}}$=0.9, 1.1, and 1.3 TeV, assuming B=1. Events that satisfy the preselection requirements are considered. The yields correspond to an integrated luminosity of 139 fb$^{-1}$.

Cutflow of the signal region requirements in the $2\ell$SS/$3\ell+\geq 1\tau$ channel (see Table 5) for $\mathrm{LQ}_{3}^{\mathrm{d}}$ signals with $m_{\mathrm{LQ}_{3}^{\mathrm{d}}}$=0.9, 1.1, and 1.3 TeV, assuming B=1. Events that satisfy the preselection requirements are considered. In this channel, two signal regions (SR-L and SR-H) are defined based on $p_{\mathrm{T}, 1}^{\tau}$, with SR-L and SR-H requiring $125< p_{\mathrm{T}, 1}^{\tau} < 225$ GeV and $p_{\mathrm{T}, 1}^{\tau}>225$ GeV, respectively. The yields correspond to an integrated luminosity of 139 fb$^{-1}$.