Observed limits on the effective theory mass scale M* as a function of the dark matter mass M(chi) at 90% confidence-level from combined mono-W-boson and mono-Z-boson signals for various operators.

Limits on chi-nucleon cross sections as a function of M(chi) at 90% confidence-level.

Limit on the Higgs boson cross section for decay to invisible particles divided by the cross section for decays to Standard Model particles as a function of M(Higgs) at 95% confidence-level.

Acceptance (A), efficiency (EPSILON), cross-section (SIG) and limits in number of events for the excited quark benchmark model, as a function of the signal mass M(q*). Uncertainties on the cross section are on the order of 1%. The limits include statistical uncertainties only. Expected limits include the 68% uncertainty band. Acceptance was calculated using parton-level quantities by imposing criteria that apply directly to kinematic selections (photon/jet |eta|, photon/jet transverse momentum, Delta(eta), Delta(R)). All other selections, which in general correspond to event and object quality criteria, were used to calculate the efficiency based on the events included in the acceptance.

Observed 90% C.L. lower limits on the mass scale, M*, of considered effective field theories as a function of mChi. For each operator, the values below the corresponding line are excluded.

Expected 95% C.L. upper limits on the cross section times branching fraction as a function of mChi. For each operator, the values above the corresponding line are excluded.

Observed 95% C.L. upper limits on the cross section times branching fraction as a function of mChi. For each operator, the values above the corresponding line are excluded.

Definition of the fiducial phase space.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Numbers of observed and background events for SR3L low for each bin of the distribution in Meff. The table corresponds to Fig. 4(d). The statistical and systematic uncertainties are combined for the predicted numbers.

Numbers of observed and background events for SR3L high for each bin of the distribution in Meff. The table corresponds to Fig. 4(e). The statistical and systematic uncertainties are combined for the predicted numbers.

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

The efficiencies are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

The efficiencies are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.

The efficiencies are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into b s and gluinos decay into t stop (see Fig. 5d in the paper).

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

The efficiencies are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

The acceptances (in percent, %) are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

The acceptances (in percent, %) are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.

The acceptances (in percent, %) are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

The acceptances (in percent, %) are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

The limits on observed cross section are calculated for all simplified models. The simplified models are for direct pair production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair-production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

The signal event yields are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

The signal event yields are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop)-20 GeV.

The signal event yields are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

The signal event yields are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

Experimental uncertainties on the signal event yields are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

Experimental uncertainties on the signal event yields are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.

Experimental uncertainties on the signal event yields are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

Experimental uncertainties on the signal event yields are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

Statistical uncertainties on the signal event yields are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

Statistical uncertainties on the signal event yields are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.

Statistical uncertainties on the signal event yields are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

Statistical uncertainties on the signal event yields are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W ^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

The confidence levels are calculated for all simplified models. For each model, the observed and expected values are given. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

The confidence levels are calculated for all simplified models. For each model, the observed and expected values are given. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

The confidence levels are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluion), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

The confidence levels are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the expected and observed values are given. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).

The confidence levels are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the expected and observed values are given. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.

The confidence levels are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the expected and observed values are given.

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

The confidence levels are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the expected and observed values are given. The model assumes tan(beta)=30, A0=2m0, and mu>0.

Missing ET distribution in SR2B for stop GMSB model (data+/-stat, bkg+/-(stat+syst), signal+/-stat), m(stop1)=500 GeV, m(neutralino1)=400 GeV.

Missing ET distribution in SR2C for stop GMSB model (data+/-stat, bkg+/-(stat+syst), signal+/-stat), m(stop1)=500 GeV, m(neutralino1)=400 GeV.

met_sr3a (data+/-stat, bkg+/-(stat+syst), signal+/-stat).

met_sr3b (data+/-stat, bkg+/-(stat+syst), signal+/-stat).

Expected exclusion limits at 95% CL for stop2 grid.

Expected exclusion limits +1sigma at 95% CL for stop2 grid.

Expected exclusion limits -1sigma at 95% CL for stop2 grid.

Observed exclusion limits at 95% CL for stop2 grid.

Observed exclusion limits +1sigma SUSY cross section uncertainty at 95% CL for stop2 grid.

Observed exclusion limits -1sigma SUSY cross section uncertainty at 95% CL for stop2 grid.

t2_350_n1_20_Observed.

t2_350_n1_20_Expected.

t2_500_n1_20_Observed.

t2_500_n1_20_Expected.

t2_500_n1_120_Observed.

t2_500_n1_120_Expected.

Expected exclusion limits at 95% CL for stop GMSB model.

Expected exclusion limits +1sigma at 95% CL for stop GMSB model.

Expected exclusion limits -1sigma at 95% CL for stop GMSB model.

Observed exclusion limits at 95% CL for stop GMSB model.

Observed exclusion limits +1sigma SUSY cross section uncertainty at 95% CL for stop GMSB model.

Observed exclusion limits -1sigma SUSY cross section uncertainty at 95% CL for stop GMSB model.

met_3l2j (data+/-stat, bkg+/-(stat+syst), signal+/-stat).

met_3l3j (data+/-stat, bkg+/-(stat+syst), signal+/-stat).

The best expected signal region for stop2 model, where 1 and 2 mean SR3A and SR3B.

The best expected signal region for stop GMSB model, where 1 and 2 mean SR2A and SR2B.

The best expected signal region for stop2 mass 350 GeV and neutralino1 mass 20 GeV, where 1 and 2 mean SR3A and SR3B.

The best expected signal region for stop2 mass 500 GeV and neutralino1 mass 20 GeV, where 1 and 2 mean SR3A and SR3B.

The best expected signal region for stop2 mass 500 GeV and neutralino1 mass 120 GeV, where 1 and 2 mean SR3A and SR3B.

Observed upper limit on the signal cross section for stop2 grid.

Number of generated MC events for stop Natural GMSB model.

Cross section for stop Natural GMSB model.

xsec_stop2.

Ntot_stop2.

Acceptance of stop GMSB model for SR2A.

Efficiency of stop GMSB model for SR2A.

Number of expected signal events of stop GMSB model for SR2A.

Total systematic uncertainty of stop GMSB model for SR2A.

Observed CL_s of stop GMSB model for SR2A.

Expected CL_s of stop GMSB model for SR2A.

Acceptance of stop GMSB model for SR2B.

Efficiency of stop GMSB model for SR2B.

Number of expected signal events of stop GMSB model for SR2B.

Total systematic uncertainty of stop GMSB model for SR2B.

Observed CL_s of stop GMSB model for SR2B.

Expected CL_s of stop GMSB model for SR2B.

Acceptance of stop GMSB model for SR2C.

Efficiency of stop GMSB model for SR2C.

Number of expected signal events of stop GMSB model for SR2C.

Total systematic uncertainty of stop GMSB model for SR2C.

Observed CL_s of stop GMSB model for SR2C.

Expected CL_s of stop GMSB model for SR2C.

Nexp_SR3A.

RelUnc_SR3A.

Acc_SR3A.

Eff_SR3A.

CLsExp_SR3A.

CLs_SR3A.

Nexp_SR3B.

RelUnc_SR3B.

Acc_SR3B.

Eff_SR3B.

CLsExp_SR3B.

CLs_SR3B.

The effective mass distribution in VR2Z.

The ETmiss distribution in SR0noZa.

The effective mass distribution in SR0noZa.

The ETmiss distribution in SR1noZa.

The effective mass distribution in SR1noZa.

The ETmiss distribution in SR2noZa.

The effective mass distribution in SR2noZa.

The ETmiss distribution in SR0noZb.

The effective mass distribution in SR0noZb.

The ETmiss distribution in SR1noZb.

The effective mass distribution in SR1noZb.

The ETmiss distribution in SR2noZb.

The effective mass distribution in SR2noZb.

The ETmiss distribution in SR0Z.

The effective mass distribution in SR0Z.

The ETmiss distribution in SR1Z.

The effective mass distribution in SR1Z.

The ETmiss distribution in SR2Z.

The effective mass distribution in SR2Z.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the R-slepton RPC model.

Expected 95% CL exclusion contour for the R-slepton RPC model.

Observed and expected 95% CL cross-section upper limits for the Stau RPC model, together with the theoretically predicted cross-section.

Observed and expected 95% CL cross-section upper limits for the Z RPC model, together with the theoretically predicted cross-section.

Observed 95% CL exclusion contour for the GGM tan beta = 1.5 model.

Expected 95% CL exclusion contour for the GGM tan beta = 1.5 model.

Observed 95% CL exclusion contour for the GGM tan beta = 30 model.

Expected 95% CL exclusion contour for the GGM tan beta = 30 model.

Observed 95% CL cross-section upper limit for the RPV chargino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV chargino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV gluino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV gluino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Lslepton NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Lslepton NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Rslepton NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Rslepton NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV sneutrino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV sneutrino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the R-slepton RPC model, and the selection of Z-veto signal regions used to set limits in this model. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bbb' means that the regions SR0noZb, SR1noZb and SR2noZb were used, in addition to the three Z-rich regions (SR0-2Z). For the RPC stau and Z models, the ``aaa' combination of regions was used throughout.

Performance of the SR0noZa selection in the R-slepton RPC model: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR0noZb selection in the RPV chargino NLSP model with lambda_121 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR1noZa selection in the RPV sneutrino NLSP model with lambda_233 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR1noZb selection in the RPV gluino NLSP model with lambda_133 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR2noZa selection in the RPV sneutrino NLSP model with lambda_233 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR2noZb selection in the RPV gluino NLSP model with lambda_133 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR0Z selection in the GGM tan beta = 30 model: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Cut flows for a representative selection of SUSY signal points in the Z-veto signal regions. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise.

Cut flows for a representative selection of SUSY signal points in the Z-rich signal regions. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses (or the value of mu in the case of GGM models). The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise.

Cut flows by lepton channel for a representative selection of SUSY signal points in the SR0noZa signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The RPC R-slepton model is used, with (m2,m1) = (450,300) GeV.

Cut flows by lepton channel for a representative selection of SUSY signal points in the SR1noZb signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The RPV gluino NLSP model is used, with lambda_133 != 0 and (m2,m1) = (800,400) GeV.

Cut flows by lepton channel for a representative selection of SUSY signal points in the SR0Z signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the value of mu. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The GGM tan beta = 30 model is used, with (m2,m1) = (200,1000) GeV.

For events in the low-ETmiss validation region, the M(l tau) distribution in VR1taua.

For events in the low-ETmiss validation region, the MT2max distribution in VR2taua.

For events in the high-ETmiss + b-tagged jet validation region, the ETmiss distribution in VR0taunoZb.

For events in the high-ETmiss + b-tagged jet validation region, the ETmiss distribution in VR0tauZb.

For events in the high-ETmiss + b-tagged jet validation region, the ETmiss distribution in VR1taub.

For events in the high-ETmiss + b-tagged jet validation region, the ETmiss distribution in VR2taub.

Expected distributions of SM background events and observed data distributions in the binned signal regions SR0taua.

The distribution of ETmiss in the summation of all SR0taua regions prior to the requirements on this variable.

The distribution of MT in the summation of all SR0taua regions prior to the requirements on this variable.

The distribution of M(SFOS) in the summation of all SR0taua regions prior to the requirements on this variable.

Expected distribution of SM background events and observed data distribution for the MIN(DELTA(PHI(ll))) variable in the SR0taub region, prior to the requirements on this variable.

Expected distribution of SM background events and observed data distribution for the ETmiss variable in the SR1tau region, prior to the requirements on this variable.

Expected distribution of SM background events and observed data distribution for the MT2max variable in the SR2taua region, prior to the requirements on this variable.

Expected distribution of SM background events and observed data distribution for the M(tau tau) variable in the SR2taub region, prior to the requirements on this variable.

Observed 95% CL exclusion contour for chargino and neutralino production in the sleptonL-mediated simplified model.

Expected 95% CL exclusion contour for chargino and neutralino production in the sleptonL-mediated simplified model.

Observed 95% CL exclusion contour for chargino and neutralino production in the WZ-mediated simplified model.

Expected 95% CL exclusion contour for chargino and neutralino production in the WZ-mediated simplified model.

Observed 95% CL exclusion contour for chargino and neutralino production in the stauL-mediated simplified model.

Expected 95% CL exclusion contour for chargino and neutralino production in the stauL-mediated simplified model.

Observed 95% CL exclusion contour for chargino and neutralino production in the Wh-mediated simplified model.

Expected 95% CL exclusion contour for chargino and neutralino production in the Wh-mediated simplified model.

Observed 95% CL exclusion contour in the pMSSM model with sleptons and M1 = 100 GeV.

Expected 95% CL exclusion contour in the pMSSM model with sleptons and M1 = 100 GeV.

Observed 95% CL exclusion contour in the pMSSM model with sleptons and M1 = 140 GeV.

Expected 95% CL exclusion contour in the pMSSM model with sleptons and M1 = 140 GeV.

Observed 95% CL exclusion contour in the pMSSM model with sleptons and M1 = 250 GeV.

Expected 95% CL exclusion contour in the pMSSM model with sleptons and M1 = 250 GeV.

Observed 95% CL exclusion contour in the pMSSM model with staus.

Expected 95% CL exclusion contour in the pMSSM model with staus.

Observed 95% CL exclusion contour in the pMSSM model with no sleptons.

Expected 95% CL exclusion contour in the pMSSM model with no sleptons.

Excluded model cross-sections at 95% confidence level for the slepL-mediated simplified model.

Excluded model cross-sections at 95% confidence level for WZ-mediated simplified model.

Excluded model cross-sections at 95% confidence level for stauL-mediated simplified model.

Excluded model cross-sections at 95% confidence level for Wh-mediated simplified model.

Number of generated signal events for slepL-mediated simplified model.

Number of generated signal events for WZ-mediated simplified model.

Number of generated signal events for stauL-mediated simplified model.

Number of generated signal events for Wh-mediated simplified model.

Cross-sections for slepL-mediated simplified model.

Cross-sections for WZ-mediated simplified model.

Cross-sections for stauL-mediated simplified model.

Cross-sections for Wh-mediated simplified model.

Acceptance for slepL-mediated simplified model using SR0taua bin 20.

Acceptance for WZ-mediated simplified model using SR0taua bin 16.

Acceptance for stauL-mediated simplified model using SR2taua.

Acceptance for Wh-mediated simplified model using SR2taub.

Efficiency for slepL-mediated simplified model using SR0taua bin 20.

Efficiency for WZ-mediated simplified model using SR0taua bin 16.

Efficiency for stauL-mediated simplified model using SR2taua.

Efficiency for Wh-mediated simplified model using SR2taub.

The total experimental uncertainty, not including Monte Carlo statistics, for the slepL-mediated simplified model using SR0taua bin 20.

The total experimental uncertainty, not including Monte Carlo statistics, for the WZ-mediated simplified model using SR0taua bin 16.

The total experimental uncertainty, not including Monte Carlo statistics, for the stauL-mediated simplified model using SR2taua.

The total experimental uncertainty, not including Monte Carlo statistics, for the Wh-mediated simplified model using SR2taub.

The expected CL for slepL-mediated simplified model using SR0taua bin 20, using pseudo-experiments.

The expected CL for WZ-mediated simplified model using SR0taua bin 16, using pseudo-experiments.

The expected CL for stauL-mediated simplified model using SR2taua, using pseudo-experiments.

The expected CL for Wh-mediated simplified model using SR2taub, using pseudo-experiments.

The observed CL for slepL-mediated simplified model using SR0taua bin 20, using pseudo-experiments.

The observed CL for WZ-mediated simplified model using SR0taua bin 16, using pseudo-experiments.

The observed CL for stauL-mediated simplified model using SR2taua, using pseudo-experiments.

The observed CL for Wh-mediated simplified model using SR2taub, using pseudo-experiments.

95% C.L. observed exclusion contour for all regions combined.

Best expected signal region for signal points.

95% CLs observed upper limit on model cross-section for signal points in the signal region with $m_{CT}>150$ GeV.

95% C.L. expected exclusion contour for the $m_{CT}>150 $ GeV region.

95% C.L. observed exclusion contour for the $m_{CT}>150 $ GeV region.

95% CLs observed upper limit on model cross-section for signal points in the signal region with $m_{CT}>200$ GeV.

95% C.L. expected exclusion contour for the $m_{CT}>200 $ GeV region.

95% C.L. observed exclusion contour for the $m_{CT}>200 $ GeV region.

95% CLs observed upper limit on model cross-section for signal points in the signal region with $m_{CT}>250$ GeV.

95% C.L. expected exclusion contour for the $m_{CT}>250 $ GeV region.

95% C.L. observed exclusion contour for the $m_{CT}>250 $ GeV region.

95% CLs upper limit on model cross-section for signal points in C1.

95% CLs upper limit on model cross-section for signal points in C2.

Acceptance times Efficiency for signal points in the signal region with $m_{CT}>150$ GeV.

Acceptance times Efficiency for signal points in the signal region with $m_{CT}>200$ GeV.

Acceptance times Efficiency for signal points in the signal region with $m_{CT}>250$ GeV.

Acceptance (flavour-blind) for signal points in the signal region with $m_{CT}>150$ GeV.

Acceptance (flavour-blind) for signal points in the signal region with $m_{CT}>200$ GeV.

Acceptance (flavour-blind) for signal points in the signal region with $m_{CT}>250$ GeV.

Signal cross-sections and uncertainties.

Distribution of ETmiss in the signal region for data and for the background predicted from the fit in the CRs. Overflows are included in the final bin.

Limits at 90% C.L. on the EFT suppression scale M* as a function of the WIMP mass m_chi, for the vector operator D5. Results where EFT truncation is applied are also shown, assuming coupling values sqrt(g_f g_chi)= 1, 4pi.

Limits at 90% C.L. on the EFT suppression scale M* as a function of the WIMP mass m_chi, for the axial-vector operator D8. Results where EFT truncation is applied are also shown, assuming coupling values sqrt(g_f g_chi)= 1, 4pi.

Limits at 90% C.L. on the EFT suppression scale M* as a function of the WIMP mass m_chi, for the tensor operator D9. Results where EFT truncation is applied are also shown, assuming coupling values sqrt(g_f g_chi)= 1, 4pi.

Upper limits at 90% C.L. on the WIMP-nucleon scattering cross section as a function of m_chi for spin-independent and spin-dependent interactions, for a coupling strength g = sqrt(g_f g_chi) of unity or the maximum value (4 pi) that keeps the model within its perturbative regime. The truncation procedure is applied for both cases.

Upper limits at 95% C.L. on the WIMP simplified model coupling parameter, sqrt(g_f g_chi), with vector coupling and mediator width Gamma=m_V/3, as a function of WIMP (m_chi) and the mediator particle (m_V) masses.

Observed lower limits at 95% C.L. on the EFT suppression scale M* as a function of the mediator mass mV, for a Z'-like mediator with vector interactions. For a dark-matter mass m_chi of 50 or 400 GeV, results are shown for different values of the mediator total decay width Gamma.

Observed lower limits at 95% C.L. on the EFT suppression scale M* as a function of the mediator mass mV, for a Z'-like mediator with axial-vector interactions. For a dark-matter mass m_chi of 50 or 400 GeV, results are shown for different values of the mediator total decay width Gamma.

Limits at 95% C.L. on the effective mass scale M* in the (k2, k1) parameter plane for the s-channel EFT model inspired by Fermi-LAT gamma-ray line, for m_chi = 130 GeV. The upper part of the plane is excluded.

Lower limits at 95% C.L. on the mass scale M_D in the ADD models of large extra dimensions, for several values of the number of extra dimensions.

Upper limits at 95% C.L. on the cross section for the compressed squark model, as a function of the squark mass, m_squark, and of the difference between the squark mass and the mass of the neutralino, m_squark-m_neutralino, in the compressed region of m_squark-m_neutralino < 50 GeV.