 | Expected and observed exclusion contours derived from the combination of the results in the high-\pt\ and \lowpt\ edge SRs based on the best-expected sensitivity (top) and zoomed-in view for the \lowpt\ only (bottom) for the \zstar\ model. The dashed line indicates the expected limits at $95\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and the experimental uncertainties in the signal ($\pm1\sigma_\text{exp}$). The dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma^\text{SUSY}_\text{theory}$). The shaded area on the upper plot indicates the observed limit on this model from Ref.~\cite{SUSY-2016-05}. In the lower plot the observed and expected contours derived from the high-\pt\ SRs alone are overlaid, illustrating the added sensitivity from the low-\pt\ SRs. Small differences in the contours in the compressed region are due to differences in interpolation between the top and bottom plot. |
 | Left, the \met\ spectrum in \dyjets\ MC simulation compared to that of the \gjets\ method applied to \gjets\ MC simulation in SR-low (top), SR-medium (middle) and SR-high (bottom). No selection on \met\ is applied. The error bars on the points indicate the statistical uncertainty of the \dyjets\ MC simulation, and the hashed uncertainty bands indicate the statistical and reweighting systematic uncertainties of the $\gamma+$jet background method. Right, the \met\ spectrum when the method is applied to data in VR-$\Delta\phi$-low (top), VR-$\Delta\phi$-medium (middle) and VR-$\Delta\phi$-high (bottom). The bottom panel of each figure shows the ratio of observation (left, in MC simulation; right, in data) to prediction. In cases where the data point is not accommodated by the scale of this panel, an arrow indicates the direction in which the point is out of range. The last bin always contains the overflow. |
 | Left, the \met\ spectrum in \dyjets\ MC simulation compared to that of the \gjets\ method applied to \gjets\ MC simulation in SR-low (top), SR-medium (middle) and SR-high (bottom). No selection on \met\ is applied. The error bars on the points indicate the statistical uncertainty of the \dyjets\ MC simulation, and the hashed uncertainty bands indicate the statistical and reweighting systematic uncertainties of the $\gamma+$jet background method. Right, the \met\ spectrum when the method is applied to data in VR-$\Delta\phi$-low (top), VR-$\Delta\phi$-medium (middle) and VR-$\Delta\phi$-high (bottom). The bottom panel of each figure shows the ratio of observation (left, in MC simulation; right, in data) to prediction. In cases where the data point is not accommodated by the scale of this panel, an arrow indicates the direction in which the point is out of range. The last bin always contains the overflow. |
 | Expected and observed exclusion contours derived from the best-expected-sensitivity combination of results in the on-$Z$ \mll\ windows of SR-medium and SR-high for the $\tilde{g}$--$\chionezero$ on-shell grid. The dashed line indicates the expected limits at $95\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and the experimental uncertainties in the signal ($\pm1\sigma_\text{exp}$). The dotted lines surrounding the observed limit contour indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma^\text{SUSY}_\text{theory}$). The shaded area indicates the observed limit on this model from Ref.~\cite{SUSY-2016-05}. |
 | Expected and observed exclusion contours derived from the combination of the results in the high-\pt\ and \lowpt\ edge SRs based on the best-expected sensitivity (top) and zoomed-in view for the \lowpt\ only (bottom) for the \zstar\ model. The dashed line indicates the expected limits at $95\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and the experimental uncertainties in the signal ($\pm1\sigma_\text{exp}$). The dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma^\text{SUSY}_\text{theory}$). The shaded area on the upper plot indicates the observed limit on this model from Ref.~\cite{SUSY-2016-05}. In the lower plot the observed and expected contours derived from the high-\pt\ SRs alone are overlaid, illustrating the added sensitivity from the low-\pt\ SRs. Small differences in the contours in the compressed region are due to differences in interpolation between the top and bottom plot. |
 | Expected and observed exclusion contours derived from the combination of the results in the high-\pt\ and \lowpt\ edge SRs based on the best-expected sensitivity (top) and zoomed-in view of the \lowpt\ only (bottom) for the slepton signal model. The dashed line indicates the expected limits at $95\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and the experimental uncertainties in the signal ($\pm1\sigma_\text{exp}$). The dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma^\text{SUSY}_\text{theory}$). The shaded area on the upper plot indicates the observed limit on this model from Ref.~\cite{SUSY-2016-05}. In the lower plot the observed and expected contours derived from the high-\pt\ SRs alone are overlaid, illustrating the added sensitivity from the low-\pt\ SRs. Small differences between the contours in the compressed region are due to differences in interpolation between the top and bottom plot. |
 | Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in (top left) SR-low, (top-right) SR-medium, and (bottom) SR-high of the edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. The last bin contains the overflow. One (two) example signal model(s) are overlaid on the top left (top right, bottom). For the slepton model, the numbers in parentheses in the legend indicate the gluino and $\tilde{\chi}_1^0$ masses of the example model point. In the case of the $Z$ model illustrated, the numbers in parentheses indicate the gluino and $\tilde{\chi}_2^0$ masses, with the $\tilde{\chi}_1^0$ mass being fixed at 1~\GeV\ in this model. |
 | Validation of the flavour-symmetry method using MC simulation (left) and data (right), in SR-low and VR-low (top), SR-medium and VR-medium (middle), and SR-high and VR-high (bottom). On the left the flavour-symmetry estimate from \ttbar, $Wt$, $WW$ and $Z\rightarrow \tau\tau$ MC samples in the $e\mu$ channel is compared with the SF distribution from these MC samples. The MC statistical uncertainty is indicated by the hatched band. In the data plots, all uncertainties in the background expectation are included in the hatched band. The bottom panel of each figure shows the ratio of the observation to the prediction. In cases where the data point is not accommodated by the scale of this panel, an arrow indicates the direction in which the point is out of range. The last bin always contains the overflow. |
 | The observed and expected yields in the diboson VRs. The data are compared to the sum of the expected backgrounds. The observed deviation from the expected yield normalised to the total uncertainty is shown in the bottom panel. The hatched uncertainty band includes the statistical and systematic uncertainties of the background prediction. |
 | Schematic diagrams of the main validation and signal regions for the high-\pt\ (top) and \lowpt\ (bottom) searches. Regions where hatched markings overlap indicate the overlap between various regions. For each search (high-\pt\ or \lowpt), the SRs are not orthogonal; in the case of high-\pt, the VRs also overlap. In both cases, as indicated in the diagrams, there is no overlap between SRs and VRs. |
 | Validation of the flavour-symmetry method using MC simulation (left) and data (right), in SR-low and VR-low (top), SR-medium and VR-medium (middle), and SR-high and VR-high (bottom). On the left the flavour-symmetry estimate from \ttbar, $Wt$, $WW$ and $Z\rightarrow \tau\tau$ MC samples in the $e\mu$ channel is compared with the SF distribution from these MC samples. The MC statistical uncertainty is indicated by the hatched band. In the data plots, all uncertainties in the background expectation are included in the hatched band. The bottom panel of each figure shows the ratio of the observation to the prediction. In cases where the data point is not accommodated by the scale of this panel, an arrow indicates the direction in which the point is out of range. The last bin always contains the overflow. |
 | Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in (left) SRC and (right) SRC-MET of the \lowpt\ edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the $Z^{(*)}$ model with $m(\tilde g)=1000~\GeV$ and $m(\tilde{\chi}_1^0)=900~\GeV$ is overlaid. |
 | Validation of the flavour-symmetry method using MC simulation (left) and data (right), in SR-low and VR-low (top), SR-medium and VR-medium (middle), and SR-high and VR-high (bottom). On the left the flavour-symmetry estimate from \ttbar, $Wt$, $WW$ and $Z\rightarrow \tau\tau$ MC samples in the $e\mu$ channel is compared with the SF distribution from these MC samples. The MC statistical uncertainty is indicated by the hatched band. In the data plots, all uncertainties in the background expectation are included in the hatched band. The bottom panel of each figure shows the ratio of the observation to the prediction. In cases where the data point is not accommodated by the scale of this panel, an arrow indicates the direction in which the point is out of range. The last bin always contains the overflow. |
 | Left, the \met\ spectrum in \dyjets\ MC simulation compared to that of the \gjets\ method applied to \gjets\ MC simulation in SR-low (top), SR-medium (middle) and SR-high (bottom). No selection on \met\ is applied. The error bars on the points indicate the statistical uncertainty of the \dyjets\ MC simulation, and the hashed uncertainty bands indicate the statistical and reweighting systematic uncertainties of the $\gamma+$jet background method. Right, the \met\ spectrum when the method is applied to data in VR-$\Delta\phi$-low (top), VR-$\Delta\phi$-medium (middle) and VR-$\Delta\phi$-high (bottom). The bottom panel of each figure shows the ratio of observation (left, in MC simulation; right, in data) to prediction. In cases where the data point is not accommodated by the scale of this panel, an arrow indicates the direction in which the point is out of range. The last bin always contains the overflow. |
 | Validation of the flavour-symmetry method using MC simulation (left) and data (right), in SR-low and VR-low (top), SR-medium and VR-medium (middle), and SR-high and VR-high (bottom). On the left the flavour-symmetry estimate from \ttbar, $Wt$, $WW$ and $Z\rightarrow \tau\tau$ MC samples in the $e\mu$ channel is compared with the SF distribution from these MC samples. The MC statistical uncertainty is indicated by the hatched band. In the data plots, all uncertainties in the background expectation are included in the hatched band. The bottom panel of each figure shows the ratio of the observation to the prediction. In cases where the data point is not accommodated by the scale of this panel, an arrow indicates the direction in which the point is out of range. The last bin always contains the overflow. |
 | Example decay topologies for three of the simplified models considered. The left two decay topologies involve gluino pair production, with the gluinos following an effective three-body decay for $\tilde{g}\to q \bar{q} \tilde{\chi}_2^0$, with $\tilde{\chi}_{2}^{0} \to \tilde{\ell}^{\mp}\ell^{\pm} / \tilde{\nu}\nu$ for the ``slepton model'' (left) and $\tilde{\chi}_2^0\rightarrow \zstar \tilde{\chi}_1^0$ in the \zstar, $\tilde{g}$--$\tilde{\chi}_2^0$ or $\tilde{g}$--$\tilde{\chi}_1^0$ model (middle). The diagram on the right illustrates the $\tilde{q}$--$\tilde{\chi}_2^0$ on-shell model, where squarks are pair-produced, followed by the decay $\tilde{q}\to q \tilde{\chi}_2^0$, with $\tilde{\chi}_2^0\rightarrow Z \tilde{\chi}_1^0$. |
 | Validation of the background modelling for the \lowpt\ analysis in VRA (top left), VRA2 (top right), VRB (bottom left) and VRC (bottom right) in the SF channels. The \ttbar\ and $Wt$ backgrounds are normalised in $e\mu$ data samples for which the requirements are otherwise the same as in the VR in question. All uncertainties in the background expectation are included in the hatched band. The last bin always contains the overflow. |
 | Validation of the background modelling for the \lowpt\ analysis in VRA (top left), VRA2 (top right), VRB (bottom left) and VRC (bottom right) in the SF channels. The \ttbar\ and $Wt$ backgrounds are normalised in $e\mu$ data samples for which the requirements are otherwise the same as in the VR in question. All uncertainties in the background expectation are included in the hatched band. The last bin always contains the overflow. |
 | Validation of the background modelling for the \lowpt\ analysis in VRA (top left), VRA2 (top right), VRB (bottom left) and VRC (bottom right) in the SF channels. The \ttbar\ and $Wt$ backgrounds are normalised in $e\mu$ data samples for which the requirements are otherwise the same as in the VR in question. All uncertainties in the background expectation are included in the hatched band. The last bin always contains the overflow. |
 | Left, the \met\ spectrum in \dyjets\ MC simulation compared to that of the \gjets\ method applied to \gjets\ MC simulation in SR-low (top), SR-medium (middle) and SR-high (bottom). No selection on \met\ is applied. The error bars on the points indicate the statistical uncertainty of the \dyjets\ MC simulation, and the hashed uncertainty bands indicate the statistical and reweighting systematic uncertainties of the $\gamma+$jet background method. Right, the \met\ spectrum when the method is applied to data in VR-$\Delta\phi$-low (top), VR-$\Delta\phi$-medium (middle) and VR-$\Delta\phi$-high (bottom). The bottom panel of each figure shows the ratio of observation (left, in MC simulation; right, in data) to prediction. In cases where the data point is not accommodated by the scale of this panel, an arrow indicates the direction in which the point is out of range. The last bin always contains the overflow. |
 | Validation of the background modelling for the \lowpt\ analysis in VRA (top left), VRA2 (top right), VRB (bottom left) and VRC (bottom right) in the SF channels. The \ttbar\ and $Wt$ backgrounds are normalised in $e\mu$ data samples for which the requirements are otherwise the same as in the VR in question. All uncertainties in the background expectation are included in the hatched band. The last bin always contains the overflow. |
 | Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in (top left) SR-low, (top-right) SR-medium, and (bottom) SR-high of the edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. The last bin contains the overflow. One (two) example signal model(s) are overlaid on the top left (top right, bottom). For the slepton model, the numbers in parentheses in the legend indicate the gluino and $\tilde{\chi}_1^0$ masses of the example model point. In the case of the $Z$ model illustrated, the numbers in parentheses indicate the gluino and $\tilde{\chi}_2^0$ masses, with the $\tilde{\chi}_1^0$ mass being fixed at 1~\GeV\ in this model. |
 | Expected and observed exclusion contours derived from the best-expected-sensitivity combination of results in the on-$Z$ \mll\ windows of SR-medium and SR-high for the (top) $\tilde{g}$--$\chitwozero$ on-shell grid and (bottom) $\tilde{q}$--$\chitwozero$ on-shell grid. The dashed line indicates the expected limits at $95\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and the experimental uncertainties in the signal ($\pm1\sigma_\text{exp}$). The dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma^\text{SUSY}_\text{theory}$). The shaded area indicates the observed limit on this model from Ref.~\cite{SUSY-2016-05}. |
 | Expected and observed exclusion contours derived from the best-expected-sensitivity combination of results in the on-$Z$ \mll\ windows of SR-medium and SR-high for the (top) $\tilde{g}$--$\chitwozero$ on-shell grid and (bottom) $\tilde{q}$--$\chitwozero$ on-shell grid. The dashed line indicates the expected limits at $95\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and the experimental uncertainties in the signal ($\pm1\sigma_\text{exp}$). The dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma^\text{SUSY}_\text{theory}$). The shaded area indicates the observed limit on this model from Ref.~\cite{SUSY-2016-05}. |
 | Expected and observed exclusion contours derived from the combination of the results in the high-\pt\ and \lowpt\ edge SRs based on the best-expected sensitivity (top) and zoomed-in view of the \lowpt\ only (bottom) for the slepton signal model. The dashed line indicates the expected limits at $95\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and the experimental uncertainties in the signal ($\pm1\sigma_\text{exp}$). The dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma^\text{SUSY}_\text{theory}$). The shaded area on the upper plot indicates the observed limit on this model from Ref.~\cite{SUSY-2016-05}. In the lower plot the observed and expected contours derived from the high-\pt\ SRs alone are overlaid, illustrating the added sensitivity from the low-\pt\ SRs. Small differences between the contours in the compressed region are due to differences in interpolation between the top and bottom plot. |
 | Validation of the data-driven fake-lepton background for the \lowpt\ analysis. The \mll\ distribution in VR-fakes (left) and VR-SS (right). Processes with two prompt leptons are modelled using MC simulation. The hatched band indicates the total systematic and statistical uncertainty of the background prediction. The last bin always contains the overflow. |
 | The observed and expected yields in the (overlapping) \mll\ windows of SR-low, SR-medium, SR-high, SRC and SRC-MET. These are shown for the 29 \mll\ windows for the high-\pt\ SRs (top) and the 12 \mll\ windows for the \lowpt\ SRs (bottom). The data are compared to the sum of the expected backgrounds. The significance of the difference between the observed and expected yields is shown in the bottom plots. For cases where the $p$-value is less than 0.5 a negative significance is shown. The hatched uncertainty band includes the statistical and systematic uncertainties of the background prediction. |
 | Schematic diagrams to show the \mll\ binning used in the various SRs alongside the overlapping \mll\ windows used for model-independent interpretations. The unfilled boxes indicate the \mll\ bin edges for the shape fits used in the model-dependent interpretations. Each filled region underneath indicates one of the \mll\ windows, formed of one or more \mll\ bins, used to derive model-independent results for the given SR. In each case, the last \mll\ bin includes the overflow. |
 | Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in (left) SRC and (right) SRC-MET of the \lowpt\ edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the $Z^{(*)}$ model with $m(\tilde g)=1000~\GeV$ and $m(\tilde{\chi}_1^0)=900~\GeV$ is overlaid. |
 | Validation of the flavour-symmetry method using MC simulation (left) and data (right), in SR-low and VR-low (top), SR-medium and VR-medium (middle), and SR-high and VR-high (bottom). On the left the flavour-symmetry estimate from \ttbar, $Wt$, $WW$ and $Z\rightarrow \tau\tau$ MC samples in the $e\mu$ channel is compared with the SF distribution from these MC samples. The MC statistical uncertainty is indicated by the hatched band. In the data plots, all uncertainties in the background expectation are included in the hatched band. The bottom panel of each figure shows the ratio of the observation to the prediction. In cases where the data point is not accommodated by the scale of this panel, an arrow indicates the direction in which the point is out of range. The last bin always contains the overflow. |
 | The observed and expected yields in the (overlapping) \mll\ windows of SR-low, SR-medium, SR-high, SRC and SRC-MET. These are shown for the 29 \mll\ windows for the high-\pt\ SRs (top) and the 12 \mll\ windows for the \lowpt\ SRs (bottom). The data are compared to the sum of the expected backgrounds. The significance of the difference between the observed and expected yields is shown in the bottom plots. For cases where the $p$-value is less than 0.5 a negative significance is shown. The hatched uncertainty band includes the statistical and systematic uncertainties of the background prediction. |
 | Left, the \met\ spectrum in \dyjets\ MC simulation compared to that of the \gjets\ method applied to \gjets\ MC simulation in SR-low (top), SR-medium (middle) and SR-high (bottom). No selection on \met\ is applied. The error bars on the points indicate the statistical uncertainty of the \dyjets\ MC simulation, and the hashed uncertainty bands indicate the statistical and reweighting systematic uncertainties of the $\gamma+$jet background method. Right, the \met\ spectrum when the method is applied to data in VR-$\Delta\phi$-low (top), VR-$\Delta\phi$-medium (middle) and VR-$\Delta\phi$-high (bottom). The bottom panel of each figure shows the ratio of observation (left, in MC simulation; right, in data) to prediction. In cases where the data point is not accommodated by the scale of this panel, an arrow indicates the direction in which the point is out of range. The last bin always contains the overflow. |
 | Validation of the data-driven fake-lepton background for the \lowpt\ analysis. The \mll\ distribution in VR-fakes (left) and VR-SS (right). Processes with two prompt leptons are modelled using MC simulation. The hatched band indicates the total systematic and statistical uncertainty of the background prediction. The last bin always contains the overflow. |
 | Schematic diagrams of the main validation and signal regions for the high-\pt\ (top) and \lowpt\ (bottom) searches. Regions where hatched markings overlap indicate the overlap between various regions. For each search (high-\pt\ or \lowpt), the SRs are not orthogonal; in the case of high-\pt, the VRs also overlap. In both cases, as indicated in the diagrams, there is no overlap between SRs and VRs. |
 | Left, the \met\ spectrum in \dyjets\ MC simulation compared to that of the \gjets\ method applied to \gjets\ MC simulation in SR-low (top), SR-medium (middle) and SR-high (bottom). No selection on \met\ is applied. The error bars on the points indicate the statistical uncertainty of the \dyjets\ MC simulation, and the hashed uncertainty bands indicate the statistical and reweighting systematic uncertainties of the $\gamma+$jet background method. Right, the \met\ spectrum when the method is applied to data in VR-$\Delta\phi$-low (top), VR-$\Delta\phi$-medium (middle) and VR-$\Delta\phi$-high (bottom). The bottom panel of each figure shows the ratio of observation (left, in MC simulation; right, in data) to prediction. In cases where the data point is not accommodated by the scale of this panel, an arrow indicates the direction in which the point is out of range. The last bin always contains the overflow. |
 | Example decay topologies for three of the simplified models considered. The left two decay topologies involve gluino pair production, with the gluinos following an effective three-body decay for $\tilde{g}\to q \bar{q} \tilde{\chi}_2^0$, with $\tilde{\chi}_{2}^{0} \to \tilde{\ell}^{\mp}\ell^{\pm} / \tilde{\nu}\nu$ for the ``slepton model'' (left) and $\tilde{\chi}_2^0\rightarrow \zstar \tilde{\chi}_1^0$ in the \zstar, $\tilde{g}$--$\tilde{\chi}_2^0$ or $\tilde{g}$--$\tilde{\chi}_1^0$ model (middle). The diagram on the right illustrates the $\tilde{q}$--$\tilde{\chi}_2^0$ on-shell model, where squarks are pair-produced, followed by the decay $\tilde{q}\to q \tilde{\chi}_2^0$, with $\tilde{\chi}_2^0\rightarrow Z \tilde{\chi}_1^0$. |
 | Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in (top left) SR-low, (top-right) SR-medium, and (bottom) SR-high of the edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. The last bin contains the overflow. One (two) example signal model(s) are overlaid on the top left (top right, bottom). For the slepton model, the numbers in parentheses in the legend indicate the gluino and $\tilde{\chi}_1^0$ masses of the example model point. In the case of the $Z$ model illustrated, the numbers in parentheses indicate the gluino and $\tilde{\chi}_2^0$ masses, with the $\tilde{\chi}_1^0$ mass being fixed at 1~\GeV\ in this model. |
 | Schematic diagrams to show the \mll\ binning used in the various SRs alongside the overlapping \mll\ windows used for model-independent interpretations. The unfilled boxes indicate the \mll\ bin edges for the shape fits used in the model-dependent interpretations. Each filled region underneath indicates one of the \mll\ windows, formed of one or more \mll\ bins, used to derive model-independent results for the given SR. In each case, the last \mll\ bin includes the overflow. |
 | Validation of the flavour-symmetry method using MC simulation (left) and data (right), in SR-low and VR-low (top), SR-medium and VR-medium (middle), and SR-high and VR-high (bottom). On the left the flavour-symmetry estimate from \ttbar, $Wt$, $WW$ and $Z\rightarrow \tau\tau$ MC samples in the $e\mu$ channel is compared with the SF distribution from these MC samples. The MC statistical uncertainty is indicated by the hatched band. In the data plots, all uncertainties in the background expectation are included in the hatched band. The bottom panel of each figure shows the ratio of the observation to the prediction. In cases where the data point is not accommodated by the scale of this panel, an arrow indicates the direction in which the point is out of range. The last bin always contains the overflow. |
 | Example decay topologies for three of the simplified models considered. The left two decay topologies involve gluino pair production, with the gluinos following an effective three-body decay for $\tilde{g}\to q \bar{q} \tilde{\chi}_2^0$, with $\tilde{\chi}_{2}^{0} \to \tilde{\ell}^{\mp}\ell^{\pm} / \tilde{\nu}\nu$ for the ``slepton model'' (left) and $\tilde{\chi}_2^0\rightarrow \zstar \tilde{\chi}_1^0$ in the \zstar, $\tilde{g}$--$\tilde{\chi}_2^0$ or $\tilde{g}$--$\tilde{\chi}_1^0$ model (middle). The diagram on the right illustrates the $\tilde{q}$--$\tilde{\chi}_2^0$ on-shell model, where squarks are pair-produced, followed by the decay $\tilde{q}\to q \tilde{\chi}_2^0$, with $\tilde{\chi}_2^0\rightarrow Z \tilde{\chi}_1^0$. |