Observed (points with error bars) and expected background (solid histograms) distributions for $E_{T}^{miss}$ in the signal region (a) SRL, (b) SRM and (c) SRH after the background-only fit applied to the CRs. The predicted signal distributions for the two models with a gluino mass of 2000 GeV and neutralino mass of 250 GeV (SRL), 1050 GeV (SRM) or 1950 GeV (SRH) are also shown for comparison. The uncertainties in the SM background are only statistical.

Observed and expected exclusion limit in the gluino-neutralino mass plane at 95% CL combined using the signal region with the best expected sensitivity at each point, for the full Run-2 dataset corresponding to an integrated luminosity of $139~\mathrm{fb}^{-1}$, for $\gamma/Z$ (a) and $\gamma/h$ (b) signal models. The black solid line corresponds to the expected limits at 95% CL, with the light (yellow) bands indicating the 1$\sigma$ exclusions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves, the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties. For each point in the higgsino-bino parameter space, the labels indicate the best-expected signal region, where L, M and H mean SRL, SRM and SRH, respectively.

Observed and expected exclusion limit in the gluino-neutralino mass plane at 95% CL combined using the signal region with the best expected sensitivity at each point, for the full Run-2 dataset corresponding to an integrated luminosity of $139~\mathrm{fb}^{-1}$, for $\gamma/Z$ (a) and $\gamma/h$ (b) signal models. The black solid line corresponds to the expected limits at 95% CL, with the light (yellow) bands indicating the 1$\sigma$ exclusions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves, the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties. For each point in the higgsino-bino parameter space, the labels indicate the best-expected signal region, where L, M and H mean SRL, SRM and SRH, respectively.

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Cutflow for the SRL selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 250 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.

Cutflow for the SRM selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 1050 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.

Cutflow for the SRH selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 1950 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Breakdown of expected and observed yields in the electroweak search Int, Low, and OffShell signal regions after a simultaneous fit to the signal regions and control regions. All statistical and systematic uncertainties are included.

Breakdown of expected and observed yields in the four edge signal regions, integrated over the $m_{\ell\ell}$ distribution after a separate simultaneous fit to each signal region and control region pair. The uncertainties include both the statistical and systematic sources.

Breakdown of expected and observed yields in the three on-$Z$ signal regions after a separate simultaneous fit to each signal region and control region pair. The uncertainties include both the statistical and systematic sources.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.

Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.

Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.

Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.

Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.

Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.

Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.

Observed and expected dilepton mass distributions in VR3L-STR without a fit to the data. The 'Other' category includes the negligible contributions from $t\bar{t}$ and $Z/\gamma^*$+jets processes. The hatched band contains the statistical uncertainty and the theoretical systematic uncertainties of the $WZ$/$ZZ$ prediction, which are the dominant sources of uncertainty. No fit is performed. The last bin contains the overflow.

Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.

Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.

Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.

Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.

Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.

Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.

Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.

Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.

Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294]. The grey numbers indicate the observed 95\% CLs upper limit on the cross section.

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). 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 on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294]. The grey numbers indicate the observed 95$\%$ CLs upper limit on the cross section.

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. 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 experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

The combined $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution of VRLow-STR and SRLow-STR (left), and the same region with the $\Delta\phi(\boldsymbol{j}_{1,2},\boldsymbol{\mathit{p}}_{ ext{T}}^{ ext{miss}})<0.4$ requirement, used as a control region to normalize the $Z/\gamma^*+\mathrm{jets}$ process (right). Separate fits for the SR and VR are performed, as for the results in the paper, and the resulting distributions are merged. All statistical and systematic uncertainties are included in the hatched bands. The last bins contain the overflow.

Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.

Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.

Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.

Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.

Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.

Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.

Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.

Table 36: Cutflow of expected events in the region SR-OffShell_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 36: Cutflow of expected events in the region SR-OffShell_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 37: Cutflow of expected events in the region SR-OffShell_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 37: Cutflow of expected events in the region SR-OffShell_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 38: Cutflow of expected events in the region SR-Low_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 38: Cutflow of expected events in the region SR-Low_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 39: Cutflow of expected events in the region SR-Low_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 39: Cutflow of expected events in the region SR-Low_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 40: Cutflow of expected events in the region SR-Low-2-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 40: Cutflow of expected events in the region SR-Low-2-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 41: Cutflow of expected events in the region SR-Int_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 41: Cutflow of expected events in the region SR-Int_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 42: Cutflow of expected events in the region SR-Int_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 42: Cutflow of expected events in the region SR-Int_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 43: Cutflow of expected events in the region SR-High_16a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 43: Cutflow of expected events in the region SR-High_16a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 44: Cutflow of expected events in the region SR-High_16b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 44: Cutflow of expected events in the region SR-High_16b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 45: Cutflow of expected events in the region SR-High_8a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 45: Cutflow of expected events in the region SR-High_8a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 46: Cutflow of expected events in the region SR-High_8b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 46: Cutflow of expected events in the region SR-High_8b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 47: Cutflow of expected events in the region SR-1J-High-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 47: Cutflow of expected events in the region SR-1J-High-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 48: Cutflow of expected events in the region SR-llbb-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 48: Cutflow of expected events in the region SR-llbb-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

The combined $m_{jj}$ distribution of CR-Z-EWK and SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in CR-Z-met-EWK (right), which removes the upper limit of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}}) < 9$ from the definition of CR-Z-EWK. This $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ tail overlaps other control and validation regions, but not signal regions. The arrows indicate the signal region SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ phase space which is not included in CR-Z-EWK (right). All EWK search control and signal regions are included in the fit. All statistical and systematic uncertainties are included in the hatched bands. The theoretical uncertainties from CR-Z-EWK are applied to CR-Z-met-EWK. The last bins contain the overflow.

The combined $m_{jj}$ distribution of CR-Z-EWK and SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in CR-Z-met-EWK (right), which removes the upper limit of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}}) < 9$ from the definition of CR-Z-EWK. This $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ tail overlaps other control and validation regions, but not signal regions. The arrows indicate the signal region SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ phase space which is not included in CR-Z-EWK (right). All EWK search control and signal regions are included in the fit. All statistical and systematic uncertainties are included in the hatched bands. The theoretical uncertainties from CR-Z-EWK are applied to CR-Z-met-EWK. The last bins contain the overflow.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Upper limits on the production cross section times branching fraction of the b* RH hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Upper limits on the production cross section times branching fraction of the b* VL hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Upper limits on the production cross section times branching fraction of the B+b hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Upper limits on the production cross section times branching fraction of the B+t hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Parton inclusive-jet $p_T$ and $A_{LL}$ values with associated uncertainties for jet-$\eta$ region $0.5<|\eta|<1$.

Parton inclusive-jet $p_T$ and $A_{LL}$ values with associated uncertainties for jet-$\eta$ region $|\eta|<0.5$.

Parton dijet invariant mass $M_{inv}$ and $A_{LL}$ values with associated uncertainties for the $\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$ topology.

Parton dijet invariant mass $M_{inv}$ and $A_{LL}$ values with associated uncertainties for the $\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$ topology.

Parton inclusive-jet $p_T$, $x_T$, and $A_{LL}$ values with associated uncertainties for jet-$\eta$ region $|\eta|<1$.

The correlation matrix for the point-to-point uncertainties for inclusive jet measurements with jets in the $0.5<|\eta|<1$ region. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The correlation matrix for the point-to-point uncertainties for inclusive jet measurements with jets in the $|\eta|<0.5$ region. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The correlation matrix for the point-to-point uncertainties for inclusive jet measurements with jets in the $|\eta|<1$ region. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The correlation matrix for the point-to-point uncertainties coupling inclusive jet measurements with jets in the $|\eta|<0.5$ region and jets in the $0.5<|\eta|<1$ region. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The correlation matrix for the point-to-point uncertainties coupling inclusive jet measurements with jets in the $0.5<|\eta|<1$ region with dijet measurements with the the $\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The correlation matrix for the point-to-point uncertainties coupling inclusive jet measurements with jets in the $0.5<|\eta|<1$ region with dijet measurements with the the $\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The correlation matrix for the point-to-point uncertainties coupling inclusive jet measurements with jets in the $|\eta|<0.5$ region with dijet measurements with the the $\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The correlation matrix for the point-to-point uncertainties coupling inclusive jet measurements with jets in the $|\eta|<0.5$ region with dijet measurements with the the $\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The correlation matrix for the point-to-point uncertainties coupling inclusive jet measurements with jets in the $|\eta|<1$ region with dijet measurements with the the $\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The correlation matrix for the point-to-point uncertainties coupling inclusive jet measurements with jets in the $|\eta|<1$ region with dijet measurements with the the $\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The correlation matrix for the point-to-point uncertainties for dijet measurements with the $\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The correlation matrix for the point-to-point uncertainties for dijet measurements with the $\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The correlation matrix for the point-to-point uncertainties coupling dijet measurements with the $\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$ topology and the $\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values.

The ratio of away-side yields in Lead-Lead/Proton-Proton collisions in the peripheral region.

The ratio between near-side central/peripheral yields in Lead-Lead collisions.

The ratio between away-side central/peripheral yields in Lead-Lead collisions.