Missing transverse momentum distribution after SR3b selection, beside the $E_\mathrm{T}^\mathrm{miss}$ requirement. The results in the signal region correspond to the last inclusive bin. The systematic uncertainties include theory uncertainties for the backgrounds with prompt SS/3L and the full systematic uncertainties for data-driven backgrounds. For illustration the distribution for a benchmark SUSY scenario ($pp\to \tilde g\tilde g$, $\tilde g\to t\bar t\tilde\chi_1^0$, $m_{\tilde g}=1.2$ TeV, $m_{\tilde\chi_1^0}=0.7$ TeV) is also shown.

Observed exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qq(\tilde\ell\ell/\tilde\nu\nu)$ decays. All limits are computed at 95% CL.

Expected exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qq(\tilde\ell\ell/\tilde\nu\nu)$ decays. All limits are computed at 95% CL.

Upper limits on signal cross-sections as function of the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qq(\tilde\ell\ell/\tilde\nu\nu)$ decays, obtained using the signal efficiency and acceptance specific to each model. All limits are computed at 95% CL.

Observed exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qqWZ\tilde\chi_1^0$ decays. All limits are computed at 95% CL.

Expected exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qqWZ\tilde\chi_1^0$ decays. All limits are computed at 95% CL.

Upper limits on signal cross-sections as function of the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qqWZ\tilde\chi_1^0$ decays, obtained using the signal efficiency and acceptance specific to each model. All limits are computed at 95% CL.

Observed exclusion limits on the $\tilde b_1$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde b_1\tilde b_1^*$ pair production with exclusive $\tilde b_1\to t\tilde\chi_1^-$ decays. All limits are computed at 95% CL.

Expected exclusion limits on the $\tilde b_1$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde b_1\tilde b_1^*$ pair production with exclusive $\tilde b_1\to t\tilde\chi_1^-$ decays. All limits are computed at 95% CL.

Upper limits on signal cross-sections as function of the $\tilde b_1$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde b_1\tilde b_1^*$ pair production with exclusive $\tilde b_1\to t\tilde\chi_1^-$ decays, obtained using the signal efficiency and acceptance specific to each model. All limits are computed at 95% CL.

Observed exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to t\bar t\tilde\chi_1^0$ decays. All limits are computed at 95% CL.

Expected exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to t\bar t\tilde\chi_1^0$ decays. All limits are computed at 95% CL.

Upper limits on signal cross-sections as function of the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to t\bar t\tilde\chi_1^0$ decays, obtained using the signal efficiency and acceptance specific to each model. All limits are computed at 95% CL.

SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to q\bar q(\tilde\ell\ell/\tilde\nu\nu)$ decay: signal acceptance (in %) in the signal region SR0b3j. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to q\bar q(\tilde\ell\ell/\tilde\nu\nu)$ decay: reconstruction efficiency (in %) in the signal region SR0b3j. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to q\bar qWZ\tilde\chi_1^0$ decay: signal acceptance (in %) in the signal region SR0b5j. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to q\bar qWZ\tilde\chi_1^0$ decay: reconstruction efficiency (in %) in the signal region SR0b5j. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde b_1\tilde b_1^*$ production and $\tilde b_1\to tW\tilde\chi_1^0$ decay: signal acceptance (in %) in the signal region SR1b. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde b_1\tilde b_1^*$ production and $\tilde b_1\to tW\tilde\chi_1^0$ decay: reconstruction efficiency (in %) in the signal region SR1b. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to t\bar t\tilde\chi_1^0$ decay: signal acceptance (in %) in the signal region SR3b. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to t\bar t\tilde\chi_1^0$ decay: reconstruction efficiency (in %) in the signal region SR3b. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

Observed 95% CL limit for the pMSSM grid.

Observed 95% CL limit for the pMSSM grid when the signal cross section is increased by one standard deviation.

Observed 95% CL limit for the pMSSM grid when the signal cross section is decreased by one standard deviation.

Expected 95% CL limit for the pMSSM grid.

+1 sigma excursion of the expected 95% CL limit for the pMSSM grid.

-1 sigma excursion of the expected 95% CL limit for the pMSSM grid.

Observed 95% CL limit for the 2Step grid.

Observed 95% CL limit for the 2Step grid when the signal cross section is increased by one standard deviation.

Observed 95% CL limit for the 2Step grid when the signal cross section is decreased by one standard deviation.

Expected 95% CL limit for the 2Step grid.

+1 sigma excursion of the expected 95% CL limit for the 2Step grid.

-1 sigma excursion of the expected 95% CL limit for the 2Step grid.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j50 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 9j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 9j50 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 9j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 7j80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 7j80 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 7j80 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

Degree of multijet closure for signal and vaidation regions with at no b-jet requirement. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The bins labelled in bold are signal regions, while the others are validation regions. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions with at least 1 b-jet. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The bins labelled in bold are signal regions, while the others are validation regions. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions with at least 2 b-jets. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The bins labelled in bold are signal regions, while the others are validation regions. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Summary of all 15 signal regions (post-fit).

Signal region yielding the best-expected CLs value, the best expected CLs value, and the corresponding observed CLs value for the 2Step grid.

Signal region yielding the best-expected CLs value, the best expected CLs value, and the corresponding observed CLs value for the pMSSM grid.

95% CLs observed upper limit on model cross-section for 2-step signal points for the best-expected signal region.

Performance of the 8j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 9j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 9j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 9j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 10j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 10j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 10j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 7j80-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 7j80-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 7j80-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j80-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j80-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j80-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 9j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 9j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 9j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 10j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 10j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 10j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 7j80-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 7j80-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 7j80-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j80-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j80-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j80-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Cross-section upper limit in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the best expected signal region.

Cross-section upper limit in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the SRA250 signal region.

Cross-section upper limit in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the SRA350 signal region.

Cross-section upper limit in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the SRA450 signal region.

Cross-section upper limit in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the SRB signal region.

Expected CLs values in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the best expected signal region.

Expected CLs values in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the SRA250 signal region.

Expected exclusion limit at 95% CL in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for signal region SRA250.

Observed exclusion limit at 95% CL in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for signal region SRA250.

Expected CLs values in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the SRA350 signal region.

Expected exclusion limit at 95% CL in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for signal region SRA350.

Observed exclusion limit at 95% CL in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for signal region SRA350.

Expected CLs values in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the SRA450 signal region.

Expected exclusion limit at 95% CL in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for signal region SRA450.

Observed exclusion limit at 95% CL in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for signal region SRA450.

Expected CLs values in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the SRB signal region.

Expected exclusion limit at 95% CL in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for signal region SRB.

Observed exclusion limit at 95% CL in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for signal region SRB.

Observed CLs values in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the best expected signal region.

Observed CLs values in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the SRA250 signal region.

Observed CLs values in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the SRA350 signal region.

Observed CLs values in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the SRA450 signal region.

Observed CLs values in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the SRB signal region.

Signal efficiency (in %) in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for the best expected signal region.

Signal efficiency (in %) in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for the SRA250 signal region.

Signal efficiency (in %) in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for the SRA350 signal region.

Signal efficiency (in %) in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for the SRA450 signal region.

Signal efficiency (in %) in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for the SRB signal region.

Signal acceptance (in %) in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for the best expected signal region.

Signal acceptance (in %) in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for the SRA250 signal region.

Signal acceptance (in %) in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for the SRA350 signal region.

Signal acceptance (in %) in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for the SRA450 signal region.

Signal acceptance (in %) in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane for the sbottom pair production scenario, for the SRB signal region.

Total experimental systematic uncertainty in percent on the signal efficiency times acceptance in the $m(\tilde b_1)$-$m(\tilde\chi^0_1)$ plane. The best expected signal region selection is used per point.

Comparison of data with estimated backgrounds in the $\tilde{E}_\text{T}^\text{miss}$ distribution with the TZCR1 event selection except for the requirement on $\tilde{E}_\text{T}^\text{miss}$. The variables $\tilde{E}_\text{T}^\text{miss}$ and $\tilde{m}_\text{T}$ are constructed in the same way as $E_\text{T}^\text{miss}$ and $m_\text{T}$ but treating the leading photon transverse momentum as invisible. The predicted backgrounds are scaled with normalization factors. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin includes overflow.

Comparison of data with estimated backgrounds in the $\tilde{m}_\text{T}$ distribution with the TZCR1 event selection except for the requirement on $\tilde{m}_\text{T}$. The variables $\tilde{E}_\text{T}^\text{miss}$ and $\tilde{m}_\text{T}$ are constructed in the same way as $E_\text{T}^\text{miss}$ and $m_\text{T}$ but treating the leading photon transverse momentum as invisible. The predicted backgrounds are scaled with normalization factors. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin includes overflow.

Comparison of the observed data ($n_\text{obs}$) with the predicted background ($n_\text{exp}$) in the validation and signal regions. The background predictions are obtained using the background-only fit configuration. The bottom panel shows the significance of the difference between data and predicted background, where the significance is based on the total uncertainty ($\sigma_\text{tot}$).

Jet multiplicity distributions for events where exactly two signal leptons are selected. No correction factors are included in the background normalizations. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin includes overflow.

Jet multiplicity distributions for events where exactly one lepton plus one $\tau$ candidate are selected. No correction factors are included in the background normalizations. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin includes overflow.

The $E_\text{T}^\text{miss}$ distribution in SR1. In the plot, the full event selection in the corresponding signal region is applied, except for the requirement on $E_\text{T}^\text{miss}$. The predicted backgrounds are scaled with normalization factors. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin contains the overflow. Benchmark signal models are overlaid for comparison. The benchmark models are specified by the gluino and stop masses, given in TeV in the table.

The $m_\text{T}$ distribution in SR1. In the plot, the full event selection in the corresponding signal region is applied, except for the requirement on $m_\text{T}$. The predicted backgrounds are scaled with normalization factors. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin contains the overflow. Benchmark signal models are overlaid for comparison. The benchmark models are specified by the gluino and stop masses, given in TeV in the table.

Expected (black dashed) 95% excluded regions in the plane of $m_{\tilde{g}}$ versus $m_{\tilde{t}_1}$ for gluino-mediated stop production.

Observed (red solid) 95% excluded regions in the plane of $m_{\tilde{g}}$ versus $m_{\tilde{t}_1}$ for gluino-mediated stop production.

Expected (black dashed) 95% excluded regions in the plane of $m_{\tilde{t}_1}$ versus $m_{\tilde{\chi}_1^0}$ for direct stop production.

Observed (red solid) 95% excluded regions in the plane of $m_{\tilde{t}_1}$ versus $m_{\tilde{\chi}_1^0}$ for direct stop production.

The expected upper limits on $T$ quark pair production times the squared branching ratio for $T \rightarrow tZ$ as a function of the $T$ quark mass.

The observed upper limits on $T$ quark pair production times the squared branching ratio for $T \rightarrow tZ$ as a function of the $T$ quark mass.

The expected limits on $T$ quarks as a function of the branching ratios $B\left(T \rightarrow bW\right)$ and $B\left(T \rightarrow tH\right)$ for a $T$ quark with a mass of 800 GeV. The $T$ is assumed to decay in three possible ways: $T \to tZ$, $T \to tH$, and $T \to bW$.

The observed limits on $T$ quarks as a function of the branching ratios $B\left(T \rightarrow bW\right)$ and $B\left(T \rightarrow tH\right)$ for a $T$ quark with a mass of 800 GeV. The $T$ is assumed to decay in three possible ways: $T \to tZ$, $T \to tH$, and $T \to bW$.

The $m_\text{T}$ distribution in the WVR2-tail validation region which has the same preselection and jet $p_\text{T}$ requirements as SR2.

The $am_\text{T2}$ distribution in the WVR2-tail validation region which has the same preselection and jet $p_\text{T}$ requirements as SR2.

Large-radius jet mass ($R=1.2$), decomposed into the number of small-radius jet constituents. The lower panel shows the ratio of the total data to the total prediction (summed over all jet multiplicities). Events are required to have one lepton, four jets with $p_\text{T}>80,50,40,40$ GeV, at least one $b$-tagged jet, $E_\text{T}^\text{miss}>200$ GeV, and $m_\text{T}>30$ GeV.

Distribution of $m_\text{T2}^\tau$ in data for a selection enriched in $t\bar{t}$ events with one hadronically decaying $\tau$. Events that have no hadronic $\tau$ candidate (that passes the Loose identification criteria, as well as other requirements) are not shown in the plot.

Upper limits on the model cross-section in units of pb for the gluino-mediated stop models.

Upper limits on the model cross-section in units of pb for the models with direct stop pair production.

Illustration of the best expected signal region per signal grid point for the gluino-mediated stop models. This mapping is used for the final combined exclusion limits.

Illustration of the best expected signal region per signal grid point for models with direct stop pair production. This mapping is used for the final combined exclusion limits.

Expected $CL_s$ values for the gluino-mediated stop models.

Observed $CL_s$ values for the gluino-mediated stop models.

Expected $CL_s$ values for the direct stop pair production models.

Observed $CL_s$ values for the direct stop pair production models.

Expected limit using SR1 for models with direct stop pair production and an unpolarized stop (and bino LSP).

Expected limit using SR1 for models with direct stop pair production with $\tilde{t}_1=\tilde{t}_L$ (and bino LSP).

Expected limit using SR1 for models with direct stop pair production with $\tilde{t}_1\sim\tilde{t}_R$ (and bino LSP).

Observed limit using SR1 for models with direct stop pair production and an unpolarized stop (and bino LSP).

Observed limit using SR1 for models with direct stop pair production with $\tilde{t}_1=\tilde{t}_L$ (and bino LSP).

Observed limit using SR1 for models with direct stop pair production with $\tilde{t}_1\sim\tilde{t}_R$ (and bino LSP).

Expected limit using SR2 for models with direct stop pair production and an unpolarized stop (and bino LSP).

Expected limit using SR2 for models with direct stop pair production with $\tilde{t}_1=\tilde{t}_L$ (and bino LSP).

Expected limit using SR2 for models with direct stop pair production with $\tilde{t}_1\sim\tilde{t}_R$ (and bino LSP).

Observed limit using SR2 for models with direct stop pair production and an unpolarized stop (and bino LSP).

Observed limit using SR2 for models with direct stop pair production with $\tilde{t}_1=\tilde{t}_L$ (and bino LSP).

Observed limit using SR2 for models with direct stop pair production with $\tilde{t}_1\sim\tilde{t}_R$ (and bino LSP).

Expected limit using SR1+SR2 (best expected) for models with direct stop pair production and an unpolarized stop (and bino LSP).

Expected limit using SR1+SR2 (best expected) for models with direct stop pair production with $\tilde{t}_1=\tilde{t}_L$ (and bino LSP).

Expected limit using SR1+SR2 (best expected) for models with direct stop pair production with $\tilde{t}_1\sim\tilde{t}_R$ (and bino LSP).

Observed limit using SR1+SR2 (best expected) for models with direct stop pair production and an unpolarized stop (and bino LSP).

Observed limit using SR1+SR2 (best expected) for models with direct stop pair production with $\tilde{t}_1=\tilde{t}_L$ (and bino LSP).

Observed limit using SR1+SR2 (best expected) for models with direct stop pair production with $\tilde{t}_1\sim\tilde{t}_R$ (and bino LSP).

Acceptance for SR1 in the gluino-mediated stop models. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance for SR1 in the direct stop pair production. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance for SR2 in the gluino-mediated stop models. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance for SR2 in the direct stop pair production. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance for SR3 in the gluino-mediated stop models. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance for SR3 in the direct stop pair production. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Efficiency for SR1 in the gluino-mediated stop models. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency for SR1 in the direct stop pair production. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency for SR2 in the gluino-mediated stop models. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency for SR2 in the direct stop pair production. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency for SR3 in the gluino-mediated stop models. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency for SR3 in the direct stop pair production. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Despite listing this as an exclusive final state (as there must be at least one b-jets), there is no explicit selection on the presence of additional light-flavour jets. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 300, 500 and 800 GeV and $\tan\beta$ = 10 in the hMSSM scenario are also provided.

Observed and predicted mTtot distribution for the b-inclusive selection in the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. In the paper, the first bin is cut off at 60 GeV for aesthetics but contains underflows down to 50 GeV as in the HepData table. The last bin includes overflows. The prediction for a SSM Zprime with masses of 1500, 2000 and 2500 GeV are also provided.

Observed and predicted mTtot distribution for the b-inclusive selection in the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The prediction for a SSM Zprime with masses of 1500, 2000 and 2500 GeV are also provided.

Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.

Observed and expected 95% CL upper limits on the Drell Yan production cross section times ditau branching fraction as a function of the Zprime boson mass.

Observed and expected 95% CL upper limits on the Higgs boson production cross section times ditau branching fraction as a function of the boson mass and the relative strength of the b-associated production.

Ratio of the 95% CL upper limits on the production cross section times branching fraction for alternate Zprime models with respect to the SSM, both observed and expected are shown.

Acceptance, acceptance times efficiency and b-tag category fraction for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.

Acceptance, acceptance times efficiency and b-tag category fraction for a scalar boson produced by b-associated production as a function of the scalar boson mass.

Acceptance and acceptance times efficiency for a heavy gauge boson produced by Drell Yan as a function of the gauge boson mass.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the boson mass.

The observed and expected $E_T^{miss}$ distribution in the dimuon SR-Z. The negigible estimated contribution from Z+jets is omitted in these distributions. The last bin contains the overflow.

The observed and expected dielectron invariant mass distribution in SR-loose. The last bin contains the overflow.

The observed and expected dimuon invariant mass distribution in SR-loose. The last bin contains the overflow.

The observed and expected dielectron invariant mass distribution in the two-jet $b$-veto SR. The last bin contains the overflow.

The observed and expected dimuon invariant mass distribution in the two-jet $b$-veto SR. The last bin contains the overflow.

The observed and expected dielectron invariant mass distribution in the four jet b-veto SR. The last bin contains the overflow.

The observed and expected dimuon invariant mass distribution in the four-jet $b$-veto SR. The last bin contains the overflow.

The observed and expected dielectron invariant mass distribution in the two-jet $b$-tag SR. The last bin contains the overflow.

The observed and expected dimuon invariant mass distribution in two-jet $b$-tag SR. The last bin contains the overflow.

The observed and expected dielectron invariant mass distribution in the four-jet $b$-tag SR. The last bin contains the overflow.

The observed and expected dimuon invariant mass distribution in the four-jet $b$-tag SR. The last bin contains the overflow.

Expected 95% exclusion contour for the GGM model with $\tan(\beta)=1.5$ in SR-Z.

Observed 95% exclusion contour for the GGM model with $\tan(\beta)=1.5$ in SR-Z.

Expected 95% exclusion contour for the GGM model with $\tan(\beta)=30$ in SR-Z.

Observed 95% exclusion contour for the GGM model with $\tan(\beta)=30$ in SR-Z.

Expected 95% exclusion contour for the two-step first- and second-generation squark simplified model with sleptons in the two-jet $b$-veto SR.

Observed 95% exclusion contour for the two-step first- and second-generation squark simplified model with sleptons in the two-jet $b$-veto SR.

Expected 95% exclusion contour for the two-step gluino simplified model with sleptons in the four-jet $b$-veto SR.

Observed 95% exclusion contour for the two-step gluino simplified model with sleptons in the four-jet $b$-veto SR.

Number of generated events in the two-step gluino simplified model with sleptons.

Production cross-section in the two-step gluino simplified model with sleptons.

Number of generated events in the two-step first- and second-generation squark simplified model with sleptons.

Production cross-section in the two-step first- and second-generation squark simplified model with sleptons.

Number of generated events in the GGM model with $\tan(\beta)=1.5$.

Production cross-section in the GGM model with $\tan(\beta)=1.5$.

Number of generated events in the GGM model with $\tan(\beta)=30$.

Production cross-section in the GGM model with $\tan(\beta)=30$.

Total experimental uncertainty [%] for the two-step gluino simplified model with sleptons.

Total experimental uncertainty [%] for the GGM model with $\tan(\beta)=1.5$.

Total experimental uncertainty for the GGM model with $\tan(\beta)=30$.

Signal acceptance for the GGM model with $\tan(\beta)=1.5$ in the combined electron and muon SR-Z.

Signal acceptance for the GGM model with $\tan(\beta)=30$ in the combined electron and muon SR-Z.

Signal efficiency for the GGM model with $\tan(\beta)=1.5$ in the dielectron SR-Z.

Signal efficiency for the GGM model with $\tan(\beta)=30$ in the dielectron SR-Z.

Signal efficiency for the GGM model with $\tan(\beta)=1.5$ in the dimuon SR-Z.

Signal efficiency for the GGM model with $\tan(\beta)=30$ in the dimuon SR-Z.

Signal efficiency for the GGM model with $\tan(\beta)=1.5$ in the electron and muon combined SR-Z.

Signal efficiency for the GGM model with $\tan(\beta)=30$ in the the electron and muon combined SR-Z.

Signal acceptance for the two-step first- and second-generation squarks simplified model with sleptons in the two-jet $b$-veto SR.

Signal acceptance for the two-step gluino simplified model with sleptons in the four-jet $b$-veto SR.

Signal efficiency for the two-step first- and second-generation squarks simplified model with sleptons in the two-jet $b$-veto SR.

Signal efficiency for the two-step gluino simplified model with sleptons in the four-jet $b$-veto SR.

Upper limits on the signal cross-section at 95% CL for the GGM model with $\tan(\beta)=1.5$.

Observed CL$_{\text{S}}$ for the GGM model with $\tan(\beta)=1.5$.

Expected CL$_{\text{S}}$ for the GGM model with $\tan(\beta)=1.5$.

Upper limits on the signal cross-section at 95% CL for the GGM model with $\tan(\beta)=30$.

Observed CL$_{\text{S}}$ for the GGM model with $\tan(\beta)=30$.

Expected CL$_{\text{S}}$ for the GGM model with $\tan(\beta)=30$.

Upper limits on the signal stength at 95% CL for the two-step first- and second-generation squark simplified model with sleptons. The excluded signal strength is defined as the ratio of the observed excluded production cross section to the expected production cross section calculated at NLO+NLL.

Upper limits on the signal stength at 95% CL for the two-step gluino simplified model with sleptons. The excluded signal strength is defined as the ratio of the observed excluded production cross section to the expected production cross section calculated at NLO+NLL.

Observed CL$_{\text{S}}$ for the two-step first- and second-generation squark simplified model with sleptons.

Expected CL$_{\text{S}}$ for the two-step first- and second-generation squark simplified model with sleptons.

Observed CL$_{\text{S}}$ for the two-step gluino simplified model with sleptons.

Expected CL$_{\text{S}}$ for the two-step gluino simplified model with sleptons.

Cutflow table for three benchmark signal points in SR-Z for the $ee$ and $\mu\mu$ channels separately. The three signal points are taken from the $\tan\beta = 1.5$ grid. 100000 events were generated for each of these points. Shown here are both the unweighted number of events and the number of events normalised to 20.3 fb$^{-1}$. The total experimental systematic uncertainty on the signal yields is indicated at the last cut, along with the corresponding observed and expected $CL_S$ values.

Cutflow table for three benchmark signal points in the two jet b-veto SR of the off-$Z$ search for the $ee$ and $\mu\mu$ channels separately. Shown here are both the unweighted number of events and the number of events normalised to 20.3$^{-1}$. Except for the last two rows indicating the dilepton mass requirements, quoted event yields include all requirements from the top of the table down to the given row.

Cutflow table for three benchmark signal points in the four jet b-veto SR of the off-$Z$ search for the $ee$ and $\mu\mu$ channels separately. Shown here are both the unweighted number of events and the number of events normalised to 20.3 fb$^{-1}$. Except for the last two rows indicating the dilepton mass requirements, quoted event yields include all requirements from the top of the table down to the given row.

Efficiency for the calorimetric MET>80 GeV trigger as a function of the metastable R-hadron mass. The R-hadron decays to g/qq plus neutralino of mass = m(gluino) - 100 GeV with a lifetime of 1 ns.

Efficiency for the calorimetric MET>80 GeV trigger as a function of the metastable R-hadron mass. The R-hadron decays to g/qq plus neutralino of mass 100 GeV with a lifetime of 1 ns.

Efficiency for the calorimetric MET>80 GeV trigger as a function of the stable chargino mass.

Total selection efficiency as a function of the stable R-hadron mass.

Total selection efficiency as a function of the metastable R-hadron mass. The R-hadron decays to g/qq plus neutralino of mass 100 GeV with a lifetime of 10 ns.

Total selection efficiency as a function of the metastable R-hadron mass. The R-hadron decays to g/qq plus neutralino of mass = m(gluino) - 100 GeV with a lifetime of 10 ns.

Total selection efficiency as a function of the metastable R-hadron mass. The R-hadron decays to g/qq plus neutralino of mass 100 GeV with a lifetime of 1 ns.

Total selection efficiency as a function of the stable chargino mass.

Ionisation distribution of all the CR2 tracks, and those not matched to a reconstructed muon. The two distributions are normalised to their total number of entries.

Distribution of the mass of selected candidates, derived from the specific ionisation loss, for an example of gluino R-hadron signal, for searches for stable particles. The signal distributions are stacked on the expected background, and a narrower binning is used for them to allow the signal shape to be seen more clearly. The number of signal events is that expected according to the theoretical cross sections.

Distribution of the mass of selected candidates, derived from the specific ionisation loss, for one example of chargino signal, for searches for stable particles. The signal distributions are stacked on the expected background, and a narrower binning is used for them to allow the signal shape to be seen more clearly. The number of signal events is that expected according to the theoretical cross sections.

Distribution of the mass of selected candidates, derived from the specific ionisation loss, for background and data, for searches for stable particles. The expected background is shown with its total uncertainty (sum in quadrature of statistical, normalisation and systematic errors).

Distribution of the mass of selected candidates, derived from the specific ionisation loss, for an example of gluino R-hadron signal, for searches for metastable particles. The signal distributions are stacked on the expected background, and a narrower binning is used for them to allow the signal shape to be seen more clearly. The number of signal events is that expected according to the theoretical cross sections.

Distribution of the mass of selected candidates, derived from the specific ionisation loss, for an example of chargino signal, for searches for metastable particles. The signal distributions are stacked on the expected background, and a narrower binning is used for them to allow the signal shape to be seen more clearly. The number of signal events is that expected according to the theoretical cross sections.

Distribution of the mass of selected candidates, derived from the specific ionisation loss, for background and data. The expected background is shown with its total uncertainty (sum in quadrature of statistical, normalisation and systematic errors).

Theoretical values for the cross section of gluino pairs production with their uncertainty.

Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into g/qq plus a light neutralino of mass 100 GeV, in the background-only case, with its 1 sigma band.

Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into g/qq plus a light neutralino of mass 100 GeV.

Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into g/qq plus a heavy neutralino of mass(gluino) - 100 GeV, in the background-only case, with its 1 sigma band.

Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into g/qq plus a heavy neutralino of mass(gluino) - 100 GeV.

The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section.

The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section, plus 1 experimental sigma.

The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section, minus 1 experimental sigma.

The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section.

The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section minus its uncertainty.

The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section plus its uncertainty.

The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section.

The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section, plus 1 experimental sigma.

The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section, minus 1 experimental sigma.

The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section.

The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section minus its uncertainty.

The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section plus its uncertainty.

Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into tt plus a light neutralino of mass 100 GeV, in the background-only case, with its 1 sigma band.

Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into tt plus a light neutralino of mass 100 GeV.

Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into tt plus a heavy neutralino of mass(gluino) - 100 GeV, in the background-only case, with its 1 sigma band.

Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into tt plus a heavy neutralino of mass(gluino) - 100 GeV.

The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section.

The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section, plus 1 experimental sigma.

The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section, minus 1 experimental sigma.

The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section.

The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section minus its uncertainty.

The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section plus its uncertainty.

The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section.

The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section, plus 1 experimental sigma.

The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section, minus 1 experimental sigma.

The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section.

The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section minus its uncertainty.

The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section plus its uncertainty.

Theoretical values for the production cross section of charginos or chargino/neutralino pairs, with their uncertainty.

Expected upper limits on the production cross section as a function of mass for metastable charginos, with lifetime tau =1.0 ns, decaying into neutralino + pion, in the background-only case, with its 1 sigma band.

Observed 95 PCT upper limits on the production cross section as a function of mass for metastable charginos, with lifetime tau =1.0 ns, decaying into neutralino + pion.

The expected excluded range of lifetimes as a function of chargino mass for charginos decaying into neutralino plus pion, with respect to the nominal theoretical cross section.

The expected excluded range of lifetimes as a function of chargino mass for charginos decaying into neutralino plus pion, with respect to the nominal theoretical cross section, plus 1 experimental sigma.

The expected excluded range of lifetimes as a function of chargino mass for charginos decaying into neutralino plus pion, with respect to the nominal theoretical cross section, minus 1 experimental sigma.

The observed excluded range of lifetimes as a function of chargino mass for charginos decaying into neutralino plus pion, with respect to the nominal theoretical cross section.

The observed excluded range of lifetimes as a function of chargino mass for charginos decaying into neutralino plus pion, with respect to the nominal theoretical cross section minus its uncertainty.

The observed excluded range of lifetimes as a function of gluino mass for chargino mass for charginos decaying into neutralino plus pion, with respect to the nominal theoretical cross section plus its uncertainty.

dEdx ionization for data, 1 TeV gluino R-hadrons stable and decaying in 100 GeV neutralinos with a 10 ns lifetime and for charginos of 350 GeV. Tracks that fulfil all the requirements up to including the High-m_T (see Tab.1 in the paper) are considered at this stage and normalised to an integrated luminosity of 18.4 fb^-1.

Expected upper limits on the production cross section as a function of mass for stable gluino R-hadrons, in case of background only, with its 1 sigma band.

Observed 95 PCT upper limits on the production cross section as a function of mass for stable gluino R-hadrons.

Theoretical values for the cross section of squark pairs production with their uncertainty.

Expected upper limits on the production cross section as a function of mass for stable sbottom R-hadrons, in case of background only, with its 1 sigma band.

Observed 95 PCT upper limits on the production cross section as a function of mass for stable sbottom $R$-hadrons. Cross section IN PB.

Expected upper limits on the production cross section as a function of mass for stop R-hadrons, in case of background only, with its 1 sigma band.

Observed 95 PCT upper limits on the production cross section as a function of mass for stop R-hadrons.

Expected upper limits on the production cross section as a function of mass for stable charginos, in case of background only, with its 1 sigma band.

Observed 95 PCT upper limits on the production cross section as a function of mass for stable charginos.

Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to g/qq plus a light neutralino of mass 100 GeV.

Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to g/qq plus a light neutralino of mass 100 GeV.

Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV.

Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV.

Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to tt plus a light neutralino of mass 100 GeV.

Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to tt plus a light neutralino of mass 100 GeV.

Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to tt plus a heavy neutralino of mass = m(gluino) - 100 GeV.

Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to tt plus a heavy neutralino of mass = m(gluino) - 100 GeV.

Expected upper limits on the production cross section as a function of mass for metastable charginos, with lifetime tau =15 ns, decaying to neutralino and pion, in case of background only, with its 1 sigma band.

Observed 95 PCT upper limits on the production cross section as a function of mass for metastable charginos, with lifetime tau =15 ns, decaying to neutralino and pion, in case of background only, with its 1 sigma band.

Distribution of the transverse mass of the $W$-candidate $m_{\rm T}^{W}$ for the one lepton and two $b$-jets channel in SRlbb-1 and SRlbb-2, $m_{bb}$ sidebands. The background histograms are obtained from the background-only fit, and their uncertainty represents the total background uncertainty after the fit. The last bin includes overflow.

Distribution of the number of $b$-jets for the one lepton and two $b$-jets channel in SRlbb-1 and SRlbb-2 without the b-jet multiplicity requirement, central $m_{bb}$ bin. The background histograms are obtained from the background-only fit, and their uncertainty represents the total background uncertainty after the fit.

Distribution of the invariant mass of the $b$-jets $m_{bb}$ for the one lepton and two $b$-jets channel in the SRlbb-1 and SRlbb-2. The background histograms are obtained from the background-only fit, and their uncertainty represents the total background uncertainty after the fit.

Distribution of missing transverse momentum $E_{\rm T}^{\rm miss}$ in the one lepton and two photons signal regions SR$\ell\gamma\gamma$-1 and SR$\ell\gamma\gamma$-2 for the Higgs-mass window ($120\lt m_{\gamma\gamma} \lt 130$ GeV). The final column (background) is a simulation-based cross check. The contributions from non-Higgs backgrounds are scaled by 10 GeV / 50 GeV = 0.2 from the $m_{\gamma\gamma}$ sideband ($100 \lt m_{\gamma\gamma} \lt 120$ GeV and $130 \lt m_{\gamma\gamma} \lt 160$ GeV) into the Higgs-mass window. The last bin includes overflow. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

Distribution of the azimuth difference between the $W$ and Higgs boson candidates $\Delta\phi(W,h)$ in the one lepton and two photons signal regions SR$\ell\gamma\gamma$-1 and SR$\ell\gamma\gamma$-2 for the Higgs-mass window ($120\lt m_{\gamma\gamma} \lt 130$ GeV). The final column (background) is a simulation-based cross check. The contributions from non-Higgs backgrounds are scaled by 10 GeV / 50 GeV = 0.2 from the $m_{\gamma\gamma}$ sideband ($100 \lt m_{\gamma\gamma} \lt 120$ GeV and $130 \lt m_{\gamma\gamma} \lt 160$ GeV) into the Higgs-mass window. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

Distribution of the transverse mass of the $W$ and photon system $m_{\rm{T}}^{W\gamma_1}$ in the one lepton and two photons signal regions SR$\ell\gamma\gamma$-1 and SR$\ell\gamma\gamma$-2 for the Higgs-mass window ($120\lt m_{\gamma\gamma} \lt 130$ GeV). The final column (background) is a simulation-based cross check. The contributions from non-Higgs backgrounds are scaled by 10 GeV / 50 GeV = 0.2 from the $m_{\gamma\gamma}$ sideband ($100 \lt m_{\gamma\gamma} \lt 120$ GeV and $130 \lt m_{\gamma\gamma} \lt 160$ GeV) into the Higgs-mass window. The last bin includes overflow. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

Distribution of the transverse mass of the $W$ and photon system $m_{\rm{T}}^{W\gamma_2}$ in the one lepton and two photons signal regions SR$\ell\gamma\gamma$-1 and SR$\ell\gamma\gamma$-2 for the Higgs-mass window ($120\lt m_{\gamma\gamma} \lt 130$ GeV). The final column (background) is a simulation-based cross check. The contributions from non-Higgs backgrounds are scaled by 10 GeV / 50 GeV = 0.2 from the $m_{\gamma\gamma}$ sideband ($100 \lt m_{\gamma\gamma} \lt 120$ GeV and $130 \lt m_{\gamma\gamma} \lt 160$ GeV) into the Higgs-mass window. The last bin includes overflow. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

Results of the background-only fit to the diphoton invariant mass, $m_{\gamma\gamma}$, distribution in the one lepton and two photons signal region SR$l\gamma\gamma$-1. The contributions from SM Higgs boson production are constrained to the MC prediction and associated systematic uncertainties. The fit is performed on events with 100 GeV $ \lt m_{\gamma\gamma} \lt $ 160 GeV, with events in SR$l\gamma\gamma$-1 or SR$l\gamma\gamma$-2 in the Higgs-mass window (120 GeV $\le m_{\gamma\gamma} \le$ 130 GeV) excluded from the fit.

Results of the background-only fit to the diphoton invariant mass, $m_{\gamma\gamma}$, distribution in the one lepton and two photons signal region SR$l\gamma\gamma$-2. The contributions from SM Higgs boson production are constrained to the MC prediction and associated systematic uncertainties. The fit is performed on events with 100 GeV $ \lt m_{\gamma\gamma} \lt $ 160 GeV, with events in SR$l\gamma\gamma$-1 or SR$l\gamma\gamma$-2 in the Higgs-mass window (120 GeV $\le m_{\gamma\gamma} \le$ 130 GeV) excluded from the fit.

Results of the background-only fit to the diphoton invariant mass, $m_{\gamma\gamma}$, distribution in the one lepton and two photons validation region VR$l\gamma\gamma$-1. The contributions from SM Higgs boson production are constrained to the MC prediction and associated systematic uncertainties. The fit is performed on events with 100 GeV $ \lt m_{\gamma\gamma} \lt $ 160 GeV, with events in SR$l\gamma\gamma$-1 or SR$l\gamma\gamma$-2 in the Higgs-mass window (120 GeV $\le m_{\gamma\gamma} \le$ 130 GeV) excluded from the fit.

Results of the background-only fit to the diphoton invariant mass, $m_{\gamma\gamma}$, distribution in the one lepton and two photons validation region VR$l\gamma\gamma$-2. The contributions from SM Higgs boson production are constrained to the MC prediction and associated systematic uncertainties. The fit is performed on events with 100 GeV $ \lt m_{\gamma\gamma} \lt $ 160 GeV, with events in SR$l\gamma\gamma$-1 or SR$l\gamma\gamma$-2 in the Higgs-mass window (120 GeV $\le m_{\gamma\gamma} \le$ 130 GeV) excluded from the fit.

Distribution of effective mass $m_{\rm eff}$ in the validation region of the same-sign $e\mu$ channel. This validation region is defined by requiring one, two, or three jets, and reversing the $m_{lj}$, $m_{ljj}$ criteria. The distribution of a signal hypothesis is also shown.

Distribution of effective mass $m_{\rm eff}$ for the same-sign dilepton channel in the signal regions with one jet SR$ll$-1. SR$ll$-1 is the sum of SR$ee$-1, SR$e\mu$-1, and SR$\mu\mu$-1. All selection criteria are applied, except for the one on $m_{\rm eff}$. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(130,0)$ GeV. The last bin includes overflow.

Distribution of effective mass $m_{\rm eff}$ for the same-sign dilepton channel in the signal regions with two or three jets SR$ll$-2. SR$ll$-2 is the sum of SR$ee$-2, SR$e\mu$-2, and SR$\mu\mu$-2. All selection criteria are applied, except for the one on $m_{\rm eff}$. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(130,0)$ GeV. The last bin includes overflow.

Distribution of largest transverse mass $m_{\rm T}^{\rm max}$ for the same-sign dilepton channel in the signal regions with one jet SR$ll$-1. SR$ll$-1 is the sum of SR$ee$-1, SR$e\mu$-1, and SR$\mu\mu$-1. All selection criteria are applied, except for the one on $m_{\rm T}^{\rm max}$. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(130,0)$ GeV. The last bin includes overflow.

Distribution of largest transverse mass $m_{\rm T}^{\rm max}$ for the same-sign dilepton channel in the signal regions with two or three jets SR$ll$-2. SR$ll$-2 is the sum of SR$ee$-2, SR$e\mu$-2, and SR$\mu\mu$-2. All selection criteria are applied, except for the one on $m_{\rm T}^{\rm max}$. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(130,0)$ GeV. The last bin includes overflow.

Distribution of invariant mass of lepton and jet $m_{lj}$ for the same-sign dilepton channel in the signal regions with one jet SR$ll$-1. SR$ll$-1 is the sum of SR$ee$-1, SR$e\mu$-1, and SR$\mu\mu$-1. All selection criteria are applied, except for the one on $m_{lj}$. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(130,0)$ GeV. The last bin includes overflow.

Distribution of invariant mass of lepton and di-jet $m_{ljj}$ for the same-sign dilepton channel in the signal regions with two or three jets SR$ll$-2. SR$ll$-2 is the sum of SR$ee$-2, SR$e\mu$-2, and SR$\mu\mu$-2. All selection criteria are applied, except for the one on $m_{ljj}$. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(130,0)$ GeV. The last bin includes overflow.

One lepton and two $b$-jets channel: observed and expected 95% CL upper limits on the cross section normalised by the simplified model prediction as a function of the common mass $m_{\tilde{\chi}_1^\pm \tilde{\chi}^0_2}$ for $m_{\tilde{\chi}^0_1}=0$.

One lepton and two photons channel: observed and expected 95% CL upper limits on the cross section normalised by the simplified model prediction as a function of the common mass $m_{\tilde{\chi}_1^\pm \tilde{\chi}^0_2}$ for $m_{\tilde{\chi}^0_1}=0$.

Same-sign dilepton channel: observed and expected 95% CL upper limits on the cross section normalised by the simplified model prediction as a function of the common mass $m_{\tilde{\chi}_1^\pm \tilde{\chi}^0_2}$ for $m_{\tilde{\chi}^0_1}=0$.

Combination: observed and expected 95% CL upper limits on the cross section normalised by the simplified model prediction as a function of the common mass $m_{\tilde{\chi}_1^\pm \tilde{\chi}^0_2}$ for $m_{\tilde{\chi}^0_1}=0$. This combination is obtained using the result from the ATLAS three-lepton search, J. High Energy Phys. 04 (2014) 169, in addition to the three channels reported in this paper.

One lepton and two b-jets channel: Expected 95% CL exclusion contour for chargino neutralino production via Wh.

One lepton and two b-jets channel: Observed 95% CL exclusion contour for chargino neutralino production via Wh.

One lepton and two photons channel: Expected 95% CL exclusion contour for chargino neutralino production via Wh.

One lepton and two photons channel: Observed 95% CL exclusion contour for chargino neutralino production via Wh.

Same-sign dilepton channel: Expected 95% CL exclusion contour for chargino neutralino production via Wh.

Same-sign dilepton channel: Observed 95% CL exclusion contour for chargino neutralino production via Wh.

Combination: Expected 95% CL exclusion contour for chargino neutralino production via Wh.

Combination: Observed 95% CL exclusion contour for chargino neutralino production via Wh.

Combination: excluded model cross-section at 95% CL IN PB.

Acceptance SR$\ell\gamma\gamma$-1.

Acceptance SR$\ell\gamma\gamma$-2.

Efficiency SR$\ell\gamma\gamma$-1.

Efficiency SR$\ell\gamma\gamma$-2.

$m_{\gamma\gamma}$ distribution in the SR$l\gamma\gamma$-1 region for the full $m_{\gamma\gamma}$ window. The last column (background) is from a simulation-based cross check. $Z\gamma$ events, with $Z\rightarrow{ee}$ and one electron mis-identified as a photon, are included in the $Z\gamma(\gamma)$ background. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

$m_{\gamma\gamma}$ distribution in the SR$l\gamma\gamma$-2 region for the full $m_{\gamma\gamma}$ window. The last column (background) is from a simulation-based cross check. $Z\gamma$ events, with $Z\rightarrow{ee}$ and one electron mis-identified as a photon, are included in the $Z\gamma(\gamma)$ background. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

$m_{\gamma\gamma}$ distribution in the VR$l\gamma\gamma$-1 region for the full $m_{\gamma\gamma}$ window. The last column (background) is from a simulation-based cross check. $Z\gamma$ events, with $Z\rightarrow{ee}$ and one electron mis-identified as a photon, are included in the $Z\gamma(\gamma)$ background. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

$m_{\gamma\gamma}$ distribution in the VR$l\gamma\gamma$-2 region for the full $m_{\gamma\gamma}$ window. The last column (background) is from a simulation-based cross check. $Z\gamma$ events, with $Z\rightarrow{ee}$ and one electron mis-identified as a photon, are included in the $Z\gamma(\gamma)$ background. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

Acceptance for SRlbb-1, central $m_{bb}$ bin.

Acceptance for SRlbb-1, $m_{bb}$ sideband.

Acceptance for SRlbb-2, central $m_{bb}$ bin.

Acceptance for SRlbb-2, $m_{bb}$ sideband.

Efficiency for SRlbb-1, central $m_{bb}$ bin.

Efficiency for SRlbb-1, $m_{bb}$ sideband.

Efficiency for SRlbb-2, central $m_{bb}$ bin.

Efficiency for SRlbb-2, $m_{bb}$ sideband.

Acceptance for the same-sign $ee$ channel with one jet.

Acceptance for the same-sign $ee$ channel with two or three jets.

Acceptance for the same-sign $e\mu$ channel with one jet.

Acceptance for the same-sign $e\mu$ channel with two or three jets.

Acceptance for the same-sign $\mu\mu$ channel with one jet.

Acceptance for the same-sign $\mu\mu$ channel with two or three jets.

Efficiency for the same-sign $ee$ channel with one jet.

Efficiency for the same-sign $ee$ channel with two or three jets.

Efficiency for the same-sign $e\mu$ channel with one jet.

Efficiency for the same-sign $e\mu$ channel with two or three jets.

Efficiency for the same-sign $\mu\mu$ channel with one jet.

Efficiency for the same-sign $\mu\mu$ channel with two or three jets.

Number of data events (20.3 fb$^{-1}$), number of predicted events from the fit, statistical uncertainty on the fit, systematic uncertainty on the choice of control region, and on the choice of fit function versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ lower bin edge for inclusive jet multiplicity $N_{\textrm{Jet}} \geq 6$. The total uncertainty is obtained by adding the three uncertainties linearly.

Number of data events (20.3 fb$^{-1}$), number of predicted events from the fit, statistical uncertainty on the fit, systematic uncertainty on the choice of control region, and on the choice of fit function versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ lower bin edge for inclusive jet multiplicity $N_{\textrm{Jet}} \geq 7$. The total uncertainty is obtained by adding the three uncertainties linearly.

Number of data events (20.3 fb$^{-1}$), number of predicted events from the fit, statistical uncertainty on the fit, systematic uncertainty on the choice of control region, and on the choice of fit function versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ lower bin edge for inclusive jet multiplicity $N_{\textrm{Jet}} \geq 8$. The total uncertainty is obtained by adding the three uncertainties linearly.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 3$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 4$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 5$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 6$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 7$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 8$.

Mean reconstruction efficiencies $(\epsilon)$ and RMS of the reconstruction efficiencies for various black hole and string ball models.

The effective mass distribution in VR2Z.

The ETmiss distribution in SR0noZa.

The effective mass distribution in SR0noZa.

The ETmiss distribution in SR1noZa.

The effective mass distribution in SR1noZa.

The ETmiss distribution in SR2noZa.

The effective mass distribution in SR2noZa.

The ETmiss distribution in SR0noZb.

The effective mass distribution in SR0noZb.

The ETmiss distribution in SR1noZb.

The effective mass distribution in SR1noZb.

The ETmiss distribution in SR2noZb.

The effective mass distribution in SR2noZb.

The ETmiss distribution in SR0Z.

The effective mass distribution in SR0Z.

The ETmiss distribution in SR1Z.

The effective mass distribution in SR1Z.

The ETmiss distribution in SR2Z.

The effective mass distribution in SR2Z.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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