Multiplicity of additional jets with pt>80GeV

Transverse momentum of leading b-jet

Transverse momentum of sub-leading b-jet

Transverse momentum of leading (highest pt) additional jet

Measured Gap fraction within |y|<0.8 as a function of Q0

Measured Gap fraction within 0.8<|y|<1.5 as a function of Q0

Measured Gap fraction within 1.5<|y|<2.1 as a function of Q0

Measured Gap fraction within |y|<2.1 as a function of Q0

Measured Gap fraction within |y|<2.1 as a function of Q0 for invariant mass region m_{emubb} < 300GeV

Measured Gap fraction within |y|<2.1 as a function of Q0 for invariant mass region 300 GeV < m_{emubb} < 425GeV

Measured Gap fraction within |y|<2.1 as a function of Q0 for invariant mass region 425 GeV< m_{emubb} < 600GeV

Measured Gap fraction within |y|<2.1 as a function of Q0 for invariant mass region m_{emubb} > 600GeV

Measured Gap fraction within |y|<0.8 as a function of QSUM

Measured Gap fraction within 0.8<|y|<1.5 as a function of QSUM

Measured Gap fraction within 1.5<|y|<2.1 as a function of QSUM

Measured Gap fraction within |y|<2.1 as a function of QSUM

Measured Gap fraction within |y|<2.1 as a function of QSUM for invariant mass region m_{emubb} < 300GeV

Measured Gap fraction within |y|<2.1 as a function of QSUM for invariant mass region 300 GeV < m_{emubb} < 425 GeV

Measured Gap fraction within |y|<2.1 as a function of QSUM for invariant mass region 425GeV< m_{emubb} < 600GeV

Measured Gap fraction within |y|<2.1 as a function of QSUM for invariant mass region m_{emubb} > 600GeV

Fit results in SRt1, SRt2 and SRt3 for an integrated luminosity of $36.1 fb^{-1}$. The background normalisation parameters are obtained from the background-only fit in the CRs and are applied to the SRs. Small backgrounds are indicated as Others. Benchmark signal models yields are given for each SR. The uncertainties on the yields include all systematic uncertainties.

95% CL upper limits on the visible cross-section ($\langle\epsilon\mathcal{A}\sigma\rangle^{\rm obs}_{95}$) and on the number of BSM events ($S^{\rm obs}_{95}$ ). The third column ($S^{\rm exp}_{95}$) shows the 95% CL upper limit on the number of signal events, given the expected number (and $\pm 1\sigma$ excursions on the expectation) of background events. The last column indicates the discovery $p$-value ($p(s = 0)$) and Z (the number of equivalent Gaussian standard deviations).

Comparison of the data with the post-fit SM prediction of the $E_{\mathrm T}^{\mathrm{miss}}$ distribution in SRb1. The last bins include overflows, where applicable. All signal region requirements except the one on the distribution shown are applied. The signal region requirement on the distribution shown is indicated by an arrow. The bottom panel shows the ratio of the data over the prediction. The band includes all systematic uncertainties.

Comparison of the data with the post-fit SM prediction of the $\cos{\theta}^*_{bb}$ distribution in SRb2. The last bins include overflows, where applicable. All signal region requirements except the one on the distribution shown are applied. The signal region requirement on the distribution shown is indicated by an arrow. The bottom panel shows the ratio of the data over the prediction. The band includes all systematic uncertainties.

Comparison of the data with the post-fit SM prediction of the $m_{\mathrm T}^{\mathrm{b,min}}$ distribution in SRt1. The last bins include overflows, where applicable. All signal region requirements except the one on the distribution shown are applied. The signal region requirement on the distribution shown is indicated by an arrow. The bottom panel shows the ratio of the data over the prediction. The band includes all systematic uncertainties.

Comparison of the data with the post-fit SM prediction of the $E_{\mathrm T}^{\mathrm{miss,sig}}$ distribution in SRt2. The last bins include overflows, where applicable. All signal region requirements except the one on the distribution shown are applied. The signal region requirement on the distribution shown is indicated by an arrow. The bottom panel shows the ratio of the data over the prediction. The band includes all systematic uncertainties.

Comparison of the data with the post-fit SM prediction of the $\xi^{+}_{\ell\ell}$ distribution in SRt3. The last bins include overflows, where applicable. All signal region requirements except the one on the distribution shown are applied. The signal region requirement on the distribution shown is indicated by an arrow. The bottom panel shows the ratio of the data over the prediction. The band includes all systematic uncertainties.

Expected exclusion limits for colour-neutral scalar model in the SRb2 as a function of the mediator mass for a DM mass of 1 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$.

Observed exclusion limits for colour-neutral scalar model in SRb2 as a function of the mediator mass for a DM mass of 1 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$.

Expected exclusion limits for colour-neutral scalar model in the SRt1/SRt2 as a function of the mediator mass for a DM mass of 1 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$. To derive the results for the fully hadronic $t\bar{t}$ final state the region among SRt1 and SRt2 providing the best expected sensitivity is used.

Observed exclusion limits for colour-neutral scalar model in SRt1/SRt2 as a function of the mediator mass for a DM mass of 1 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$. To derive the results for the fully hadronic $t\bar{t}$ final state the region among SRt1 and SRt2 providing the best expected sensitivity is used.

Expected exclusion limits for colour-neutral scalar model in SRt3 as a function of the mediator mass for a DM mass of 1 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$.

Observed exclusion limits for colour-neutral scalar model in SRt3 as a function of the mediator mass for a DM mass of 1 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$.

Expected exclusion limits for colour-neutral pseudo-scalar model in SRb2 as a function of the mediator mass for a DM mass of 1 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$.

Observed exclusion limits for colour-neutral pseudo-scalar model in SRb2 as a function of the mediator mass for a DM mass of 1 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$.

Expected exclusion limits for colour-neutral pseudo-scalar model in SRt1/SRt2 as a function of the mediator mass for a DM mass of 1 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$. To derive the results for the fully hadronic $t\bar{t}$ final state the region among SRt1 and SRt2 providing the best expected sensitivity is used.

Observed exclusion limits for colour-neutral pseudo-scalar model in SRt1/SRt2 as a function of the mediator mass for a DM mass of 1 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$. To derive the results for the fully hadronic $t\bar{t}$ final state the region among SRt1 and SRt2 providing the best expected sensitivity is used.

Expected limits for colour-neutral pseudo-scalar model in SRt3 as a function of the mediator mass for a DM mass of 1 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$.

Observed exclusion limits for colour-neutral pseudo-scalar model in SRt3 as a function of the mediator mass for a DM mass of 1 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$.

Expected exclusion limits for colour-neutral scalar model in SRt1/SRt2 as a function of the DM mass for a mediator mass of 10 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$. To derive the results for the fully hadronic $t\bar{t}$ final state the region among SRt1 and SRt2 providing the best expected sensitivity is used.

Observed exclusion limits for colour-neutral scalar model in SRt1/SRt2 as a function of the DM mass for a mediator mass of 10 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$. To derive the results for the fully hadronic $t\bar{t}$ final state the region among SRt1 and SRt2 providing the best expected sensitivity is used.

Expected exclusion limits for colour-neutral scalar model in SRt3 as a function of the DM mass for a mediator mass of 10 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$.

Observed exclusion limits for colour-neutral scalar model in SRt3 as a function of the DM mass for a mediator mass of 10 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$.

Expected exclusion limits for colour-neutral pseudo-scalar model in SRt1/SRt2 as a function of the DM mass for a mediator mass of 10 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$. To derive the results for the fully hadronic $t\bar{t}$ final state the region among SRt1 and SRt2 providing the best expected sensitivity is used.

Observed exclusion limits for colour-neutral pseudo-scalar model in SRt1/SRt2 as a function of the DM mass for a mediator mass of 10 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$. To derive the results for the fully hadronic $t\bar{t}$ final state the region among SRt1 and SRt2 providing the best expected sensitivity is used.

Expected exclusion limits for colour-neutral pseudo-scalar model in SRt3 as a function of the DM mass for a mediator mass of 10 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$.

Observed xclusion limits for colour-neutral pseudo-scalar model in SRt3 as a function of the DM mass for a mediator mass of 10 GeV. The limits are calculated at 95% C.L. and are expressed in terms of the ratio of the excluded cross-section over the nominal cross-section for a coupling assumption of $g = g_\chi = g_\nu = 1$.

Comparison of the 90% CL limits on the spin-independent DM–nucleon cross-section versus mediator mass between these results and the direct-detection experiments, in the context of the colour-neutral simplified model with scalar mediator. The black line indicates the exclusion contour derived from the observed limits of SRt3. Values inside the contour are excluded.

Expected exclusion limits for colour-charged scalar mediators ($b$-FDM) as a function of the mediator and DM masses for $36.1fb^{-1}$ of data. The limits are calculated at 95% C.L for a coupling assumption $\lambda_b$ yielding the measured relic density.

Exclusion observed limits for colour-charged scalar mediators ($b-$FDM) as a function of the mediator and DM masses for $36.1fb^{-1}$ of data. The limits are calculated at 95% C.L for a coupling assumption $\lambda_b$ yielding the measured relic density.

Comparison of the data with the post-fit Monte Carlo prediction of sub leading jet $p_{T}$ in SRb1. The last bin includes overflows. The bottom panel shows the ratio of the data over the Monte Carlo prediction. The band includes all systematic uncertainties.

Comparison of the data with the post-fit Monte Carlo prediction of $H_{\mathrm T}^{ratio}$ distribution in SRb2. The last bin includes overflows. The bottom panel shows the ratio of the data over the Monte Carlo prediction. The band includes all systematic uncertainties.

Comparison of the data with the post-fit Monte Carlo prediction of $\Delta R_{bb}$ in SRt1. The last bin includes overflows. The bottom panel shows the ratio of the data over the Monte Carlo prediction. The band includes all systematic uncertainties.

Comparison of the data with the post-fit Monte Carlo prediction of $M_{\mathrm T}^{b,min}$ in SRt2. The last bin includes overflows. The bottom panel shows the ratio of the data over the Monte Carlo prediction. The band includes all systematic uncertainties.

Comparison of the data with the post-fit Monte Carlo prediction of $\Delta \phi_{boost}$ in SRt3. The last bin includes overflows. The bottom panel shows the ratio of the data over the Monte Carlo prediction. The band includes all systematic uncertainties.

Acceptance of the SRb1 selection of the $b$-FDM model signal samples

Efficiency of the SRb1 selection of the $b$-FDM model signal samples

Acceptance of the SRb2 selection of the colour-neutral simplified model samples with scalar mediator decaying into dark matter pairs produced in association with bottom-quark pairs.

Efficiency of the SRb2 selection to the colour-neutral simplified model samples with scalar mediator decaying into dark matter pairs produced in association with bottom-quark pairs

Efficiency of the SRb2 selection to the colour-neutral simplified model samples with pseudo-scalar mediator decaying into dark matter pairs produced in association with bottom-quark pairs

Acceptance of SRb2 selection to the colour-neutral simplified model samples with pseudo-scalar mediator decaying into dark matter pairs produced in association with bottom-quark pairs

Acceptance of the SRt2 selections to the color-neutral simplified model samples with scalar mediator decaying into dark matter pairs produced in association with top quarks.

Acceptance of the SRt1 selections to the color-neutral simplified model samples with scalar mediator decaying into dark matter pairs produced in association with top quarks.

Efficiency of the SRt2 selections to the color-neutral simplified model samples with scalar mediator decaying into dark matter pairs produced in association with top quarks.

Efficiency of the SRt1 selections to the color-neutral simplified model samples with scalar mediator decaying into dark matter pairs produced in association with top quarks.

Acceptance of the SRt2 selections to the color-neutral simplified model samples with pseudo-scalar mediator decaying into dark matter pairs produced in association with top quarks.

Acceptance of the SRt1 selections to the color-neutral simplified model samples with pseudo-scalar mediator decaying into dark matter pairs produced in association with top quarks.

Efficiency of the SRt2 selections to the color-neutral simplified model samples with pseudo-scalar mediator decaying into dark matter pairs produced in association with top quarks.

Efficiency of the SRt1 selections to the color-neutral simplified model samples with pseudo-scalar mediator decaying into dark matter pairs produced in association with top quarks.

Acceptance of the SRt3 selections to the color-neutral simplified model samples with scalar mediator decaying into dark matter pairs produced in association with top quarks.

Efficiency of the SRt3 selections to the color-neutral simplified model samples with scalar mediator decaying into dark matter pairs produced in association with top quarks.

Acceptance of the SRt3 selections to the color-neutral simplified model samples with pseudo-scalar mediator decaying into dark matter pairs produced in association with top quarks.

Efficiency of the SRt3 selections to the color-neutral simplified model samples with pseudo-scalar mediator decaying into dark matter pairs produced in association with top quarks.

Number of signal events selected at different stages of the SRb1 selections for the $b$-FDM benchmark model $m(\phi_b,\chi)=(1000,35)$GeV

Number of signal events selected at different stages of the SRb2 selections for the $b\bar{b} +\phi$ benchmark model $m(\phi,\chi)=(20,1)$GeV, $g=1$.

Number of signal events selected at different stages of the SRt1 selections for the $t \bar{t} +\phi$ benchmark model $m(\phi,\chi)=(20,1)$GeV, $g=1$.

Number of signal events selected at different stages of the SRt2 selections for the $t \bar{t} +\phi$ benchmark model $m(\phi,\chi)=(20,1)$GeV, $g=1$.

Number of signal events selected at different stages of the SRt1 selections for the $t \bar{t} +a$ benchmark model $m(a,\chi)=(20,1)$GeV, $g=1$.

Number of signal events selected at different stages of the SRt2 selections for the $t \bar{t} +a$ benchmark model $m(\phi,\chi)=(20,1)$GeV, $g=1$.

Number of signal events selected at different stages of the SRt3 selections for the $t \bar{t} +\phi$ benchmark model $m(\phi,\chi)=(20,1)$GeV, $g=1$.

Figure 2, right, subfigure b, Transverse mass distribution in the VBF top-quark control regions. For NWA signals, the "0" value means lack of statistics.

Figure 3, left, subfigure a, Transverse mass distribution in the quasi-inclusive ggF WW control regions. The "0" value means lack of statistics.

Figure 3, right, subfigure b, Transverse mass distribution in the quasi-inclusive VBF1Jet WW control regions. The "0" value means lack of statistics.

Figure 4, top left, subfigure a, post-fit distributions of the transverse mass mT in the ggF Signal region. The "0" value means lack of statistics.

Figure 4, top right, subfigure b, post-fit distributions of the transverse mass mT in the VBF1Jet Signal region. The "0" value means lack of statistics.

Figure 4, bottom, subfigure c, post-fit distributions of the transverse mass mT in the VBF2Jet Signal region. The "0" value means lack of statistics.

Figure 5, left, subfigur a, Upper limits at 95% CL on the Higgs boson production cross section times branching fraction in the evmuv channel, for ggF signals with narrow-width lineshape as a function of the signal mass.

Figure 5, right, subfigure b, Upper limits at 95% CL on the Higgs boson production cross section times branching fraction in the evmuv channel, for VBF signals with narrow-width lineshape as a function of the signal mass.

Figure 6, Upper limits at 95% CL on the total ggF and VBF Higgs boson production cross section times branching fraction in the evmuv channel, for a signal at 800 GeV as a function of the ggF cross section divided by the combined ggF and VBF production cross section.

Figure 9, top left, subfigure a, Upper limits at 95% CL on the Higgs boson production cross section times branching fraction for a signal with a width of 15% of the mass for the ggF production.

Figure 9, top right, subfigure b, Upper limits at 95% CL on the Higgs boson production cross section times branching fraction for a signal with a width of 15% of the mass for the VBF production.

Figure 10, left, subfigure a, Upper limits at 95% CL on the resonance production cross section times branching fraction for a GM signal.

Figure 11, left, subfigure a, Upper limits at 95% CL on the resonance production cross section times branching fraction for a HVT qqA signal.

Figure 11, right, subfigure b, Upper limits at 95% CL on the resonance production cross section times branching fraction for a HVT VBF signal.

Figure 12, bottom, subfigure c, Upper limits at 95% CL on the resonance production cross section times branching fraction for an EML spin-2 VBF signal.

Figure 12, top right, subfigure b, Upper limits at 95% CL on the resonance production cross section times branching fraction for a graviton signal with coupling parameter equals 0.5

Figure 12, top left, subfigure a, Upper limits at 95% CL on the resonance production cross section times branching fraction for a graviton signal with coupling parameter equals 1.0

Auxiliary material Figure 2e, Event selection efficiencies in the VBF2J event categories as a function of the signal mass for the ggF or qqA production. The "0" efficiency mass point means there's no such signal sample for the corresponding model.

Auxiliary material Figure 2f, Event selection efficiencies in the VBF2J event categories for different kinds of VBF signals production. The "0" efficiency mass point means there's no such signal sample for the corresponding model.

Auxiliary material Figure 2c, Event selection efficiencies in the VBF1J event categories as a function of the signal mass for the ggF or qqA production. The "0" efficiency mass point means there's no such signal sample for the corresponding model.

Auxiliary material Figure 2d, Event selection efficiencies in the VBF1J event categories for different kinds of VBF signals production. The "0" efficiency mass point means there's no such signal sample for the corresponding model.

Auxiliary material Figure 2a, Event selection efficiencies in the ggF event categories as a function of the signal mass for the ggF or qqA production. The "0" efficiency mass point means there's no such signal sample for the corresponding model.

Auxiliary material Figure 2b, Event selection efficiencies in the ggF event categories for different kinds of VBF signals production. The "0" efficiency mass point means there's no such signal sample for the corresponding model.

Auxiliary material Figure 6a, Upper limits at 95% CL on the Higgs production cross section times branching fraction in the evmuv channel, for a signal with a width of 5% of the mass for the ggF production.

Auxiliary material Figure 6c, Upper limits at 95% CL on the Higgs production cross section times branching fraction in the evmuv channel, for a signal with a width of 10% of the mass for the ggF production.

Auxiliary material Figure 6b, Upper limits at 95% CL on the Higgs production cross section times branching fraction in the evmuv channel, for a signal with a width of 5% of the mass for the VBF production.

Auxiliary material Figure 6d, Upper limits at 95% CL on the Higgs production cross section times branching fraction in the evmuv channel, for a signal with a width of 10% of the mass for the VBF production.

Auxiliary material Figure 7b, Upper limits at 95% CL on the total ggF and VBF Higgs production cross section times branching fraction for a signal at 1.8 TeV as a function of the ggF cross section over the combined ggF and VBF production cross section.

Auxiliary material Figure 7a, Upper limits at 95% CL on the total ggF and VBF Higgs production cross section times branching fraction for a signal at 200 GeV as a function of the ggF cross section over the combined ggF and VBF production cross section.

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 increased by one standard deviation.

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

Expected 95% CL limit for the pMSSM grid.

Expected 95% CL limit for the pMSSM grid with an up variation of the uncertainties.

Expected 95% CL limit for the pMSSM grid with an up variation of the uncertainties.

Expected 95% CL limit for the pMSSM grid with a down variation of the uncertainties.

Expected 95% CL limit for the pMSSM grid with a down variation of the uncertainties.

Observed 95% CL limit for the 2Step 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 increased by one standard deviation.

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

Expected 95% CL limit for the 2Step grid.

Expected 95% CL limit for the 2Step grid with an up variation of the uncertainties.

Expected 95% CL limit for the 2Step grid with an up variation of the uncertainties.

Expected 95% CL limit for the 2Step grid with a down variation of the uncertainties.

Expected 95% CL limit for the 2Step grid with a down variation of the uncertainties.

Observed 95% CL limit for the gtt off-shell grid.

Observed 95% CL limit for the gtt off-shell grid.

Observed 95% CL limit for the gtt off-shell grid when the signal cross section is increased by one standard deviation.

Observed 95% CL limit for the gtt off-shell grid when the signal cross section is increased by one standard deviation.

Observed 95% CL limit for the gtt off-shell grid when the signal cross section is decreased by one standard deviation.

Observed 95% CL limit for the gtt off-shell grid when the signal cross section is decreased by one standard deviation.

Expected 95% CL limit for the gtt off-shell grid.

Expected 95% CL limit for the gtt off-shell grid.

Expected 95% CL limit for the gtt off-shell grid with an up variation of the uncertainties.

Expected 95% CL limit for the gtt off-shell grid with an up variation of the uncertainties.

Expected 95% CL limit for the gtt off-shell grid with a down variation of the uncertainties.

Expected 95% CL limit for the gtt off-shell grid with a down variation of the uncertainties.

Observed 95% CL limit for the RPV grid.

Observed 95% CL limit for the RPV grid.

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

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

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

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

Expected 95% CL limit for the RPV grid.

Expected 95% CL limit for the RPV grid.

Expected 95% CL limit for the RPV grid with an up variation of the uncertainties.

Expected 95% CL limit for the RPV grid with an up variation of the uncertainties.

Expected 95% CL limit for the RPV grid with a down variation of the uncertainties.

Expected 95% CL limit for the RPV grid with a down variation of the uncertainties.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-11j50-0b. 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 SR-11j50-0b. 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 SR-11j50-1b. 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 SR-11j50-1b. 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 SR-11j50-2b. 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 SR-11j50-2b. 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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-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.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-0b. 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 SR-9j80-0b. 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 SR-9j80-1b. 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 SR-9j80-1b. 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 SR-9j80-2b. 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 SR-9j80-2b. 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 SR-8j50-0b-MJ340. 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 SR-8j50-0b-MJ340. 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 SR-8j50-0b-MJ500. 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 SR-8j50-0b-MJ500. 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 SR-9j50-0b-MJ340. 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 SR-9j50-0b-MJ340. 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 SR-9j50-0b-MJ500. 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 SR-9j50-0b-MJ500. 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 SR-10j50-0b-MJ340. 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 SR-10j50-0b-MJ340. 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 SR-10j50-0b-MJ500. 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 SR-10j50-0b-MJ500. 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 (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 50 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 50 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 50 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 50 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 50 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 50 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 80 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 80 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 80 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 80 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 80 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 80 GeV. 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 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 (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 340 GeV. 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 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 (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 340 GeV. 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 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 (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 500 GeV. 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 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 (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 500 GeV. 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 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).

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.

95% CLs observed upper limit on model cross-section (in fb) for 2Step signal points for the best-expected signal region.

95% CLs observed upper limit on model cross-section (in fb) for 2Step signal points for the best-expected signal region.

95% CLs observed upper limit on model cross-section (in fb) for RPV signal points for the best-expected signal region.

95% CLs observed upper limit on model cross-section (in fb) for RPV signal points for the best-expected signal region.

95% CLs observed upper limit on model cross-section (in fb) for gtt off-shell signal points for the best-expected signal region.

95% CLs observed upper limit on model cross-section (in fb) for gtt off-shell signal points for the best-expected signal region.

Performance of the SR-8j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-11j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-11j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-11j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-11j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-11j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-11j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-7j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-7j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-7j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-7j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-7j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-7j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Measured differential fiducial cross sections in cos(theta*) (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in number of jets (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in transverse momentum of the leading jet (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in dijet invariant mass (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in dijet angle phi (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in m12 vs m34 (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in Higgs transverse momentum for 0 jet events (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in Higgs transverse momentum for 1-jet events (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in Higgs transverse momentum for events with 2 or more jets (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in dijet angle eta (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in invariant mass of the leading lepton pair (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in number of bjets (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured fiducial cross sections (second column). The given uncertainty is split into statistical (first) and systematic components (second). The third column gives the theoretical prediction of Higgs production in the fiducial volume using the best available inclusive Higgs production cross sections at the time of the publication. The acceptance to estimate the cross section in the fiducial volume is calculated using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty.

rapidity bin 1.5 < |Y| < 2.0 anti-kt R=0.4

rapidity bin 2.0 < |Y| < 2.5 anti-kt R=0.4

rapidity bin 2.5 < |Y| < 3.0 anti-kt R=0.4

rapidity bin 0 < y* < 0.5 anti-kt R=0.4

rapidity bin 0.5 < y* < 1.0 anti-kt R=0.4

rapidity bin 1.0 < y* < 1.5 anti-kt R=0.4

rapidity bin 1.5 < y* < 2.0 anti-kt R=0.4

rapidity bin 2.0 < y* < 2.5 anti-kt R=0.4

rapidity bin 2.5 < y* < 3.0 anti-kt R=0.4

List of systematic uncertainties contributing to the total uncertainty in the measured values of $\sigma(tq)$, $\sigma(\bar{t}q)$, and $R_t= \sigma(tq)/\sigma(\bar{t}q)$. The estimation of the systematic uncertainties has a statistical uncertainty of $0.3\;\%$. In the publication, uncertainties contributing less than $0.5\,\%$ are marked with ``$<0.5$''. To provide numerical values for this table in HEPdata, these uncertainties are approximated with $\pm 0.5\,\%$. This approximation is applied to the following uncertainties on $\sigma(tq):$ electron uncertainties, $c$-tagging efficiency, light-jet tagging efficiency and $t\bar{t}$, $Wt$, $t\bar{b}+\bar{t}b$ radiation. For the measurement of $\sigma(\bar{t}q)$ the approximation is only applied to the uncertainty in the light-jet tagging efficiency. In case of the ratio $R_t$, there are six uncertainties for which the impact on $R_t$ is estimated to be $<0.5$, but for the purpose of providing the data in electronic form in this table they are quoted as $\pm 0.5\,\%$. These uncertainties are $E_\mathrm{T}^{\mathrm{miss}}$ modelling, '$b$-tagging efficiency, light-jet tagging efficiency, PDF, other background normalisation and luminosity.

Measured values of the cross-sections $\sigma(tq)$, $\sigma(\bar{t}q)$, $\sigma(tq+\bar{t} q)$, and $R_t$ for different simulated top-quark masses. The quoted uncertainties are statistical only.

The measured $E_{T}^{miss}$ distribution in the Z/$\gamma ^{*}$($\rightarrow \mu \mu$)+jets control region, for the $E_{T}^{miss}$ > 250GeV inclusive selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit. The last bin of the distribution contains overflows.

The measured leading jet $p_{T}$ distribution in the Z/$\gamma ^{*}$($\rightarrow \mu \mu$)+jets control region, for the $E_{T}^{miss}$ > 250GeV inclusive selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit. The last bin of the distribution contains overflows.

The measured $E_{T}^{miss}$ distribution in the top control region, for the $E_{T}^{miss}$ > 250GeV inclusive selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit. The last bin of the distribution contains overflows.

The measured leading jet $p_{T}$ distribution in the top control region, for the $E_{T}^{miss}$ > 250GeV inclusive selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit. The last bin of the distribution contains overflows.

Measured distribution of the $E_{T}^{miss}$ for the $E_{T}^{miss}$ > 250GeV selection compared to the SM predictions. The latter are normalized with normalization factors as determined by the global fit that considers exclusive $E_{T}^{miss}$ regions. The last bin of the distribution contains overflows.

Measured distribution of the leading jet $p_{T}$ for the $E_{T}^{miss}$ > 250GeV selection compared to the SM predictions. The latter are normalized with normalization factors as determined by the global fit that considers exclusive $E_{T}^{miss}$ regions. The last bin of the distribution contains overflows.

Measured distribution of the leading jet $|\eta|$ for the $E_{T}^{miss}$ > 250GeV selection compared to the SM predictions. The latter are normalized with normalization factors as determined by the global fit that considers exclusive $E_{T}^{miss}$ regions. The last bin of the distribution contains overflows.

Measured distribution of the jet multiplicity for the $E_{T}^{miss}$ > 250GeV selection compared to the SM predictions. The latter are normalized with normalization factors as determined by the global fit that considers exclusive $E_{T}^{miss}$ regions. The last bin of the distribution contains overflows.

The expected $95\%$ CL exclusion limit for a simplified model of dark matter production involving an axial-vector operator, Dirac DM and couplings $g_{q} = 0.25$ and $g_{\chi} = 1$ as a function of the assumed mediator mass m$_{Z_{A}}$ and the dark matter mass m$_{\chi}$.

The measured $E_{T}^{miss}$ distribution in the W($\rightarrow \mu \nu$)+jets control region, for the $E_{T}^{miss}$ > 250GeV inclusive selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit. The last bin of the distribution contains overflows.

The observed $95\%$ CL exclusion limit for a simplified model of dark matter production involving an axial-vector operator, Dirac DM and couplings $g_{q} = 0.25$ and $g_{\chi} = 1$ as a function of the assumed mediator mass m$_{Z_{A}}$ and the dark matter mass m$_{\chi}$.

The observed $90\%$ CL exclusion limit on the spin-dependent WIMP–proton scattering cross section in the context of the simplified model with axial-vector couplings, assuming minimal mediator width and the coupling values $g_{q} = 0.25$ and $g_{\chi} = 1$.

The expected $95\%$ CL exclusion limit for a simplified model of dark matter production involving a vector operator, Dirac DM and couplings $g_{q} = 0.25$ and $g_{\chi} = 1$ as a function of the assumed mediator mass m$_{Z_{V}}$ and the dark matter mass m$_{\chi}$.

The observed $95\%$ CL exclusion limit for a simplified model of dark matter production involving a vector operator, Dirac DM and couplings $g_{q} = 0.25$ and $g_{\chi} = 1$ as a function of the assumed mediator mass m$_{Z_{V}}$ and the dark matter mass m$_{\chi}$.

The expected and observed $95\%$ CL limits on the signal strength $\mu = \sigma^{95\% CL}/\sigma$ as a function of the mediator mass for a very light WIMP, in a model with spin-0 pseudoscalar mediator and $g_{q}=g_{\chi}=1.0$.

The expected and observed $95\%$ CL limits on the signal strength $\mu = \sigma^{95\% CL}/\sigma$ as a function of the WIMP mass for $m_{Z_{P}}=10$ GeV, in a model with spin-0 pseudoscalar mediator and $g_{q}=g_{\chi}=1.0$.

The expected exclusion contour at $95\%$ CL in the m$_{\eta}$–m$_{\chi}$ parameter plane for the coloured scalar mediator model, with minimal width and coupling set to $g=1$.

The observed exclusion contour at $95\%$ CL in the m$_{\eta}$–m$_{\chi}$ parameter plane for the coloured scalar mediator model, with minimal width and coupling set to $g=1$.

The expected excluded region at the $95\%$ CL in the ($\tilde{t}_{1}$,$\chi^{0}_{1}$) mass plane for the decay channel $\tilde{t}_{1} \rightarrow c + \chi^{0}_{1}$ (B = $100\%$).

The observed excluded region at the $95\%$ CL in the ($\tilde{t}_{1}$,$\chi^{0}_{1}$) mass plane for the decay channel $\tilde{t}_{1} \rightarrow c + \chi^{0}_{1}$ (B = $100\%$).

The expected excluded region at the $95\%$ CL in the ($\tilde{t}_{1}$,$\chi^{0}_{1}$) mass plane for the decay channel $\tilde{t}_{1} \rightarrow b + ff' + \chi^{0}_{1}$ (B = $100\%$).

The observed excluded region at the $95\%$ CL in the ($\tilde{t}_{1}$,$\chi^{0}_{1}$) mass plane for the decay channel $\tilde{t}_{1} \rightarrow b + ff' + \chi^{0}_{1}$ (B = $100\%$).

The expected exclusion plane at $95\%$ CL as a function of sbottom and neutralino masses for the decay channel $\tilde{b}_{1} \rightarrow b + \chi^{0}_{1}$ (B = $100\%$).

The observed exclusion plane at $95\%$ CL as a function of sbottom and neutralino masses for the decay channel $\tilde{b}_{1} \rightarrow b + \chi^{0}_{1}$ (B = $100\%$).

The expected exclusion region at $95\%$ CL as a function of squark mass and the squark-neutralino mass difference for $\tilde{q}_{1} → q + \chi^{0}_{1}$ (q =u,d,c,s).

The observed exclusion region at $95\%$ CL as a function of squark mass and the squark-neutralino mass difference for $\tilde{q}_{1} → q + \chi^{0}_{1}$ (q =u,d,c,s).

Expected and observed $95\%$ CL lower limits on the fundamental Planck scale in 4+n dimensions, M$_D$, as a function of the number of extra dimensions.

Expected and observed $95\%$ CL upper limit on the signal strength $\mu$ in the hypothesis of an axial-vector mediator, g$_{q}=0.25$, g$_{\chi}=1.0$ and minimal mediator width, as a function of the assumed mediator and DM masses.

Observed $90\%$ CL exclusion limit on the spin-dependent WIMP–neutron scattering cross section in the context of the simplified model with axial-vector couplings, assuming minimal mediator width and the coupling values $g_{q}=0.25$ and $g_{\chi}=1$.

Expected and observed $95\%$ CL upper limit on the signal strength $\mu$ in the hypothesis of a pseudoscalar mediator, $g_{q}=g_{\chi}=1.0$ and minimal mediator width, as a function of the assumed mediator and DM masses.

Distribution of the missing transverse momentum $E_{\mathrm{T}}^{\mathrm{miss}}$ for the sample satisfying all requirements of the $\mathrm{SR}^{\gamma\gamma}_{W-L}$ selection except the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement itself. Overlaid are the expected SM backgrounds, separated into the various contributing sources. Also shown are the signal expectations for the ($m_{\tilde{W}}$, $m_{\tilde{\chi}^{0}_{1}}$) = (1000,100) GeV and ($m_{\tilde{W}}$, $m_{\tilde{\chi}^{0}_{1}}$) = (1000,800) GeV models. The vertical dashed lines and right-pointing arrows show the region of the $E_{\mathrm{T}}^{\mathrm{miss}}$ observable selected for inclusion in $\mathrm{SR}^{\gamma\gamma}_{W-L}$ and $\mathrm{SR}^{\gamma\gamma}_{W-H}$. The lower panels show the ratio of observed data to the combined SM expectation. For these plots, the band represents the range of combined statistical and systematic uncertainty in the SM expectation. Events outside the range of the displayed region are included in the highest-value bin.

Distribution of the missing transverse momentum $E_{\mathrm{T}}^{\mathrm{miss}}$ for the sample satisfying all requirements of the $\mathrm{SR}^{\gamma\gamma}_{W-H}$ selection except the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement itself. Overlaid are the expected SM backgrounds, separated into the various contributing sources. Also shown are the signal expectations for the ($m_{\tilde{W}}$, $m_{\tilde{\chi}^{0}_{1}}$) = (1000,100) GeV and ($m_{\tilde{W}}$, $m_{\tilde{\chi}^{0}_{1}}$) = (1000,800) GeV models. The vertical dashed lines and right-pointing arrows show the region of the $E_{\mathrm{T}}^{\mathrm{miss}}$ observable selected for inclusion in $\mathrm{SR}^{\gamma\gamma}_{W-L}$ and $\mathrm{SR}^{\gamma\gamma}_{W-H}$. The lower panels show the ratio of observed data to the combined SM expectation. For these plots, the band represents the range of combined statistical and systematic uncertainty in the SM expectation. Events outside the range of the displayed region are included in the highest-value bin.

Comparisons between expected and observed content of the validation and signal regions for the photon+jets analysis. The uncertainties in the expected numbers of events are the combined statistical and systematic uncertainties. The lower panel shows the pull (difference between observed and expected event counts normalized by the uncertainty) for each region.

Distribution of the missing transverse momentum $E_{\mathrm{T}}^{\mathrm{miss}}$ for the sample satisfying all requirements of the $\mathrm{SR}^{\gamma j}_{H}$ selection except the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement itself. Overlaid are the expected SM backgrounds, separated into the various contributing sources. Also shown are the signal expectations for points in the $m_{\tilde{g}}-m_{\tilde{\chi}^{0}_{1}}$ parameter space of the GGM model relevant to the photon+jets analysis (mass values in GeV). The value of the gluino mass arises from the choice $M_{3}$ = 1900 GeV. The $\tilde{\chi}^{0}_{1}$ mass values of 1868, 1920, 442 and 652 GeV arise from the choices $\mu$ = 1810, 1868, 400 and 600 GeV, respectively, combined with the constraint that the branching fraction of $\tilde{\chi}^{0}_{1}$ $\to \gamma \tilde{G}$ be 50%. The vertical dashed lines and right-pointing arrows show the region of the $E_{\mathrm{T}}^{\mathrm{miss}}$ observable selected for inclusion in $\mathrm{SR}^{\gamma j}_{H}$ and $\mathrm{SR}^{\gamma j}_{L}$ for $\mathrm{SR}^{\gamma j}_{L200}$, the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement is 200 GeV rather than 300 GeV. The lower panels show the ratio of observed data to the combined SM expectation. For these plots, the band represents the range of statistical uncertainty in the SM expectation. Events outside the range of the displayed region are included in the highest-value bin.

Distribution of the missing transverse momentum $E_{\mathrm{T}}^{\mathrm{miss}}$ for the sample satisfying all requirements of the $\mathrm{SR}^{\gamma j}_{L}$ or $\mathrm{SR}^{\gamma j}_{L200}$ selection except the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement itself. Overlaid are the expected SM backgrounds, separated into the various contributing sources. Also shown are the signal expectations for points in the $m_{\tilde{g}}-m_{\tilde{\chi}^{0}_{1}}$ parameter space of the GGM model relevant to the photon+jets analysis (mass values in GeV). The value of the gluino mass arises from the choice $M_{3}$ = 1900 GeV. The $\tilde{\chi}^{0}_{1}$ mass values of 1868, 1920, 442 and 652 GeV arise from the choices $\mu$ = 1810, 1868, 400 and 600 GeV, respectively, combined with the constraint that the branching fraction of $\tilde{\chi}^{0}_{1} \to \gamma \tilde{G}$ be 50%. The vertical dashed lines and right-pointing arrows show the region of the $E_{\mathrm{T}}^{\mathrm{miss}}$ observable selected for inclusion in $\mathrm{SR}^{\gamma j}_{H}$ and $\mathrm{SR}^{\gamma j}_{L}$ for $\mathrm{SR}^{\gamma j}_{L200}$, the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement is 200 GeV rather than 300 GeV. The lower panels show the ratio of observed data to the combined SM expectation. For these plots, the band represents the range of statistical uncertainty in the SM expectation. Events outside the range of the displayed region are included in the highest-value bin.

Expected exclusion limits in the gluino-bino mass plane, using the $\mathrm{SR}^{\gamma\gamma}_{S-H}$ analysis for $m_{\tilde{\chi}^{0}_{1}} > 1600$ GeV and the $\mathrm{SR}^{\gamma\gamma}_{S-L}$ analysis for $m_{\tilde{\chi}^{0}_{1}} < 1600$ GeV.

Observed exclusion limits in the gluino--bino mass plane, using the $\mathrm{SR}^{\gamma\gamma}_{S-H}$ analysis for $m_{\tilde{\chi}^{0}_{1}} > 1600$ GeV and the $\mathrm{SR}^{\gamma\gamma}_{S-L}$ analysis for $m_{\tilde{\chi}^{0}_{1}} < 1600$ GeV.

Expected exclusion limit in the squark-bino mass plane, using the $\mathrm{SR}^{\gamma\gamma}_{S-H}$ analysis for $m_{\tilde{\chi}^{0}_{1}} > 900$ GeV and the $\mathrm{SR}^{\gamma\gamma}_{S-L}$ analysis for $m_{\tilde{\chi}^{0}_{1}} < 900$ GeV.

Observed exclusion limit in the squark--bino mass plane, using the $\mathrm{SR}^{\gamma\gamma}_{S-H}$ analysis for $m_{\tilde{\chi}^{0}_{1}} > 900$ GeV and the $\mathrm{SR}^{\gamma\gamma}_{S-L}$ analysis for $m_{\tilde{\chi}^{0}_{1}} < 900$ GeV.

Expected exclusion limit in the wino-bino mass plane, using the $\mathrm{SR}^{\gamma\gamma}_{W-H}$ analysis for $m_{\tilde{\chi}^{0}_{1}} > 400$ GeV and the $\mathrm{SR}^{\gamma\gamma}_{W-L}$ analysis for $m_{\tilde{\chi}^{0}_{1}}$ < 400$ GeV.

Observed exclusion limit in the wino-bino mass plane, using the $\mathrm{SR}^{\gamma\gamma}_{W-H}$ analysis for $m_{\tilde{\chi}^{0}_{1}} > 400$ GeV and the $\mathrm{SR}^{\gamma\gamma}_{W-L}$ analysis for $m_{\tilde{\chi}^{0}_{1}}$ < 400$ GeV.

Expected exclusion limits for the $\mu > 0$ higgsino-bino GGM model explored by the photon+jets analysis.

Observed exclusion limits for the $\mu > 0$ higgsino-bino GGM model explored by the photon+jets analysis.

Distribution of the transverse momentum $p_{\mathrm{T}} (\ell\gamma\gamma)$ of events in the $\ell\gamma\gamma$ control region (except without a cut on $p_{\mathrm{T}} (\ell\gamma\gamma)$). Also shown is the expected contribution from various SM sources, including $W(\to\ell\nu) + \gamma\gamma$ production itself. The displayed uncertainties are a combination of those from all SM sources except $W(\to\ell\nu) + \gamma\gamma$ production, and include statistical and systematic uncertainties.

Distribution of $E_{\mathrm{T}}^{\mathrm{miss}}$ for diphoton events in a validation region defined by a requirement of $H_{\mathrm{T}} > 1750$ GeV. Also shown is the expected contribution from various SM sources, as well as their combined statistical and systematic uncertainties.

Distribution of $H_{\mathrm{T}}$ for diphoton events in a validation region defined by requirement of $E_{\mathrm{T}}^{\mathrm{miss}} > 100$ GeV. Also shown is the expected contribution from various SM sources, as well as their combined statistical and systematic uncertainties.

Distribution of $m_{\mathrm{eff}}$ for events satisfying all requirements $\mathrm{SR}^{\gamma j}_{H}$ save the $m_{\mathrm{eff}}$ requirement itself. Also shown is the expected contribution from various SM sources, and their combined statistical uncertainties.

Distribution of $m_{\mathrm{eff}}$ for events satisfying all requirements $\mathrm{SR}^{\gamma j}_{L}$ save the $m_{\mathrm{eff}}$ requirement itself. Also shown is the expected contribution from various SM sources, and their combined statistical uncertainties.

Derived exclusion limits for the gluino-bino GGM model explored by the diphoton analysis. For each point in the gluino-bino parameter space, the SR ($\mathrm{SR}^{\gamma\gamma}_{S-L}$ or $\mathrm{SR}^{\gamma\gamma}_{S-H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The model dependent upper limits on cross-section (fb) are shown by grey numbers for each signal point.

Derived exclusion limits for the squark-bino GGM model explored by the diphoton analysis. For each point in the squark-bino parameter space, the SR ($\mathrm{SR}^{\gamma\gamma}_{S-L}$ or $\mathrm{SR}^{\gamma\gamma}_{S-H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The model dependent upper limits on cross-section (fb) are shown by grey numbers for each signal point.

Derived exclusion limits for the wino-bino GGM model explored by the diphoton analysis. For each point in the wino-bino parameter space, the SR ($\mathrm{SR}^{\gamma\gamma}_{W-L}$ or $\mathrm{SR}^{\gamma\gamma}_{W-H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The model dependent upper limits on cross-section (fb) are shown by grey numbers for each signal point.

Derived exclusion limits for the $\mu > 0$ higgsino-bino GGM model explored by the photon+jets analysis. For each point in the higgsino-bino parameter space, the SR ($\mathrm{SR}^{\gamma j}_{L}$ or $\mathrm{SR}^{\gamma j}_{H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The model dependent upper limits on cross-section (fb) are shown by grey numbers for each signal point.

Derived exclusion limits for the gluino-bino GGM model explored by the diphoton analysis. For each point in the gluino-bino parameter space, the SR ($\mathrm{SR}^{\gamma\gamma}_{S-L}$ or $\mathrm{SR}^{\gamma\gamma}_{S-H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The labels indicate the best-expected signal region for each point, where SL and SH mean $\mathrm{SR}^{\gamma\gamma}_{S-L}$ and $\mathrm{SR}^{\gamma\gamma}_{S-H}$, respectively.

Derived exclusion limits for the squark-bino GGM model explored by the diphoton analysis. For each point in the squark-bino parameter space, the SR ($\mathrm{SR}^{\gamma\gamma}_{S-L}$ or $\mathrm{SR}^{\gamma\gamma}_{S-H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The labels indicate the best-expected signal region for each point, where SL and SH mean $\mathrm{SR}^{\gamma\gamma}_{S-L}$ and $\mathrm{SR}^{\gamma\gamma}_{S-H}$, respectively.

Derived exclusion limits for the wino--bino GGM model explored by the diphoton analysis. For each point in the wino-bino parameter space, the SR ($\mathrm{SR}^{\gamma\gamma}_{W-L}$ or $\mathrm{SR}^{\gamma\gamma}_{W-H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The labels indicate the best-expected signal region for each point, where WL and WH mean $\mathrm{SR}^{\gamma\gamma}_{W-L}$ and $\mathrm{SR}^{\gamma\gamma}_{W-H}$, respectively.

Derived exclusion limits for the $\mu > 0$ higgsino-bino GGM model explored by the photon+jets analysis. For each point in the higgsino-bino parameter space, the SR ($\mathrm{SR}^{\gamma j}_{L}$ or $\mathrm{SR}^{\gamma j}_{H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The labels indicate the best-expected signal region for each point, where L and H mean $\mathrm{SR}^{\gamma j}_{L}$ and $\mathrm{SR}^{\gamma j}_{H}$, respectively.

Acceptance and efficiency for $\mathrm{SR}^{\gamma\gamma}_{S-L}$ for the signal models of the gluino-bino GGM grid.

Acceptance and efficiency for $\mathrm{SR}^{\gamma\gamma}_{S-H}$ for the signal models of the gluino-bino GGM grid.

Acceptance and efficiency for $\mathrm{SR}^{\gamma\gamma}_{S-L}$ for the signal models of the squark-bino GGM grid.

Acceptance and efficiency for $\mathrm{SR}^{\gamma\gamma}_{S-H}$ for the signal models of the squark-bino GGM grid.

Acceptance and efficiency for $\mathrm{SR}^{\gamma\gamma}_{W-L}$ for the signal models of the wino-bino GGM grid.

Acceptance and efficiency for $\mathrm{SR}^{\gamma\gamma}_{W-H}$ for the signal models of the wino-bino GGM grid.

Acceptance and efficiency for $\mathrm{SR}^{\gamma j}_{L}$ for the signal models of the photon+jets GGM grid.

Acceptance and efficiency for $\mathrm{SR}^{\gamma j}_{H}$ for the signal models of the photon+jets GGM grid.

Cutflow for the $\mathrm{SR}^{\gamma\gamma}_{S-L}$ selection for one relevant signal point in the gluino-bino model, where the gluinos have mass of 1900 GeV and the $\tilde{\chi}^{0}_{1}$ has a mass of 300 GeV (10000 generated events). The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Cutflow for the $\mathrm{SR}^{\gamma\gamma}_{S-H}$ selection for one relevant signal point in the gluino-bino model, where the gluinos have mass of 1900 GeV and the $\tilde{\chi}^{0}_{1}$ has a mass of 1700 GeV (10000 generated events). The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Cutflow for the $\mathrm{SR}^{\gamma\gamma}_{S-L}$ selection for one relevant signal point in the squark-bino model, where the squarks have mass of 1700 GeV and the $\tilde{\chi}^{0}_{1}$ has a mass of 200 GeV (10000 generated events). The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Cutflow for the $\mathrm{SR}^{\gamma\gamma}_{S-H}$ selection for one relevant signal point in the squark-bino model, where the squarks have mass of 1700 GeV and the $\tilde{\chi}^{0}_{1}$ has a mass of 1600 GeV (10000 generated events). The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Cutflow for the $\mathrm{SR}^{\gamma\gamma}_{W-L}$ selection for one relevant signal point in the wino-bino model, where the winos have mass of 1000 GeV and the $\tilde{\chi}^{0}_{1}$ has a mass of 200 GeV (10000 generated events). The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Cutflow for the $\mathrm{SR}^{\gamma\gamma}_{W-H}$ selection for one relevant signal point in the wino-bino model, where the winos have mass of 1000 GeV and the $\tilde{\chi}^{0}_{1}$ has a mass of 800 GeV (10000 generated events). The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Cutflow for the $\mathrm{SR}^{\gamma j}_{L}$ selection, for two relevant signal points in the higgsino-bino model, where the gluinos have mass of 1974 GeV and the $\tilde{\chi}^{0}_{1}$ has a mass of 442 GeV (10000 generated events), and 652 GeV (10000 generated events). The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Cutflow for the $\mathrm{SR}^{\gamma j}_{H}$ selection, for two relevant signal points in the higgsino-bino model, where the gluinos have mass of 1974 GeV and the $\tilde{\chi}^{0}_{1}$ has a mass of 1868 GeV (10000 generated events), and 1920 GeV (10000 generated events). The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.