Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.

Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.

Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.

Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.

Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.

Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.

Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.

Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.

Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).

Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).

Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).

Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.

Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.

Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (750,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (400,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Upper limits at the 95% CL on the cross section for SSM W' production and decay to the muon+neutrino channel as a function of the W' pole mass.

Combined (electron and muon channels) upper limits at the 95% CL on the cross section for SSM W' production and decay to a single lepton generation as a function of the W' pole mass.

Product of acceptance and efficiency for the electron and muon selections as a function of the W' pole mass.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

HT inclusive distribution in SRZ.

Jet multiplicity distribution in SRZ.

B-tagged jet multiplicity distribution in SRZ.

Dilepton invariant mass distribution in SRMedium.

Dilepton invariant mass distribution in SRMedium.

Dilepton invariant mass in SRHigh.

Expected 95% exclusion contour for the gluino simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.

Observed 95% exclusion contour for the gluino simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.

Expected 95% exclusion contour for the squark simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.

Observed 95% exclusion contour for the squark simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.

Expected 95% exclusion contour for the gluino simplified model with varying N1 mass and decays to quarks and Z bosons in SRZ.

Observed 95% exclusion contour for the gluino simplified model with varying N1 mass and decays to quarks and Z bosons in SRZ.

Expected 95% exclusion contour for the gluino simplified model with sleptons in the edge SRs.

Observed 95% exclusion contour for the gluino simplified model with sleptons in the edge SRs.

Expected 95% exclusion contour for the gluino simplified model with decays to on- or off-shell Z bosons in the edge SRs.

Observed 95% exclusion contour for the gluino simplified model with decays to on- or off-shell Z bosons in the edge SRs.

Expected 95% exclusion contour for the gluino simplified model with decays to on- or off-shell Z bosons in SRZ.

Observed 95% exclusion contour for the gluino simplified model with decays to on- or off-shell Z bosons in SRZ.

Cutflow table for three benchmark signal points from the $\tilde{g}$--$\chi_{2}^{0}$ on-shell grid in SRZ for the $ee$ and $\mu\mu$ channels separately. The number of generated events is N RAW, while N WEIGHTED corresponds to the number of events expected in 14.7/fb, after all MC simulation corrections have been applied.

Cutflow table for three benchmark signal points for the slepton model in SR-low, SR-medium and SR-high for the $ee$ and $\mu\mu$ channels separately. The number of generated events is N RAW, while N WEIGHTED corresponds to the number of events expected in 14.7/fb, after all MC simulation corrections have been applied. The event generation was filtered to require at least two leptons (electrons or muons) with $p_{T}>5$ GeV and $|\eta|<2.8$, with 20000 events required to pass the filter. The corresponding number of unfiltered events is provided in the ``Pre-filter events'' row of the table.

Signal acceptance for the gluino simplified model with decays to quarks and Z bosons in SRZ.

Signal efficiency for the gluino simplified model with decays to quarks and Z bosons in SRZ.

Signal acceptance for the gluino simplified model with decays via sleptons in SRLow.

Signal efficiency for the gluino simplified model with decays via sleptons in SRLow.

Signal acceptance for the gluino simplified model with decays via sleptons in SRMedium.

Signal efficiency for the gluino simplified model with decays via sleptons in SRMedium.

Signal acceptance for the gluino simplified model with decays via sleptons in SRHigh.

Signal efficiency for the gluino simplified model with decays via sleptons in SRHigh.

Upper limits on the signal cross-section at 95% CL for the gluino simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.

Upper limits on the signal cross-section at 95% CL for the squark simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.

Upper limits on the signal cross-section at 95% CL for the gluino simplified model with varying N1 mass and decays to quarks and Z bosons in SRZ.

Upper limits on the signal cross-section at 95% CL for the gluino simplified model with decays via sleptons.

Upper limits on the signal cross-section at 95% CL for the gluino simplified model with decays to on-shell or off-shell Z bosons.

Kinematic distributions for "extended SR selections" of the 2-tau channel, for mTsum in the Compressed SR selection without the mTsum>1400 GeV requirement. The last bin includes overflow events. Cited uncertainties are statistical uncertainties only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "MM" refers to a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV. The GMSB benchmark model corresponds to Lambda = 90 TeV and tanbeta = 40.

Kinematic distributions for "extended SR selections" of the 2-tau channel, for mTtau1+mTtau2 in the High-Mass SR selection without the mTtau1+mTtau2>350GeV requirement. The last bin includes overflow events. Cited uncertainties are statistical uncertainties only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "MM" refers to a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV. The GMSB benchmark model corresponds to Lambda = 90 TeV and tanbeta = 40.

Kinematic distributions for "extended SR selections" of the 2-tau channel, for HT in the GMSB SR selection without the HT > 1700 GeV requirement. The last bin includes overflow events. Cited uncertainties are statistical uncertainties only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "MM" refers to a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV. The GMSB benchmark model corresponds to Lambda = 90 TeV and tanbeta = 40.

Expected exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on the combined results from the 1tau and 2tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.

Observed exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on the combined results from the 1tau and 2tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.

Expected exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on results from the 2tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.

Expected exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on results from the 1tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.

Observed exclusion contours at the 95% confidence level for the gauge-mediated supersymmetry-breaking model, based on results from the 2 tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data. Additional model parameters are M(mess) = 250 TeV, N5 = 3, mu>0 and Cgrav =1.

Expected exclusion contours at the 95% confidence level for the gauge-mediated supersymmetry-breaking model, based on results from the 2 tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data. Additional model parameters are M(mess) = 250 TeV, N5 = 3, mu>0 and Cgrav =1.

Observed upper cross section limits in pb for the simplified model of gluino pair production for the combination of all SRs.

Best expected signal region for the simplified model of gluino pair production. The respective SR has been used in the combination of the results.

Acceptance for the gluino production simplified model grid in the Compressed 1tau signal region.

Efficiency for the gluino production simplified model grid in the Compressed 1tau signal region.

Acceptance times Efficiency for the gluino production simplified model grid in the Compressed 1tau signal region.

Acceptance for the gluino production simplified model grid in the medium mass 1tau signal region.

Efficiency for the gluino production simplified model grid in the medium mass 1tau signal region.

Acceptance times Efficiency for the gluino production simplified model grid in the medium mass 1tau signal region.

Acceptance for the gluino production simplified model grid in the high mass 1tau signal region.

Efficiency for the gluino production simplified model grid in the high mass 1tau signal region.

Acceptance times Efficiency for the gluino production simplified model grid in the high mass 1tau signal region.

Acceptance for the gluino production simplified model grid in the compressed 2tau signal region.

Efficiency for the gluino production simplified model grid in the compressed 2tau signal region.

Acceptance times Efficiency for the gluino production simplified model grid in the compressed 2tau signal region.

Acceptance for the gluino production simplified model grid in the high mass 2tau signal region.

Efficiency for the gluino production simplified model grid in the high mass 2tau signal region.

Acceptance times Efficiency for the gluino production simplified model grid in the high mass 2tau signal region.

Acceptance for the GMSB model grid in the 2tau signal region.

Efficiency for the GMSB model grid in the 2tau signal region.

Acceptance times Efficiency for the GMSB model grid in the 2tau signal region.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Median expected and observed 95% CL upper limits on the cross-section times branching ratio (sigma*B) for W'_SSM production for the exclusive muon and electron channels, and for both channels combined.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Observed and expected background and signal effective mass distributions for SR2jl. For signal, a squark direct decay model with $m(\tilde q)=800$ GeV and $m(\tilde\chi^0_1)=400$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR2jm. For signal, a gluino direct decay model with $m(\tilde g)=750$ GeV and $m(\tilde\chi^0_1)=660$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR2jt. For signal, a squark direct decay model with $m(\tilde q)=1200$ GeV and $m(\tilde\chi^0_1)=0$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR4jt. For signal, a gluino direct decay model with $m(\tilde g)=1400$ GeV and $m(\tilde\chi^0_1)=0$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR5j. For signal, a gluino one-step decay model with $m(\tilde g)=1265$ GeV, $m(\tilde\chi^\pm_1)=945$ GeV and $m(\tilde\chi^0_1)=625$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR6jm. For signal, a gluino one-step decay model with $m(\tilde g)=1265$ GeV, $m(\tilde\chi^\pm_1)=945$ GeV and $m(\tilde\chi^0_1)=625$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR6jt. For signal, a gluino one-step decay model with $m(\tilde g)=1385$ GeV, $m(\tilde\chi^\pm_1)=705$ GeV and $m(\tilde\chi^0_1)=25$ GeV is shown.

Expected limit at 95% CL for squark direct decay model grid.

Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for squark direct decay model grid.

Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for squark direct decay model grid.

Observed limits at 95% CL for squark direct decay model grid.

Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for squark direct decay model grid.

Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for squark direct decay model grid.

Expected limit at 95% CL for gluino direct decay model grid.

Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino direct decay model grid.

Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino direct decay model grid.

Observed limits at 95% CL for gluino direct decay model grid.

Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for gluino direct decay model grid.

Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for gluino direct decay model grid.

Expected limit at 95% CL for gluino one-step decay model grid.

Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino one-step decay model grid.

Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino one-step decay model grid.

Observed limits at 95% CL for gluino one-step decay model grid.

Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for gluino one-step decay model grid.

Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for gluino one-step decay model grid.

Observed and expected background effective mass distributions in control region CRgamma for SR2jl.

Observed and expected background effective mass distributions in validation region VRZ for SR2jl.

Observed and expected background effective mass distributions in control region CRW for SR2jl.

Observed and expected background effective mass distributions in control region CRT for SR2jl.

Observed and expected background effective mass distributions in control region CRgamma for SR2jm.

Observed and expected background effective mass distributions in validation region VRZ for SR2jm.

Observed and expected background effective mass distributions in control region CRW for SR2jm.

Observed and expected background effective mass distributions in control region CRT for SR2jm.

Observed and expected background effective mass distributions in control region CRgamma for SR2jt.

Observed and expected background effective mass distributions in validation region VRZ for SR2jt.

Observed and expected background effective mass distributions in control region CRW for SR2jt.

Observed and expected background effective mass distributions in control region CRT for SR2jt.

Observed and expected background effective mass distributions in control region CRgamma for SR4jt.

Observed and expected background effective mass distributions in validation region VRZ for SR4jt.

Observed and expected background effective mass distributions in control region CRW for SR4jt.

Observed and expected background effective mass distributions in control region CRT for SR4jt.

Observed and expected background effective mass distributions in control region CRgamma for SR5j.

Observed and expected background effective mass distributions in validation region VRZ for SR5j.

Observed and expected background effective mass distributions in control region CRW for SR5j.

Observed and expected background effective mass distributions in control region CRT for SR5j.

Observed and expected background effective mass distributions in control region CRgamma for SR6jm.

Observed and expected background effective mass distributions in validation region VRZ for SR6jm.

Observed and expected background effective mass distributions in control region CRW for SR6jm.

Observed and expected background effective mass distributions in control region CRT for SR6jm.

Observed and expected background effective mass distributions in control region CRgamma for SR6jt.

Observed and expected background effective mass distributions in validation region VRZ for SR6jt.

Observed and expected background effective mass distributions in control region CRW for SR6jt.

Observed and expected background effective mass distributions in control region CRT for SR6jt.

Observed and expected event yields in VRZ as a function of signal region.

Observed and expected event yields in VRW as a function of signal region.

Observed and expected event yields in VRWv as a function of signal region.

Observed and expected event yields in VRT as a function of signal region.

Observed and expected event yields in VRTv as a function of signal region.

Observed and expected event yields in VRQa as a function of signal region.

Observed and expected event yields in VRQb as a function of signal region.

Signal acceptance for SR2jl in squark direct decay model grid.

Signal acceptance times efficiency for SR2jl in squark direct decay model grid.

Signal acceptance for SR2jm in squark direct decay model grid.

Signal acceptance times efficiency for SR2jm in squark direct decay model grid.

Signal acceptance for SR2jt in squark direct decay model grid.

Signal acceptance times efficiency for SR2jt in squark direct decay model grid.

Signal acceptance for SR4jt in squark direct decay model grid.

Signal acceptance times efficiency for SR4jt in squark direct decay model grid.

Signal acceptance for SR5j in squark direct decay model grid.

Signal acceptance times efficiency for SR5j in squark direct decay model grid.

Signal acceptance for SR6jm in squark direct decay model grid.

Signal acceptance times efficiency for SR6jm in squark direct decay model grid.

Signal acceptance for SR6jt in squark direct decay model grid.

Signal acceptance times efficiency for SR6jt in squark direct decay model grid.

Signal acceptance for SR2jl in gluino direct decay model grid.

Signal acceptance times efficiency for SR2jl in gluino direct decay model grid.

Signal acceptance for SR2jm in gluino direct decay model grid.

Signal acceptance times efficiency for SR2jm in gluino direct decay model grid.

Signal acceptance for SR2jt in gluino direct decay model grid.

Signal acceptance times efficiency for SR2jt in gluino direct decay model grid.

Signal acceptance for SR4jt in gluino direct decay model grid.

Signal acceptance times efficiency for SR4jt in gluino direct decay model grid.

Signal acceptance for SR5j in gluino direct decay model grid.

Signal acceptance times efficiency for SR5j in gluino direct decay model grid.

Signal acceptance for SR6jm in gluino direct decay model grid.

Signal acceptance times efficiency for SR6jm in gluino direct decay model grid.

Signal acceptance for SR6jt in gluino direct decay model grid.

Signal acceptance times efficiency for SR6jt in gluino direct decay model grid.

Signal acceptance for SR2jl in gluino one-step decay model grid.

Signal acceptance times efficiency for SR2jl in gluino one-step decay model grid.

Signal acceptance for SR2jm in gluino one-step decay model grid.

Signal acceptance times efficiency for SR2jm in gluino one-step decay model grid.

Signal acceptance for SR2j5 in gluino one-step decay model grid.

Signal acceptance times efficiency for SR2jt in gluino one-step decay model grid.

Signal acceptance for SR4jt in gluino one-step decay model grid.

Signal acceptance times efficiency for SR4jt in gluino one-step decay model grid.

Signal acceptance for SR5j in gluino one-step decay model grid.

Signal acceptance times efficiency for SR5j in gluino one-step decay model grid.

Signal acceptance for SR6jm in gluino one-step decay model grid.

Signal acceptance times efficiency for SR6jm in gluino one-step decay model grid.

Signal acceptance for SR6jt in gluino one-step decay model grid.

Signal acceptance times efficiency for SR6jt in gluino one-step decay model grid.

Observed event yields and estimated backgrounds in the low- and high-mass control regions. The uncertainty in the background yield is the sum in quadrature of the statistical and systematic uncertainties.

Summary of the relative systematic uncertainties in heavy Majorana neutrino signal yields and the background from prompt same-sign leptons, both estimated from simulation. The relative systematic uncertainties assigned to the data-driven backgrounds for the misidentified lepton background and mismeasured charge background are also shown. The uncertainties are given for the low-mass selections.

Summary of the relative systematic uncertainties in heavy Majorana neutrino signal yields and the background from prompt same-sign leptons, both estimated from simulation. The relative systematic uncertainties assigned to the data-driven backgrounds for the misidentified lepton background and mismeasured charge background are also shown. The uncertainties are given for the high-mass selections.

Summary of contributions to the systematic uncertainty related to the prompt same-sign leptons background, misidentified lepton background, and mismeasured charge background on the total background uncertainty for the case of $m_{\rm N}$ = 100 and 500 GeV.

Observed event yields and estimated backgrounds after the application of all selection, except for the final optimization. The background predictions from prompt same-sign leptons (Prompt bkgd.), misidentified leptons (Misid. bkgd.), mismeasured charge (Charge mismeas. bkgd.) and the total background (Total bkgd.) are shown together withthe number of events observed in data. The uncertainties shown are the statistical and systematic components, respectively.

Dielectron channel results after final optimization. The background predictions from prompt same-sign leptons, misidentified leptons, and mismeasured charge are shown along with the total background estimate and the number of events observed in data. The uncertainties shown are the statistical and systematic components, respectively.

Electron-muon channel results after final optimization. The background predictions from prompt same-sign leptons and misidentified leptons are shown along with the total background estimate and the number of events observed in data. The uncertainties shown are the statistical and systematic components, respectively.