The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The observed exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.

The expected exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.

The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

Model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.

Expected model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.

Model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.

Expected model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.

The distributions of $S$ in SRA-TW. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $\it{m}^{\mathrm{R=1.2}}_{1}$ in SRB-TT. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of R$_{ISR}$ in SRC signal regions before R$_{ISR}$ cuts are applied. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD0. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD1. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD2. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TT. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TW. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-T0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (700,400)\ \mathrm{GeV} $ in signal regions SRB-TT, SRB-TW and SRB-T0. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 60000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (500,327)\ \mathrm{GeV} $ in regions SRC-1, SRC-2, SRC-3, SRC-4 and SRC-5. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 150000 raw MC events with filter efficiency of 0.384 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD1. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD2. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Signal acceptance in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.

Signal acceptance in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.

Signal efficiency in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.

Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.

Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).

Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).

Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.

Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.

Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.

Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.

Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).

Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).

Model dependent upper limits on cross-section (fb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).

Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.

Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.

The generator-level acceptance after reconstruction, for selecting and reconstructing charginos as a function of the chargino $eta$ and chargino decay radius (at generator level).

The generator-level acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.

The generator-level acceptance after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level).

The generator-level acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.

Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.

Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.

The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.

The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.

Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.

Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anticorrelation between different backgrounds.

Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracket background events is small.

Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.

The covariance matrix containing the statistical uncertainties of Figure 2a is shown.

The covariance matrix containing the experimental uncertainties of Figure 2a is shown.

The covariance matrix containing the model uncertainties of Figure 2a is shown.

The covariance matrix containing the statistical uncertainties of Figure 2b is shown.

The covariance matrix containing the experimental uncertainties of Figure 2b is shown.

The covariance matrix containing the model uncertainties of Figure 2b is shown.

Event yields for a simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ sample with $m_a = 17.5\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. Cut 0 corresponds to the initial number of events. Cut 1 requires the single lepton trigger. Cut 2 requires 2 identified leptons. Cut 3 requires the Z-boson mass window. Cut 4 requires 2 reconstructed $a\to b\bar{b}$ candidates. Cut 5a requires 2 identified $a\to b\bar{b}$ candidates in the 1HPC1LPC region. Cut 6a requires the 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region to be inside the Higgs mass window. Cut 5b requires 2 identified $a\to b\bar{b}$ candidates in the 2HPC region. Cut 6b requires the 2 $a\to b\bar{b}$ candidates in the 2HPC region to be inside the Higgs mass window.

Background yield table for Z+jets, $t\bar{t}$, and rare sources. Observed data yield. Signal $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ yield with $m_a = 20\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$, with a branching ratio set to 1 for the $H \rightarrow aa$ decay, whereas the ATLAS figure attached to this entry instead uses the upper-limit branching ratio (smaller than 1). The table includes the yields in two signal regions with leptons consistent with an on-shell Z-boson decay, one with 2 $a\to b\bar{b}$ candidates in the 2HPC region and one with 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region. The table also includes the yields in four control regions, one with leptons consistent with an on-shell Z-boson decay and 2 $a\to b\bar{b}$ candidates in the Low Purity Category (LPC), and three others where the leptons are not consistent an on-shell Z-boson decay.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production

Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.

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

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

The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.

Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.

Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.

Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.

The measured inclusive fiducial cross section measurements. The WW fiducial region is defined by requiring two same-sign leptons with $p_{T}>20$, $|\eta|<2.5$, and $m_{ll}>20$, and two jets with $m_{jj}>500$ and $|\Delta \eta_{jj}|>2.5$. The jets at generator level are clustered from stable particles, excluding neutrinos, using the anti-kt clustering algorithm with R = 0.4, and are required to have $p_{T}>50$ and $|\eta|<4.7$. The jets within $\Delta R<0.4$ of the selected charged leptons are not included. The WZ fiducial region is defined by requiring three leptons with $p_{T}>20$, $|\eta|<2.5$, a pair of opposite charge same-flavor lepton pair with $|m_{ll}-m_{Z}|<15$, and two jets with $m_{jj}>500$ and $|\Delta \eta_{jj}|>2.5$.

Distributions of $m_{jj}$ in the WW signal region.

Distributions of $m_{ll}$ in the WW signal region.

Distributions of $m_{jj}$ in the WZ signal region.

Distributions of BDT score in the WZ signal region.

Absolute WW cross section in $m_{jj}$ bins.

Normalized WW cross section in $m_{jj}$ bins.

Absolute WW cross section in $m_{ll}$ bins.

Normalized WW cross section in $m_{ll}$ bins.

Absolute WW cross section in $p_{T}^{l max}$ bins.

Normalized WW cross section in $p_{T}^{l max}$ bins.

Absolute WZ cross section in $m_{jj}$ bins.

Normalized WZ cross section in $m_{jj}$ bins.

Distributions of $m_{T}^{WW}$ in the WW signal region.

Distributions of $m_{T}^{WZ}$ in the WZ signal region.

Observed and expected lower and upper 95\% confidence level limits in TeV$^{-4}$ on the parameters of the quartic, obtained without using any unitarization procedure.

Observed and expected lower and upper 95\% confidence level limits in TeV$^{-4}$ on the parameters of the quartic by cutting the EFT expansion at the unitarity limit.

Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.

Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.

Track multiplicity $n_{Tracks}$ for preselected DVs in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

The observed event yields in the control, validation and signal regions are shown for the MET Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.

The observed event yields in the control, validation and signal regions are shown for the Muon Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.

Expected exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Expected (1 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Expected (2 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed (+1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed (-1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Exclusion limits on the production cross section as a function of m($\tilde{t}$) are shown for several values of $\tau(\tilde{t})$ along with the nominal signal production cross section and its theoretical uncertainty.

Parameterized event selection efficiencies for the $E_{T}^{miss}$ Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.

Parameterized event selection efficiencies for the Muon Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.

Parameterized muon-level reconstruction efficiencies as a function of the muon $p_{T}$ and $d_{0}$. The muon-level efficiencies are extracted using muons passing the muon acceptance criteria.

Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated independent of the muons originating from this truth vertex.

Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated only for truth vertices which have a muon originating from them which is matched to a reconstructed muon.

The $p_{T}$ distribution of all muons originating from LLP decays in the samples used to calculate and validate the efficiencies.

The invariant mass and multiplicity of selected decay products of all truth vertices used in the calculation and validation of the reconstructed efficiencies.

Observed yields and pre-fit background predictions for Njets 8-9.

Observed yields and pre-fit background predictions for Njets >=10.

Observed yields and pre-fit background predictions for aggregated bins.

Pre-fit background covariance matrix $\sigma_{xy}$ for the 174 analysis bins.

Pre-fit background correlation matrix $\rho_{xy}$ for the 174 analysis bins.

Observed yields and post-fit background predictions for Njets 2-3.

Observed yields and post-fit background predictions for Njets 4-5.

Observed yields and post-fit background predictions for Njets 6-7.

Observed yields and post-fit background predictions for Njets 8-9.

Observed yields and post-fit background predictions for Njets >=10.

Simulated signal yields for representative gluino signal model light-LSP points in the aggregate search regions. The uncertainties shown are statistical.

Simulated signal yields for representative gluino signal model compressed points in the aggregate search regions. The uncertainties shown are statistical.

Simulated signal yields for representative squark signal model light-LSP points in the aggregate search regions. The uncertainties shown are statistical.

Simulated signal yields for representative squark signal model compressed points in the aggregate search regions. The uncertainties shown are statistical.

The 95% CL observed and expected upper limits on the production cross sections of the T1tttt signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T1bbbb signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T1qqqq signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T5qqqqVV signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T2tt signal model as a function of the top squark and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T2bb signal model as a function of the bottom squark and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T2qq signal model as a function of the LSP and light squark masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

The observed significance of the SMS models for T1tttt as function of the gluino and LSP masses.

The observed significance of the SMS models for T1bbbb as function of the gluino and LSP masses.

The observed significance of the SMS models for T1qqqq as function of the gluino and LSP masses.

The observed significance of the SMS models for T5qqqqVV as function of the gluino and LSP masses.

The observed significance of the SMS models for T2tt as function of the top squark and LSP masses.

The observed significance of the SMS models for T2bb as function of the bottom squark and LSP masses.

The observed significance of the SMS models for T2qq as function of the LSP and light squark masses.

The efficiency times acceptance of the SMS models for T1tttt as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T1bbbb as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T1qqqq as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T5qqqqVV as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T2tt as function of the top squark and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T2bb as function of the bottom squark and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T2qq as function of the LSP and light squark masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for four representative gluino pair production signal models with m(gluino) >> m(LSP). Only statistical uncertainties are shown.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for four representative gluino pair production signal models with m(gluino) ~ m(LSP). Only statistical uncertainties are shown.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for three representative squark pair production signal models with m(squark) >> m(LSP). Only statistical uncertainties are shown.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for three representative squark pair production signal models with m(squark) ~ m(LSP). Only statistical uncertainties are shown.

Transverse mass $m_T$ spectrum at midrapidity of $\phi$ mesons produced in minimum bias p+p collisions at beam momentum of 158 GeV/c. $m_0$ is the PDG mass of the $\phi$ meson.

Transverse mass $m_T$ spectrum at midrapidity of $\phi$ mesons produced in minimum bias p+p collisions at beam momentum of 80 GeV/c. $m_0$ is the PDG mass of the $\phi$ meson.

Dependence of the slope parameter $T$ of the transverse momentum spectrum on rapidity $y$, of $\phi$ mesons produced in minimum bias p+p collisions at beam momentum of 158 GeV/c.

Dependence of the slope parameter $T$ of the transverse momentum spectrum on rapidity $y$, of $\phi$ mesons produced in minimum bias p+p collisions at beam momentum of 80 GeV/c.

Dependence of the width $\sigma_y$ of the rapidity distributions on $p_T$, of $\phi$ mesons produced in minimum bias p+p collisions at beam momentum of 158 GeV/c.

Dependence of the width $\sigma_y$ of the rapidity distributions on $p_T$, of $\phi$ mesons produced in minimum bias p+p collisions at beam momentum of 80 GeV/c.

Rapidity spectrum of $\phi$ mesons produced in minimum bias p+p collisions at beam momentum of 158 GeV/c.

Rapidity spectrum of $\phi$ mesons produced in minimum bias p+p collisions at beam momentum of 80 GeV/c.

Rapidity spectrum of $\phi$ mesons produced in minimum bias p+p collisions at beam momentum of 40 GeV/c.

Energy dependence of ratios of total yields of $\phi$ mesons to mean total yields of pions produced in in minimum bias p+p collisions at CERN SPS energies.

Energy dependence of double ratios of total yields of $\phi$ mesons to mean total yields of pions in central Pb+Pb collisions over minimum bias p+p collisions at CERN SPS energies.

Energy dependence of total yields of $\phi$ mesons produced in minimum bias p+p collisions at CERN SPS energies.

Energy dependence of midrapidity yields of $\phi$ mesons produced in minimum bias p+p collisions at CERN SPS energies.

Widths of rapidity distributions of $\phi$ mesons produced in minimum bias p+p collisions at CERN SPS energies, as a function of beam rapidity.

The $L_{T}$ distribution in the MisID-enriched region. The last bin contains the overflow events.

The $L_{T}+p^{miss}_{T}$ distribution in the 3L below-Z signal region. The last bin contains the overflow events.

The $M_{T}$ distribution in the 3L on-Z signal region. The last bin contains the overflow events.

The $L_{T}+p^{miss}_{T}$ distribution in the 3L above-Z signal region. The last bin contains the overflow events.

The $L_{T}+p^{miss}_{T}$ distribution in the 3L OSSF0 signal region. The last bin contains the overflow events.

The $L_{T}+p^{miss}_{T}$ distribution in the 4L OSSF0 signal region. The last bin contains the overflow events.

The $L_{T}+p^{miss}_{T}$ distribution in the 4L OSSF1 signal region. The last bin contains the overflow events.

The $L_{T}+p^{miss}_{T}$ distribution in the 4L OSSF2 signal region. The last bin contains the overflow events.

The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 4L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 4L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 4L(ee) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 4L(ee) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 4L(ee) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 4L(ee) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 4L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 4L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 4L($\mu\mu$) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 4L($\mu\mu$) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 4L($\mu\mu$) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 4L($\mu\mu$) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The 95% confidence level exclusion limits for the flavor-democratic scenario on the total production cross section of heavy fermion pairs.

The 95% confidence level exclusion limits on the product of the total production cross section of tt$\phi$(S) and $\mathcal{B}(\phi - {ee})$.

The 95% confidence level exclusion limits on the product of the total production cross section of tt$\phi$(PS) and $\mathcal{B}(\phi - {ee})$.

The 95% confidence level exclusion limits on the product of the total production cross section of tt$\phi$(S) and $\mathcal{B}(\phi - {\mu\mu})$.

The 95% confidence level exclusion limits on the product of the total production cross section of tt$\phi$(PS) and $\mathcal{B}(\phi - {\mu\mu})$.

The 95% confidence level exclusion limits on $g_{t}^2\mathcal{B}(\phi - {ee})$ for tt$\phi$(S).

The 95% confidence level exclusion limits on $g_{t}^2\mathcal{B}(\phi - {ee})$ for tt$\phi$(PS).

The 95% confidence level exclusion limits on $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$ for tt$\phi$(S).

The 95% confidence level exclusion limits on $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$ for tt$\phi$(PS).

Product of the fiducial acceptance and the event selection efficiency for the type-III Seesaw signal model at various signal mass hypotheses calculated after all analysis selection requirements.

Product of the fiducial acceptance and the event selection efficiency for the tt$\phi$ signal models at various signal mass hypotheses calculated after all analysis selection requirements.

The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.

The observed 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.

The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.

Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.

Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.

Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.

Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.

Signal acceptance in SR highMass for combined stau final states

Signal acceptance in SR lowMass for combined stau final states

Signal efficiency in SR highMass for combined stau final states

Signal efficiency in SR lowMass for combined stau final states

Signal acceptance*efficiency in SR highMass for combined stau final states

Signal acceptance*efficiency in SR lowMass for combined stau final states

Cutflow for two reference points (${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production) in SR. The column labelled $N_{weighted}$ shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$, while $N_{raw}$ in brackets shows the results for the generated number of events. The quoted uncertainties are statistical only. The "Generator filter" includes the requirements that two $\tau$ in the event have ${p}_{T} > 15$ GeV and $|\eta| <$ 2.6. The "Baseline Cut" includes the requirement of two baseline $\tau$ with a minimum value at 0.01 of the boosted decision tree discriminant (JetBDTSigTransMin $>$ 0.01) and ${p}_{T, \tau_{1}} > 50$ GeV and ${p}_{T, \tau_{2}} > 40$ GeV. At the step "Trigger & offline cuts", the following requirements are applied: the event is recorded using the asymmetric di-$\tau$ trigger (di-$\tau$ $E_{T}^{miss}$ trigger) in SR-lowMass (SR-highMass), and the lepton $p_{T}$ and $E_{T}^{miss}$ are required at plateau.

Observed and expected numbers of events in the control and signal regions where all control and signal region bins are included as constraints in the likelihood. The expected event yields of SM processes are given after the background-only fit. The entries marked as "--" are negligible. The uncertainties correspond to the sum in quadrature of statistical and systematic uncertainties. The correlation of systematic uncertainties among control regions and among background processes is fully taken into account.

The post-fit $m_{T2}$ distribution for SR-lowMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.

The post-fit $m_{T2}$ distribution for SR-highMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.

The $m_{T2}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.

The $m_{T2}$ post-fit distributions in the multi-jet background validation VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.

The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.

The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.

The pre-fit $m_{T2}$ distribution in the $WCR$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is estimated from data using the OS--SS method. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.

The post-fit yields in the $WVR$, $TVRs$, $ZVRs$ and $VVVRs$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is negligible and is estimated from data using the ABCD method, using CRs obtained with the same technique used for the SRs. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate.

$\mathrm{M_{\mathrm{T}}}$ distribution for the $\mathrm{e}\mu$ control region.

$\mathrm{M_{\mathrm{T}}}$ distribution for the WZ control region.

$\mathrm{M_{\mathrm{T}}}$ distribution for the ZZ control region.

$\mathrm{M_{\mathrm{T}}}$ distribution for the signal region, events with $|\eta_{\gamma}|<1$.

$\mathrm{M_{\mathrm{T}}}$ distribution for the signal region, events with $|\eta_{\gamma}|>1$.

Muon reconstruction, identification, and isolation efficiency as a function of $|\eta|$ and $\mathrm{p_\mathrm{T}}$.

Electron reconstruction, identification, and isolation efficiency as a function of $|\eta|$ and $\mathrm{p_\mathrm{T}}$.

Photon efficiency as a function of $|\eta|$ and $\mathrm{p_\mathrm{T}}$.

Covariance matrix for all bins used in the analysis. There are 45 bins in total, 15 for every data-taking year. For every year, the first bin corresponds to events in the $\mathrm{e}\mu$ control region, the following five bins correspond to events with $|\eta^\gamma|< 1$ in the signal region, the next five bins correspond to events with $|\eta^\gamma|> 1$ in the signal region, the next two bins correspond to events in the WZ control region, and finally the last two bins correspond to events in the ZZ control region.

The observed upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed.

The observed upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed.

The observed and expected upper limits at $95\%$ CL on the gluino pair production cross section for a gluino GMSB model with $m_{\tilde{g}}=2400$ GeV. The one (two) standard deviation variation in the expected limit is shown in the inner green (outer yellow) band. The blue solid line shows the observed limit obtained by the CMS displaced jet search

The distribution (normalized to unity) of number of ECAL cells hit in the jet for jets in a background enriched data sample (satisfying $|\eta| < 1.48$, $PV_{\rm track}^{\rm fraction} > 1/12$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets satisfying signal region requirements (except those on $E_{\mathrm{ECAL}}$ and $N^{\mathrm{cell}}_{\mathrm{ECAL}}$).

The distribution (normalized to unity) of $\mathrm{HEF}$ for a data sample enriched in beam halo and noise jets (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30 \,\mathrm{GeV}$, $PV_{\rm track}^{\rm fraction} < 1/12$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$) and for signal jets passing signal region selections (except on $\mathrm{HEF}$).

The distribution (normalized to unity) of $E_{\mathrm{HCAL}}$ for a data sample enriched in beam halo and noise jets (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30 \,\mathrm{GeV}$, $PV_{\rm track}^{\rm fraction} < 1/12$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$) and for signal jets passing signal region selections (except on $E_{\mathrm{HCAL}}$).

The distribution (normalized to unity) of $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ for data sample enriched in jets from noise (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $PV_{\rm track}^{\rm fraction} > 1/12$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20 \,\mathrm{GeV}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets passing signal region selections (except on $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ and $t^{\mathrm{RMS}}_\mathrm{jet}$)

The distribution (normalized to unity) of $t^{\mathrm{RMS}}_\mathrm{jet}$ for data sample enriched in jets from noise (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $PV_{\rm track}^{\rm fraction} > 1/12$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20 \,\mathrm{GeV}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets passing signal region selections (except on $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ and $t^{\mathrm{RMS}}_\mathrm{jet}$)

The distribution (normalized to unity) of $PV_{\rm track}^{\rm fraction}$ for a data sample enriched in main bunch backgrounds (satisfying $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $|t_{\mathrm{jet}}| < 3\,\mathrm{ns}$ and $E_{\mathrm{ECAL}} >20\,\mathrm{GeV}$) and for signal jets passing signal selections (except on $PV_{\rm track}^{\rm fraction}$).

The distribution (normalized to unity) of $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}}$ for a data sample enriched in beam halo (satisfying $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $PV_{\rm track}^{\rm fraction} < 1/12$, $\mathrm{HEF} < 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$ and $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$) and for signal jets passing signal selections (except on $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}}$)

The distribution (normalized to unity) of $\mathrm{max}(\Delta \phi_{\mathrm{DT}})$ for a data sample enriched in cosmic muons (satisfying $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $PV_{\rm track}^{\rm fraction} < 1/12$, $\mathrm{HEF} > 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} > 3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and failing the HCAL noise rejection quality filters) and for signal jets passing signal selections (except on $\mathrm{max}(\Delta \phi_{\mathrm{DT}})$).

The distribution (normalized to unity) of $\mathrm{max}(\Delta \phi_{\mathrm{RPC}})$ for a data sample enriched in cosmic muons (satisfying $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $PV_{\rm track}^{\rm fraction} < 1/12$, $\mathrm{HEF} > 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} > 3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and failing the HCAL noise rejection quality filters) and for signal jets passing signal selections (except on $\mathrm{max}(\Delta \phi_{\mathrm{RPC}})$).

Distribution of $t_{\mathrm{jet}}$ for jets with the full Run 2 dataset with no cleaning selection applied (a) and after all jet cleaning selections are applied (b) in events satisfying the trigger requirements and satisfying $p_T^\mathrm{miss} > 300$. The jets are required to pass an inverted selection of $PV_{\rm track}^{\rm fraction} > 1/12$ to enrich the sample in those originating from main and satellite bunch backgrounds. The cleaning selections are shown to reduce the backgrounds by many orders of magnitude.

Distribution of $t_{\mathrm{jet}}$ for jets with the full Run 2 dataset in events satisfying the trigger requirements and satisfying $p_T^\mathrm{miss} < 300$. The jets are required to pass an inverted selection of $PV_{\rm track}^{\rm fraction} > 1/12$ to enrich the sample in those originating from main and satellite bunch backgrounds (all other jet cleaning selections are applied). Clear contributions from jets from satellite bunch collisions can be seen peaked around -5, 5 and 10 ns.

Contribution to the delayed time of jets from the $\beta$ of the gluino is plotted against the delay contribution from the difference (assuming straight line paths) between the path taken by the gluino and the particle forming the jet from the path length for a particle travelling directly to the same position on the ECAL barrel for gluino $c\tau_{0} = 10$ m and mass of 1000 Gev (top) and 3000 GeV (bottom). The dominant contribution is shown to be the gluino $\beta$.

Selection efficiencies for the GMSB model with $m_{\tilde{g}}=1000$ and various proper decay lengths

Selection efficiencies for the GMSB model with $m_{\tilde{g}}=2400$ and various proper decay lengths

Selection efficiencies for the GMSB model with $m_{\tilde{g}}=3000$ and various proper decay lengths

The observed upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.

The expected upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.

The expected plus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.

The expected minus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.

The expected upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.

The expected plus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.

The expected minus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.

Expected and observed events in the 16 discovery regions along with the according control regions.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the MS-agnostic R-hadron search.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector R-hadron search.

p0-values and model-independent upper limits on cross-section x acceptance x efficiency for the 16 discovery regions.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the MS-agnostic search for metastable gluino R-hadrons.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector direct-stau search.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector chargino search.

Upper cross-section limit in gluino R-hadron search.

Upper cross-section limit in sbottom R-hadron search.

Upper cross-section limit in stop R-hadron search.

Upper cross-section limit in stau search.

Upper cross-section limit in chargino search.

Lower mass limit as function of gluino lifetime.

Acceptance x efficiency, acceptance and efficiency for the full range of simulated masses in the MS-agnostic R-hadron search.

Upper cross-section limit in meta-stable gluino R-hadron search.

Flavor composition of 800 GeV stop R-hadrons simulated using the generic model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV anti-stop R-hadrons simulated using the generic model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV stop R-hadrons simulated using the Regge model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV anti-stop R-hadrons simulated using the Regge model as a function of radial distance from the interaction point.

ETmiss trigger efficiency as function of true ETmiss (EtmissTurnOn).

Single-muon trigger efficiency as function of $|\eta|$ and $\beta$ (SingleMuTurnOn).

Candidate reconstruction efficiency for ID+Calo selection (IDCaloEff).

Candidate reconstruction efficiency for loose selection (LooseEff).

Efficiency for a loose candidate to be promoted to a tight candidate (TightPromotionEff).

Resolution and average of reconstructed dE/dx mass for a given simulated mass for ID+calo candidates.

Resolution and average of reconstructed ToF mass for a given simulated mass for ID+calo candidates.

Resolution and average of reconstructed ToF mass for a given simulated mass for FullDet candidates.

Summary of typical systematic uncertainties for the signal.

Numbers of observed events for all signal regions, including predicted background contributions and expected signal yields.

Limits on anomalous quartic couplings at 95% CL.

Expected and observed 95% CL upper limits on the cross section times the branching ratio sigma(P P --> W+- a)B(a --> W+- W-+) as a function of ALP mass

Expected and observed 95% CL upper limits on the photophobic ALP model parameter 1/f_a as a function of ALP mass.

Observed signal strength, and observed signal cross section.