Observed 95% CL exclusion contours in the $(m_{N_R}, m_{W_R})$ plane in the muon channel.

Expected 95% exclusion contours in the HVT parameter space $\{g_q,g_l\}$ with $g_h$ set to zero for a resonance masses of 3 TeV for the dilepton channel. The area outside the curves is excluded.

Observed 95% exclusion contours in the HVT parameter space $\{g_h,g_f\}$ with $g_f\equiv g_l=g_q$ for a resonance mass of 4 TeV for the dilepton channel. The area outside the curves is excluded.

Observed 95% exclusion contours in the HVT parameter space $\{g_q,g_l\}$ with $g_h$ set to zero for a resonance mass of 4 TeV for the dilepton channel. The area outside the curves is excluded.

Expected 95% exclusion contours in the HVT parameter space $\{g_h,g_f\}$ with $g_f\equiv g_l=g_q$ for a resonance mass of 4 TeV for the dilepton channel. The area outside the curves is excluded.

Expected 95% exclusion contours in the HVT parameter space $\{g_q,g_l\}$ with $g_h$ set to zero for a resonance masses of 4 TeV for the dilepton channel. The area outside the curves is excluded.

Observed 95% exclusion contours in the HVT parameter space $\{g_h,g_f\}$ with $g_f\equiv g_l=g_q$ for a resonance mass of 5 TeV for the dilepton channel. The area outside the curves is excluded.

Observed 95% exclusion contours in the HVT parameter space $\{g_q,g_l\}$ with $g_h$ set to zero for a resonance mass of 5 TeV for the dilepton channel. The area outside the curves is excluded.

Expected 95% exclusion contours in the HVT parameter space $\{g_h,g_f\}$ with $g_f\equiv g_l=g_q$ for a resonance mass of 5 TeV for the dilepton channel. The area outside the curves is excluded.

Expected 95% exclusion contours in the HVT parameter space $\{g_q,g_l\}$ with $g_h$ set to zero for a resonance masses of 5 TeV for the dilepton channel. The area outside the curves is excluded.

Distribution of the dielectron invariant mass for events passing the full selection.

Distribution of the dimuon invariant mass for events passing the full selection.

Expected upper limits at 95% CL on the fiducial cross-section times branching ratio as a function of pole mass for the zero-width, 0.5%, 1.2%, 3%, 6% and 10% relative width signals for the dielectron channel.

Expected upper limits at 95% CL on the fiducial cross-section times branching ratio as a function of pole mass for the zero-width, 0.5%, 1.2%, 3%, 6% and 10% relative width signals for the combined dilepton channel.

Expected upper limits at 95% CL on the fiducial cross-section times branching ratio as a function of pole mass for the zero-width, 0.5%, 1.2%, 3%, 6% and 10% relative width signals for the dimuon channel.

Observed upper limits at 95% CL on the fiducial cross-section times branching ratio as a function of pole mass for the zero-width, 0.5%, 1.2%, 3%, 6% and 10% relative width signals for the dielectron channel.

Observed upper limits at 95% CL on the fiducial cross-section times branching ratio as a function of pole mass for the zero-width, 0.5%, 1.2%, 3%, 6% and 10% relative width signals for the combined dilepton channel.

Observed upper limits at 95% CL on the fiducial cross-section times branching ratio as a function of pole mass for the zero-width, 0.5%, 1.2%, 3%, 6% and 10% relative width signals for the dimuon channel.

Ratio of the observed limit to the Z'$_\mathrm{SSM}$ cross-section for the combination of the dielectron and dimuon channels. A number of previous ATLAS results at $\sqrt{s}$ = 7, 8, and 13 TeV are compared to the current search.

Description of the $m_{\ell\ell}^{\mathrm{true}}$-dependence for the seven relative mass resolution parameters in the dielectron channel.

Description of the $m_{\ell\ell}^{\mathrm{true}}$-dependence for the seven relative mass resolution parameters in the dimuon channel.

Dielectron and dimuon selection efficiency as a function of pole mass for spin-0, spin-1 and spin-2 resonances. Drell-Yan MC samples are used for the spin-1 efficiencies and correspond to the zero-width signal hypothesis. Spin-0 (spin-2) efficiencies are obtained from dedicated MC samples with relative widths in the range of 0-20% (1-13%) and are averaged over all available width assumptions.

Measured and expected differential cross-section $\text{d}\sigma / \text{d} m_{4l}$ as a function of $m_{4l}$ in bin of 50$< p_{T}^{4l} <$100 GeV

Measured and expected differential cross-section $\text{d}\sigma / \text{d} m_{4l}$ as a function of $m_{4l}$ in bin of 100$< p_{T}^{4l} <$600 GeV

Measured and expected double differential cross-section $\text{d}\sigma / \text{d} m_{4l}$ as a function of $m_{4l}$ in bin of 0.0$< y_{4l} <$0.4

Measured and expected double differential cross-section $\text{d}\sigma / \text{d} m_{4l}$ as a function of $m_{4l}$ in bin of 0.4$< y_{4l} <$0.8

Measured and expected double differential cross-section $\text{d}\sigma / \text{d} m_{4l}$ as a function of $m_{4l}$ in bin of 0.8$< y_{4l} <$1.2

Measured and expected double differential cross-section $\text{d}\sigma / \text{d} m_{4l}$ as a function of $m_{4l}$ in bin of 1.2$< y_{4l} <$2.5

Measured and expected double differential cross-section $\text{d}\sigma / \text{d} m_{4l}$ as a function of $m_{4l}$ for MELA$<$1.4 bin

Measured and expected double differential cross-section $\text{d}\sigma / \text{d} m_{4l}$ as a function of $m_{4l}$ for MELA$>$1.4 bin

Measured and expected double differential cross-section $\text{d}\sigma / \text{d} m_{4l}$ as a function of $m_{4l}$ for $\mu\mu\mu\mu$ events

Measured and expected double differential cross-section $\text{d}\sigma / \text{d} m_{4l}$ as a function of $m_{4l}$ for $eeee$ events

Measured and expected double differential cross-section $\text{d}\sigma / \text{d} m_{4l}$ as a function of $m_{4l}$ for $ee\mu\mu$ events

Systematic covariance matrix for the differential $m_{4l}$ distribution.

Statistical covariance matrix for the differential $m_{4l}$ distribution.

Background covariance matrix for the differential $m_{4l}$ distribution.

Systematic covariance matrix for the differential $m_{4l}$-$p_{T}^{4l}$ distribution.<br><br> Bins labelled 1-9 correspond to the 0$< p_{T}^{4l} < $20 GeV bin with $m_{4l}$ values as listed in Table 2.<br> Bins labelled 10-16 correspond to the 20$< p_{T}^{4l} <$50 GeV bin with $m_{4l}$ values as listed in Table 3.<br> Bins labelled 17-23 correspond to the 50$< p_{T}^{4l} <$100 GeV bin with $m_{4l}$ values as listed in Table 4.<br> Bins labelled 24-30 correspond to the 100$< p_{T}^{4l} <$600 GeV bin with $m_{4l}$ values as listed in Table 5.

Statistical covariance matrix for the differential $m_{4l}$-$p_{T}^{4l}$ distribution. <br><br> Bins labelled 1-9 correspond to the 0$< p_{T}^{4l} < $20 GeV bin with $m_{4l}$ values as listed in Table 2.<br> Bins labelled 10-16 correspond to the 20$< p_{T}^{4l} <$50 GeV bin with $m_{4l}$ values as listed in Table 3.<br> Bins labelled 17-23 correspond to the 50$< p_{T}^{4l} <$100 GeV bin with $m_{4l}$ values as listed in Table 4.<br> Bins labelled 24-30 correspond to the 100$< p_{T}^{4l} <$600 GeV bin with $m_{4l}$ values as listed in Table 5.

Background covariance matrix for the differential $m_{4l}$-$p_{T}^{4l}$ distribution. <br><br> Bins labelled 1-9 correspond to the 0$< p_{T}^{4l} < $20 GeV bin with $m_{4l}$ values as listed in Table 2.<br> Bins labelled 10-16 correspond to the 20$< p_{T}^{4l} <$50 GeV bin with $m_{4l}$ values as listed in Table 3.<br> Bins labelled 17-23 correspond to the 50$< p_{T}^{4l} <$100 GeV bin with $m_{4l}$ values as listed in Table 4.<br> Bins labelled 24-30 correspond to the 100$< p_{T}^{4l} <$600 GeV bin with $m_{4l}$ values as listed in Table 5.

Systematic covariance matrix for the differential $m_{4l}$-$y_{4l}$ distribution. <br><br> Bins labelled 1-9 correspond to the 0.0$< y_{4l} < $0.4 bin with $m_{4l}$ values as listed in Table 6.<br> Bins labelled 10-18 correspond to the 0.4$< y_{4l} <$0.8 bin with $m_{4l}$ values as listed in Table 7.<br> Bins labelled 19-26 correspond to the 0.8$< y_{4l} <$1.2 bin with $m_{4l}$ values as listed in Table 8.<br> Bins labelled 27-34 correspond to the 1.2$< y_{4l} <$2.5 bin with $m_{4l}$ values as listed in Table 9.

Statistical covariance matrix for the differential $m_{4l}$-$y_{4l}$ distribution. <br><br> Bins labelled 1-9 correspond to the 0.0$< y_{4l} < $0.4 bin with $m_{4l}$ values as listed in Table 6.<br> Bins labelled 10-18 correspond to the 0.4$< y_{4l} <$0.8 bin with $m_{4l}$ values as listed in Table 7.<br> Bins labelled 19-26 correspond to the 0.8$< y_{4l} <$1.2 bin with $m_{4l}$ values as listed in Table 8.<br> Bins labelled 27-34 correspond to the 1.2$< y_{4l} <$2.5 bin with $m_{4l}$ values as listed in Table 9.

Background covariance matrix for the differential $m_{4l}$-$y_{4l}$ distribution. <br><br> Bins labelled 1-9 correspond to the 0.0$< y_{4l} < $0.4 bin with $m_{4l}$ values as listed in Table 6.<br> Bins labelled 10-18 correspond to the 0.4$< y_{4l} <$0.8 bin with $m_{4l}$ values as listed in Table 7.<br> Bins labelled 19-26 correspond to the 0.8$< y_{4l} <$1.2 bin with $m_{4l}$ values as listed in Table 8.<br> Bins labelled 27-34 correspond to the 1.2$< y_{4l} <$2.5 bin with $m_{4l}$ values as listed in Table 9.

Systematic covariance matrix for the differential $m_{4l}$-MELA distribution. <br><br> Bins labelled 1-7 correspond to the MELA$<$ 0.4 bin with $m_{4l}$ values as listed in Table 10.<br> Bins labelled 8-12 correspond to the MELA$>$ 0.4 bin with $m_{4l}$ values as listed in Table 11.

Statistical covariance matrix for the differential $m_{4l}$-MELA distribution. <br><br> Bins labelled 1-7 correspond to the MELA$<$ 0.4 bin with $m_{4l}$ values as listed in Table 10.<br> Bins labelled 8-12 correspond to the MELA$>$ 0.4 bin with $m_{4l}$ values as listed in Table 11.

Background covariance matrix for the differential $m_{4l}$-MELA distribution. <br><br> Bins labelled 1-7 correspond to the MELA$<$ 0.4 bin with $m_{4l}$ values as listed in Table 10.<br> Bins labelled 8-12 correspond to the MELA$>$ 0.4 bin with $m_{4l}$ values as listed in Table 11.

Systematic covariance matrix for the differential $m_{4l}$-lepton flavour distribution. <br><br> Bins labelled 1-9 correspond to $\mu\mu\mu\mu$ events with $m_{4l}$ values as listed in Table 12.<br> Bins labelled 10-18 correspond to $eeee$ events with $m_{4l}$ values as listed in Table 13.<br> Bins labelled 19-27 correspond to $\mu\mu\mu\mu$ events with $m_{4l}$ values as listed in Table 14.<br>

Statistical covariance matrix for the differential $m_{4l}$-lepton flavour distribution. <br><br> Bins labelled 1-9 correspond to $\mu\mu\mu\mu$ events with $m_{4l}$ values as listed in Table 12.<br> Bins labelled 10-18 correspond to $eeee$ events with $m_{4l}$ values as listed in Table 13.<br> Bins labelled 19-27 correspond to $\mu\mu\mu\mu$ events with $m_{4l}$ values as listed in Table 14.<br>

Background covariance matrix for the differential $m_{4l}$-lepton flavour distribution. <br><br> Bins labelled 1-9 correspond to $\mu\mu\mu\mu$ events with $m_{4l}$ values as listed in Table 12.<br> Bins labelled 10-18 correspond to $eeee$ events with $m_{4l}$ values as listed in Table 13.<br> Bins labelled 19-27 correspond to $\mu\mu\mu\mu$ events with $m_{4l}$ values as listed in Table 14.<br>

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.

- - - - - - - - Overview of HEPData Record - - - - - - - - <br/><br/> <b>Lower mass requirement for signal regions.</b> <ul> <li><a href="86565?version=1&table=Table1">Gluinos and squarks</a></li> <li><a href="86565?version=1&table=Table2">Staus and charginos</a></li> </ul> <b>Discovery regions:</b> <ul> <li><a href="86565?version=1&table=Table3">Yields</a></li> <li><a href="86565?version=1&table=Table6">p0-values and limits</a></li> </ul> <b>Signal yield tables:</b> <ul> <li><a href="86565?version=1&table=Table4">MS-agnostic R-hadron search</a></li> <li><a href="86565?version=1&table=Table5">Full-detector R-hadron search</a></li> <li><a href="86565?version=1&table=Table7">MS-agnostic search for metastable gluino R-hadrons</a></li> <li><a href="86565?version=1&table=Table8">Full-detector direct-stau search</a></li> <li><a href="86565?version=1&table=Table9">Full-detector chargino search</a></li> </ul> <b>Limits:</b> <ul> <li><a href="86565?version=1&table=Table10">Gluino R-hadron search</a></li> <li><a href="86565?version=1&table=Table11">Sbottom R-hadron search</a></li> <li><a href="86565?version=1&table=Table12">Stop R-hadron search</a></li> <li><a href="86565?version=1&table=Table13">Stau search</a></li> <li><a href="86565?version=1&table=Table14">Chargino search</a></li> <li><a href="86565?version=1&table=Table15">Meta-stable gluino R-hadron search</a></li> <li><a href="86565?version=1&table=Table17">Meta-stable gluino R-hadron search</a></li> </ul> <b>Acceptance and efficiency:</b> <ul> <li><a href="86565?version=1&table=Table16">MS-agnostic R-hadron search</a></li> </ul> <b>Truth quantities:</b> <ul> <li><a href="86565?version=1&table=Table18">Flavor composition of 800 GeV stop R-hadrons simulated using the generic model</a></li> <li><a href="86565?version=1&table=Table19">Flavor composition of 800 GeV anti-stop R-hadrons simulated using the generic model</a></li> <li><a href="86565?version=1&table=Table20">Flavor composition of 800 GeV stop R-hadrons simulated using the Regge model</a></li> <li><a href="86565?version=1&table=Table21">Flavor composition of 800 GeV anti-stop R-hadrons simulated using the Regge model</a></li> </ul> <b>Reinterpretation material:</b> <ul> <li><a href="86565?version=1&table=Table22">ETmiss trigger efficiency as function of true ETmiss</a></li> <li><a href="86565?version=1&table=Table23">Single-muon trigger efficiency as function of |eta| and beta</a></li> <li><a href="86565?version=1&table=Table24">Candidate reconstruction efficiency for ID+Calo selection</a></li> <li><a href="86565?version=1&table=Table25">Candidate reconstruction efficiency for loose selection</a></li> <li><a href="86565?version=1&table=Table26">Efficiency for a loose candidate to be promoted to a tight candidate</a></li> <li><a href="86565?version=1&table=Table27">Resolution and average of reconstructed dE/dx mass for a given simulated mass for ID+calo candidates</a></li> <li><a href="86565?version=1&table=Table28">Resolution and average of reconstructed ToF mass for a given simulated mass for ID+calo candidates</a></li> <li><a href="86565?version=1&table=Table29">Resolution and average of reconstructed ToF mass for a given simulated mass for FullDet candidates</a></li> </ul> <p><b>Pseudo-code snippets</b> and <b>example SLHA setups</b> are available in the "Resources" linked on the left, and more detailed reinterpretation material is available at <a href="http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2016-32/hepdata_info.pdf">http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2016-32/hepdata_info.pdf</a>.</p>

Inclusive cross-section and uncertainty from each source, for the dominant process in the each measurement region.

Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the $ee jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $p_{T}^{\mu\mu}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $p_{T}^{\mu\mu}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $p_{T}^{e\mu}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $p_{T}^{e\mu}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $p_{T}^{ee}$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $p_{T}^{ee}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the extreme $eejj$ measurement region.

Event yields in the dimuon channel control regions with total uncertainties. The observed number of events is given in the first row. The background event numbers as obtained from the fit are shown together with the total uncertainties. The second row shows the total background expectation, the further rows show the breakdown into different background components.

Event yields in the dielectron channel control regions with total uncertainties. The observed number of events is given in the first row. The background event numbers as obtained from the fit are shown together with the total uncertainties. The second row shows the total background expectation, the further rows show the breakdown into different background components.

Dijet mass distribution for the b-tagged category. Data, estimated background and uncertainties are shown. Events are collected using the combined trigger and contain a $E_T^{\gamma} > 95$ GeV photon and two $p_T^{jet} > 65$ GeV jets.

Upper limits on Gaussian-shape contributions to the dijet mass distributions from the flavour-inclusive category and masses below 450 GeV, for which the single-photon trigger was used.

Upper limits on Gaussian-shape contributions to the dijet mass distributions from the flavour-inclusive category and masses above 450 GeV, for which the combined trigger was used.

Upper limits on Gaussian-shape contributions to the dijet mass distributions from the b-tagged category and masses below 450 GeV, for which the single-photon trigger was used.

Upper limits on Gaussian-shape contributions to the dijet mass distributions from the b-tagged category and masses above 450 GeV, for which the combined trigger was used.

Kinematic acceptance values predicted for the $Z'$ model as a function of mass $m_{Z'}$ for the flavour-inclusive category using the single-photon trigger.

Kinematic acceptance values predicted for the $Z'$ model as a function of mass $m_{Z'}$ for the flavour-inclusive category using the combined trigger.

Kinematic acceptance values predicted for the $Z'$ model as a function of mass $m_{Z'}$ for the b-tagged category using the single-photon trigger.

Kinematic acceptance values predicted for the $Z'$ model as a function of mass $m_{Z'}$ for the b-tagged category using the combined trigger.

Reconstruction efficiency for $Z'$ model, flavour inclusive category, single-photon trigger.

Reconstruction efficiency for $Z'$ model, flavour inclusive category, combined trigger.

Reconstruction efficiency for $Z'$ model, b-tagged category, single-photon trigger.

Reconstruction efficiency for $Z'$ model, b-tagged category, combined trigger.

Summary of the relative uncertainties in the measured fiducial cross section $\sigma^{\mathrm{fid}}_{W^\pm Z j j-EW}$ . The uncertainties are reported as percentages.

Numbers of observed and expected events in the $W^{\pm}Zjj$ signal region and in the three control regions, after the fit. The expected number of $WZjj-EW$ events from $SHERPA$ and the estimated number of background events from the other processes are shown. The sum of the background containing misidentified leptons is labelled "Misid. leptons". The total correlated post-fit uncertainties are quoted.

Measured $W^{pm}Zjj$ differential cross-section in the VBS fiducial phase space. The relative uncertainties are reported as percentages. The systematic uncertainties are in order of appearance: total uncorrelated systematic and correlated systematics related respectively to unfolding, electrons, muons, jets, reducible and irreducible backgrounds, pileup and luminosity. The last bin is a cross section for all events above the lower end of the bin.

Correlation matrix for the unfolded fiducial cross-section.

Measured $W^{pm}Zjj$ differential cross-section in the VBS fiducial phase space. The relative uncertainties are reported as percentages. The systematic uncertainties are in order of appearance: total uncorrelated systematic and correlated systematics related respectively to unfolding, electrons, muons, jets, reducible and irreducible backgrounds, pileup and luminosity. The last bin is a cross section for all events above the lower end of the bin.

Correlation matrix for the unfolded fiducial cross-section.

Measured $W^{pm}Zjj$ differential cross-section in the VBS fiducial phase space. The relative uncertainties are reported as percentages. The systematic uncertainties are in order of appearance: total uncorrelated systematic and correlated systematics related respectively to unfolding, electrons, muons, jets, reducible and irreducible backgrounds, pileup and luminosity.

Correlation matrix for the unfolded fiducial cross-section.

Measured $W^{pm}Zjj$ differential cross-section in the VBS fiducial phase space. The relative uncertainties are reported as percentages. The systematic uncertainties are in order of appearance: total uncorrelated systematic and correlated systematics related respectively to unfolding, electrons, muons, jets, reducible and irreducible backgrounds, pileup and luminosity. The last bin is a cross section for all events above the lower end of the bin.

Correlation matrix for the unfolded fiducial cross-section.

Measured $W^{pm}Zjj$ differential cross-section in the VBS fiducial phase space. The relative uncertainties are reported as percentages. The systematic uncertainties are in order of appearance: total uncorrelated systematic and correlated systematics related respectively to unfolding, electrons, muons, jets, reducible and irreducible backgrounds, pileup and luminosity. The last bin is a cross section for all events above the lower end of the bin.

Correlation matrix for the unfolded fiducial cross-section.

Measured $W^{pm}Zjj$ differential cross-section in the VBS fiducial phase space. The relative uncertainties are reported as percentages. The systematic uncertainties are in order of appearance: total uncorrelated systematic and correlated systematics related respectively to unfolding, electrons, muons, jets, reducible and irreducible backgrounds, pileup and luminosity.

Correlation matrix for the unfolded fiducial cross-section.

Measured $W^{pm}Zjj$ differential cross-section in the VBS fiducial phase space. The relative uncertainties are reported as percentages. The systematic uncertainties are in order of appearance: total uncorrelated systematic and correlated systematics related respectively to unfolding, electrons, muons, jets, reducible and irreducible backgrounds, pileup and luminosity. The last bin is a cross section for all events above the lower end of the bin.

Correlation matrix for the unfolded fiducial cross-section.

Measured $W^{pm}Zjj$ differential cross-section in the VBS fiducial phase space. The relative uncertainties are reported as percentages. The systematic uncertainties are in order of appearance: total uncorrelated systematic and correlated systematics related respectively to unfolding, electrons, muons, jets, reducible and irreducible backgrounds, pileup and luminosity. the last bin is a cross section for all events above the lower end of the bin.

Correlation matrix for the unfolded fiducial cross-section.

Data and SM predictions in SRs for the $1lb\bar{b}$ analysis for $E_{\mathrm{T}}^{\mathrm{miss}}$ in SR1Lbb-Medium. All SRs selections but the one on the quantity shown are applied. All uncertainties are included in the uncertainty band. Example SUSY models are superimposed for illustrative purposes.

Distributions of $m_{\gamma\gamma}$ before the final requirement on $m_{\gamma\gamma}$ in SR1Lyy-a. The expected contributions from both the peaking and non-peaking backgrounds are shown as stacked colored histograms. Two example SUSY models are superimposed for illustrative purposes.

Distributions of $m_{\gamma\gamma}$ before the final requirement on $m_{\gamma\gamma}$ in SR1Lyy-b. The expected contributions from both the peaking and non-peaking backgrounds are shown as stacked colored histograms. Two example SUSY models are superimposed for illustrative purposes.

Acceptance for $0lb\bar{b}$ SRHad-High signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $0lb\bar{b}$ SRHad-Low signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $1lb\bar{b}$ SR1Lbb-High signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $1lb\bar{b}$ SR1Lbb-Low signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $1lb\bar{b}$ SR1Lbb-Medium signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $1l\gamma\gamma$ signal region SR1Lyy-a. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $1l\gamma\gamma$ signal region SR1Lyy-b. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $3L$ DFOS signal region SR3L-DFOS-1Ja. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $3L$ DFOS signal region SR3L-DFOS-1Jb. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $3L$ DFOS signal region SR3L-DFOS-0J. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $3L$ SFOS signal region SR3L-SFOS-0Ja. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $3L$ SFOS signal region SR3L-SFOS-0Jb. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $3L$ SFOS signal region SR3L-SFOS-1J. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $l^{\pm}l^{\pm}$ signal region SRSS-j1. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $l^{\pm}l^{\pm}$ signal region SRSS-j23. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Event selection cutflow for SM background (pre-fit) and representative signal samples for the $0lb\bar{b}$ SR. The masses of next-lightest-neutralinos and LSPs are reported. Only statistical uncertainties are shown. The MC statistics for the signal samples is 50K and 44K events, respectively. Samples are produced with generator filters which selects $h \rightarrow b\bar{b}$ and $W \rightarrow qq'$ decays. ``All events" for SUSY scenarios represent the total number of signal events for the models considered taking into account the BR of $W \rightarrow qq'$ (0.674) and $h \rightarrow b\bar{b}$ (0.582).

Event selection cutflow for SM background (pre-fit) and representative signal samples for the $1lb\bar{b}$ channel. The masses of next-lightest-neutralinos and LSPs are reported. Only statistical uncertainties are shown. The MC statistics for the signal samples is 28K, 29K and 29K events, respectively. Samples are produced with generator filters which selects $h \rightarrow b\bar{b}$ and $W \rightarrow l \nu$ decays. ``All events" for SUSY scenarios represent the total number of signal events for the models considered taking into account the BR of $W \rightarrow l \nu$ (0.324) and $h \rightarrow b\bar{b}$ (0.582).

Event selection cutflow is presented for SM background (pre-fit) and three signal scenarios for the $1l\gamma\gamma$ channel SRs. The masses of next-lightest-neutralinos and LSPs are reported. The uncertainties only include statistical uncertainties. The MC statistics for the signal samples is 10K events in all cases. Samples are produced with generator filters which selects $h \rightarrow \gamma\gamma$ and $W \rightarrow l \nu$ decays. The data-driven-estimated non-peaking background is not evaluated at each stage of the selection, hence only the peaking background cutflow is presented.

Event selection cut-flow is presented for one signal scenario for each signal regions. The model with next-to-lightest neutralino mass of 150 GeV and massless LSP with 100 \% BR is considered. The MC statistics for the signal samples is 123K events. Samples are produced with a generator filter which selects events with at least two leptons with pT $>$ 7 GeV. ``3L+Trigger" indicates three-lepton and trigger requirements. ``Preselection" includes the veto on bjets, ETmiss above 20 GeV and invariant mass of the three leptons above 20 GeV.

Event selection cutflow is presented for one signal scenario for SRSS-j1. The model with next-to-lightest neutralino mass of 175 GeV and massless $\tilde{\chi}^{0}_{1})$ with 100% BR is considered. The MC statistics for the signal samples is 75K events. Samples are produced with a generator filter which selects events with at least two leptons with $p_{\mathrm{T}} > 7$ GeV. ``2SS leptons" indicates the selection of two same-sign electrons or muons as described in the text (Section 6.4).

Event selection cutflow is presented for one signal scenario for SRSS-j23. The model with next-to-lightest neutralino mass of 175 GeV and massless $\tilde{\chi}^{0}_{1})$ with 100% BR is considered. The MC statistics for the signal samples is 75K events. Samples are produced with a generator filter which selects events with at least two leptons with $p_{\mathrm{T}} > 7$ GeV. ``2SS leptons" indicates the selection of two same-sign electrons or muons as described in the text (Section 6.4).

Efficiencies for $0lb\bar{b}$ SRHad-High signal region.

Efficiencies for $0lb\bar{b}$ SRHad-Low signal region.

Efficiency for $1lb\bar{b}$ SR1Lbb-High signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiency for $1lb\bar{b}$ SR1Lbb-Low signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiency for $1lb\bar{b}$ SR1Lbb-Medium signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $1l\gamma\gamma$ signal region SR1Lyy-a.

Efficiencies for $1l\gamma\gamma$ signal region SR1Lyy-b.

Efficiencies for $3L$ DFOS signal region SR3L-DFOS-0J. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $3L$ DFOS signal region SR3L-DFOS-1Ja. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $3L$ DFOS signal region SR3L-DFOS-1Jb. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $3L$ SFOS signal region SR3L-SFOS-0Ja. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $3L$ SFOS signal region SR3L-SFOS-0Jb. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $3L$ SFOS signal region SR3L-SFOS-1J. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $l^{\pm}l^{\pm}$ signal region SRSS-j1. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $l^{\pm}l^{\pm}$ signal region SRSS-j23. Note that the acceptance is relative to the total chargino-neutralino production cross section.

The expected exclusion for the $0lb\bar{b}$ channel. 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 expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $0lb\bar{b}$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The expected exclusion for the $1l\gamma\gamma$ channel. 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 expected exclusion for the $1lb\bar{b}$ channel. 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 expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1lb\bar{b}$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1lb\bar{b}$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1l\gamma\gamma$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1l\gamma\gamma$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $3l$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $3l$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The expected exclusion for the $l^{\pm}l^{\pm}$ channel. 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 expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $l^{\pm}l^{\pm}$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $l^{\pm}l^{\pm}$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The observed exclusion for the $0lb\bar{b}$ channel. 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 cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $0lb\bar{b}$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The observed exclusion for the $1lb\bar{b}$ channel. 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 cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1lb\bar{b}$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1lb\bar{b}$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1l\gamma\gamma$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1l\gamma\gamma$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $3l$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $3l$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The observed exclusion for the $l^{\pm}l^{\pm}$ channel. 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 cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $l^{\pm}l^{\pm}$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $l^{\pm}l^{\pm}$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

Observed and predicted distributions for $m_{jj}$ in SRSS-j1. All SRs selections but the one on the quantity shown are applied. All uncertainties are included in the uncertainty band. An example SUSY model is superimposed for illustrative purposes.

Observed and predicted distributions for $m_{T2}$ in SRSS-j23. All SRs selections but the one on the quantity shown are applied. All uncertainties are included in the uncertainty band. An example SUSY model is superimposed for illustrative purposes.

Upper cross section limits for the $0lb\bar{b}$ analysis.

Upper cross section limits for the $1lb\bar{b}$ analysis.

Upper cross section limits for the $1l\gamma\gamma$ analysis.

Upper cross section limits for the $3l$ analysis.

Upper cross section limits for the $l^{\pm}l^{\pm}$ analysis.

Normalized differential cross section, $(1/\sigma_\text{fid})d\sigma_\text{fid}/d\log(m_{bb}/p_\text{T})$, as a function of $\log(m_{bb}/p_\text{T})$ for $m_{bb}$ the invariant mass of the two b-jets.

Relative differential cross section as a function of H_Thad in emu channel

Relative differential cross section as a function of H_Thad in emu channel

Relative differential cross section as a function of pT of leading b-jet in emu channel

Relative differential cross section as a function of pT of leading b-jet in emu channel

Relative differential cross section as a function of pT of sub-leading b-jet in emu channel

Relative differential cross section as a function of pT of sub-leading b-jet in emu channel

Relative differential cross section as a function of pT of third-leading b-jet in emu channel

Relative differential cross section as a function of pT of third-leading b-jet in emu channel

The measured fiducial cross sections

Relative differential cross section as a function of invarant mass of two highest pT b-jets in emu channel

Relative differential cross section as a function of invarant mass of two highest pT b-jets in emu channel

Relative differential cross section as a function of the b-jet multiplicity in emu channel

Relative differential cross section as a function of pT of two highest pT b-jets in emu channel

Relative differential cross section as a function of pT of two highest pT b-jets in emu channel

Relative differential cross section as a function of deltaR of two highest pT b-jets in emu channel

Relative differential cross section as a function of deltaR of two highest pT b-jets in emu channel

Relative differential cross section as a function of invariant mass of two closest b-jets in deltaR in emu channel

Relative differential cross section as a function of invariant mass of two closest b-jets in deltaR in emu channel

Relative differential cross section as a function of pT of two closest b-jets in deltaR in emu channel

Relative differential cross section as a function of pT of two closest b-jets in deltaR in emu channel

Relative differential cross section as a function of deltaR of two closest b-jets in deltaR in emu channel

Relative differential cross section as a function of deltaR of two closest b-jets in deltaR in emu channel

Relative differential cross section as a function of pT of leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of sub-leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of sub-leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of third-leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of third-leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of fourth-leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of fourth-leading b-jet in lepton+jets channel

Relative differential cross section as a function of H_T in leptons+jets channel

Relative differential cross section as a function of H_T in leptons+jets channel

Relative differential cross section as a function of H_Thad in leptons+jets channel

Relative differential cross section as a function of H_Thad in leptons+jets channel

Relative differential cross section as a function of invariant mass of two highest pT b-jets in lepton+jets channel

Relative differential cross section as a function of invariant mass of two highest pT b-jets in lepton+jets channel

Relative differential cross section as a function of pT of two highest pT b-jets in lepton+jets channel

Relative differential cross section as a function of pT of two highest pT b-jets in lepton+jets channel

Relative differential cross section as a function of deltaR of two highest pT b-jets in lepton+jets channel

Relative differential cross section as a function of deltaR of two highest pT b-jets in lepton+jets channel

Relative differential cross section as a function of invariant mass of two closest b-jets in deltaR in lepton+jets channel

Relative differential cross section as a function of invariant mass of two closest b-jets in deltaR in lepton+jets channel

Relative differential cross section as a function of pT of two closest b-jets in deltaR in lepton+jets channel

Relative differential cross section as a function of pT of two closest b-jets in deltaR in lepton+jets channel

Relative differential cross section as a function of deltaR of two closest b-jets in deltaR in lepton+jets channel

Relative differential cross section as a function of deltaR of two closest b-jets in deltaR in lepton+jets channel

The measured fiducial cross sections

Barrel Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=400$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=600$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=1000$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for all Stealth SUSY benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow \nu b \bar{b}$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow cbs$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow lcb$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow \tau\tau\nu$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=100$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=125$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=200$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=400$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=600$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=1000$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for all Stealth SUSY benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow \nu b \bar{b}$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow cbs$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow lcb$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow \tau\tau\nu$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel MS vertex efficiencies (in %) for $m_{\Phi}=100$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for $m_{\Phi}=125$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for $m_{\Phi}=200$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for $m_{\Phi}=400$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for $m_{\Phi}=600$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for $m_{\Phi}=1000$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for all Stealth SUSY benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow \nu b \bar{b}$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow cbs$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow lcb$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow \tau\tau\nu$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for $m_{\Phi}=100$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for $m_{\Phi}=125$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for $m_{\Phi}=200$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for $m_{\Phi}=400$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for $m_{\Phi}=600$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for $m_{\Phi}=1000$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for all Stealth SUSY benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow \nu b \bar{b}$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow cbs$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow lcb$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow \tau\tau\nu$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=5$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=5$ GeV scalar benchmark sample for 1MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=5$ GeV scalar benchmark sample for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=8$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=8$ GeV scalar benchmark sample for 1MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=8$ GeV scalar benchmark sample for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=15$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=15$ GeV scalar benchmark sample for 1MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=15$ GeV scalar benchmark sample for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=25$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=25$ GeV scalar benchmark sample for 1MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=25$ GeV scalar benchmark sample for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=40$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=40$ GeV scalar benchmark sample for 1MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=40$ GeV scalar benchmark sample for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=250$ GeV for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=500$ GeV for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=500$ GeV for 1MSVx strategy.

Upper 95% CL limits on $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=500$ GeV for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=800$ GeV for 2MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=800$ GeV for 1MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=800$ GeV for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=1200$ GeV for 2MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=1200$ GeV for 1MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=1200$ GeV for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=1500$ GeV for 2MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=1500$ GeV for 1MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=1500$ GeV for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=2000$ GeV for 2MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=2000$ GeV for 1MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=2000$ GeV for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=100$ GeV and $m_{s}=8$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=100$ GeV and $m_{s}=25$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=200$ GeV and $m_{s}=8$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=200$ GeV and $m_{s}=25$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=200$ GeV and $m_{s}=50$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=400$ GeV and $m_{s}=50$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=400$ GeV and $m_{s}=100$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=600$ GeV and $m_{s}=50$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=600$ GeV and $m_{s}=150$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=1000$ GeV and $m_{s}=50$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=1000$ GeV and $m_{s}=150$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=1000$ GeV and $m_{s}=400$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=100$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=100$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=100$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \tau \tau \nu$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \tau \tau \nu$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \tau \tau \nu$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \tau \tau \nu$ channel with $m_{\chi}=100$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

- - - - - - - - - - - - - - - - - - - - <br/><b>Muon RoI Cluster trigger efficiency:</b> <br/><i>mPhi=100:</i> <a href="85748?version=1&table=Table1">Barrel</a> <i>mPhi=125:</i> <a href="85748?version=1&table=Table2">Barrel</a> <br/><i>mPhi=200:</i> <a href="85748?version=1&table=Table3">Barrel</a> <i>mPhi=400:</i> <a href="85748?version=1&table=Table4">Barrel</a> <br/><i>mPhi=600:</i> <a href="85748?version=1&table=Table5">Barrel</a> <i>mPhi=1000:</i> <a href="85748?version=1&table=Table6">Barrel</a> <br/><i>Stealth SUSY:</i> <a href="85748?version=1&table=Table7">Barrel</a> <br/><i>Baryogenesis nubb:</i> <a href="85748?version=1&table=Table8">Barrel</a> <i>Baryogenesis cbs:</i> <a href="85748?version=1&table=Table9">Barrel</a> <br/><i>Baryogenesis lcb:</i> <a href="85748?version=1&table=Table10">Barrel</a> <i>Baryogenesis tautaunu:</i> <a href="85748?version=1&table=Table11">Barrel</a> <br/><i>mPhi=100:</i> <a href="85748?version=1&table=Table12">Endcaps</a> <i>mPhi=125:</i> <a href="85748?version=1&table=Table13">Endcaps </a> <br/><i>mPhi=200:</i> <a href="85748?version=1&table=Table14">Endcaps</a> <i>mPhi=400:</i> <a href="85748?version=1&table=Table15">Endcaps</a> <br/><i>mPhi=600:</i> <a href="85748?version=1&table=Table16">Endcaps</a> <i>mPhi=1000:</i> <a href="85748?version=1&table=Table17">Endcaps</a> <br/><i>Stealth SUSY:</i> <a href="85748?version=1&table=Table18">Endcaps</a> <br/><i>Baryogenesis nubb:</i> <a href="85748?version=1&table=Table19">Endcaps</a> <i>Baryogenesis cbs:</i> <a href="85748?version=1&table=Table20">Endcaps</a> <br/><i>Baryogenesis lcb:</i> <a href="85748?version=1&table=Table21">Endcaps</a> <i>Baryogenesis tautaunu:</i> <a href="85748?version=1&table=Table22">Endcaps</a> <br/><b>MS vertex efficiency:</b> <br/><i>mPhi=100:</i> <a href="85748?version=1&table=Table23">Barrel</a> <i>mPhi=125:</i> <a href="85748?version=1&table=Table24">Barrel</a> <br/><i>mPhi=200:</i> <a href="85748?version=1&table=Table25">Barrel</a> <i>mPhi=400:</i> <a href="85748?version=1&table=Table26">Barrel</a> <br/><i>mPhi=600:</i> <a href="85748?version=1&table=Table27">Barrel</a> <i>mPhi=1000:</i> <a href="85748?version=1&table=Table28">Barrel</a> <br/><i>Stealth SUSY:</i> <a href="85748?version=1&table=Table29">Barrel</a> <br/><i>Baryogenesis nubb:</i> <a href="85748?version=1&table=Table30">Barrel</a> <i>Baryogenesis cbs:</i> <a href="85748?version=1&table=Table31">Barrel</a> <br/><i>Baryogenesis lcb:</i> <a href="85748?version=1&table=Table32">Barrel</a> <i>Baryogenesis tautaunu:</i> <a href="85748?version=1&table=Table33">Barrel</a> <br/><i>mPhi=100:</i> <a href="85748?version=1&table=Table34">Endcaps</a> <i>mPhi=125:</i> <a href="85748?version=1&table=Table35">Endcaps</a> <br/><i>mPhi=200:</i> <a href="85748?version=1&table=Table36">Endcaps</a> <i>mPhi=400:</i> <a href="85748?version=1&table=Table37">Endcaps</a> <br/><i>mPhi=600:</i> <a href="85748?version=1&table=Table38">Endcaps</a> <i>mPhi=1000:</i> <a href="85748?version=1&table=Table39">Endcaps</a> <br/><i>Stealth SUSY:</i> <a href="85748?version=1&table=Table40">Endcaps</a> <br/><i>Baryogenesis nubb:</i> <a href="85748?version=1&table=Table41">Endcaps</a> <i>Baryogenesis cbs:</i> <a href="85748?version=1&table=Table42">Endcaps</a> <br/><i>Baryogenesis lcb:</i> <a href="85748?version=1&table=Table43">Endcaps</a> <i>Baryogenesis tautaunu:</i> <a href="85748?version=1&table=Table44">Endcaps</a> <br/><b>Exclusion limits:</b> <br/><i>mPhi=125, mS=5:</i> <a href="85748?version=1&table=Table45">2Vx</a> <a href="85748?version=1&table=Table46">1Vx</a> <a href="85748?version=1&table=Table47">Combined</a> <br/><i>mPhi=125, mS=8:</i> <a href="85748?version=1&table=Table48">2Vx</a> <a href="85748?version=1&table=Table49">1Vx</a> <a href="85748?version=1&table=Table50">Combined</a> <br/><i>mPhi=125, mS=15:</i> <a href="85748?version=1&table=Table51">2Vx</a> <a href="85748?version=1&table=Table52">1Vx</a> <a href="85748?version=1&table=Table53">Combined</a> <br/><i>mPhi=125, mS=25:</i> <a href="85748?version=1&table=Table54">2Vx</a> <a href="85748?version=1&table=Table55">1Vx</a> <a href="85748?version=1&table=Table56">Combined</a> <br/><i>mPhi=125, mS=40:</i> <a href="85748?version=1&table=Table57">2Vx</a> <a href="85748?version=1&table=Table58">1Vx</a> <a href="85748?version=1&table=Table59">Combined</a> <br/><i>Stealth SUSY mG=250:</i> <a href="85748?version=1&table=Table60">2Vx</a> <br/><i>Stealth SUSY mG=500:</i> <a href="85748?version=1&table=Table61">2Vx</a> <a href="85748?version=1&table=Table62">1Vx</a> <a href="85748?version=1&table=Table63">Combined</a> <br/><i>Stealth SUSY mG=800:</i> <a href="85748?version=1&table=Table64">2Vx</a> <a href="85748?version=1&table=Table65">1Vx</a> <a href="85748?version=1&table=Table66">Combined</a> <br/><i>Stealth SUSY mG=1200:</i> <a href="85748?version=1&table=Table67">2Vx</a> <a href="85748?version=1&table=Table68">1Vx</a> <a href="85748?version=1&table=Table69">Combined</a> <br/><i>Stealth SUSY mG=1500:</i> <a href="85748?version=1&table=Table70">2Vx</a> <a href="85748?version=1&table=Table71">1Vx</a> <a href="85748?version=1&table=Table72">Combined</a> <br/><i>Stealth SUSY mG=2000:</i> <a href="85748?version=1&table=Table73">2Vx</a> <a href="85748?version=1&table=Table74">1Vx</a> <a href="85748?version=1&table=Table75">Combined</a> <br/><i>mPhi=100, mS=8:</i> <a href="85748?version=1&table=Table76">2Vx</a> <br/><i>mPhi=100, mS=25:</i> <a href="85748?version=1&table=Table77">2Vx</a> <br/><i>mPhi=200, mS=8:</i> <a href="85748?version=1&table=Table78">2Vx</a> <br/><i>mPhi=200, mS=25:</i> <a href="85748?version=1&table=Table79">2Vx</a> <br/><i>mPhi=200, mS=50:</i> <a href="85748?version=1&table=Table80">2Vx</a> <br/><i>mPhi=400, mS=50:</i> <a href="85748?version=1&table=Table81">2Vx</a> <br/><i>mPhi=400, mS=100:</i> <a href="85748?version=1&table=Table82">2Vx</a> <br/><i>mPhi=600, mS=50:</i> <a href="85748?version=1&table=Table83">2Vx</a> <br/><i>mPhi=600, mS=150:</i> <a href="85748?version=1&table=Table84">2Vx</a> <br/><i>mPhi=1000, mS=50:</i> <a href="85748?version=1&table=Table85">2Vx</a> <br/><i>mPhi=1000, mS=150:</i> <a href="85748?version=1&table=Table86">2Vx</a> <br/><i>mPhi=1000, mS=400:</i> <a href="85748?version=1&table=Table87">2Vx</a> <br/><i>Baryogenesis nubb, mChi=10</i> <a href="85748?version=1&table=Table88">2Vx</a> <a href="85748?version=1&table=Table89">1Vx</a> <a href="85748?version=1&table=Table90">Combined</a> <br/><i>Baryogenesis nubb, mChi=30</i> <a href="85748?version=1&table=Table91">2Vx</a> <a href="85748?version=1&table=Table92">1Vx</a> <a href="85748?version=1&table=Table93">Combined</a> <br/><i>Baryogenesis nubb, mChi=50</i> <a href="85748?version=1&table=Table94">2Vx</a> <a href="85748?version=1&table=Table95">1Vx</a> <a href="85748?version=1&table=Table96">Combined</a> <br/><i>Baryogenesis nubb, mChi=100</i> <a href="85748?version=1&table=Table97">2Vx</a> <br/><i>Baryogenesis cbs, mChi=10</i> <a href="85748?version=1&table=Table98">2Vx</a> <a href="85748?version=1&table=Table99">1Vx</a> <a href="85748?version=1&table=Table100">Combined</a> <br/><i>Baryogenesis cbs, mChi=30</i> <a href="85748?version=1&table=Table101">2Vx</a> <a href="85748?version=1&table=Table102">1Vx</a> <a href="85748?version=1&table=Table103">Combined</a> <br/><i>Baryogenesis cbs, mChi=50</i> <a href="85748?version=1&table=Table104">2Vx</a> <a href="85748?version=1&table=Table105">1Vx</a> <a href="85748?version=1&table=Table106">Combined</a> <br/><i>Baryogenesis cbs, mChi=100</i> <a href="85748?version=1&table=Table107">2Vx</a> <br/><i>Baryogenesis lcb, mChi=10</i> <a href="85748?version=1&table=Table108">2Vx</a> <a href="85748?version=1&table=Table109">1Vx</a> <a href="85748?version=1&table=Table110">Combined</a> <br/><i>Baryogenesis lcb, mChi=30</i> <a href="85748?version=1&table=Table111">2Vx</a> <a href="85748?version=1&table=Table112">1Vx</a> <a href="85748?version=1&table=Table113">Combined</a> <br/><i>Baryogenesis lcb, mChi=50</i> <a href="85748?version=1&table=Table114">2Vx</a> <a href="85748?version=1&table=Table115">1Vx</a> <a href="85748?version=1&table=Table116">Combined</a> <br/><i>Baryogenesis lcb, mChi=100</i> <a href="85748?version=1&table=Table117">2Vx</a> <br/><i>Baryogenesis tatanu, mChi=10</i> <a href="85748?version=1&table=Table118">2Vx</a> <br/><i>Baryogenesis tatanu, mChi=30</i> <a href="85748?version=1&table=Table119">2Vx</a> <br/><i>Baryogenesis tatanu, mChi=50</i> <a href="85748?version=1&table=Table120">2Vx</a> <br/><i>Baryogenesis tatanu, mChi=100</i> <a href="85748?version=1&table=Table121">2Vx</a>

Expected 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $\mu\mu$ channel.

Observed 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $\mu\mu$ channel.

Observed and expected 95% CL exclusion, for the tested signal mass hypotheses in the $m_{W_R}–m_{N_R}$ plane, for the Majorana $N_R$ neutrino $\mu\mu$ channel.

Expected 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $ee$ channel.

Observed 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $ee$ channel.

Observed and expected 95% CL exclusion, for the tested signal mass hypotheses in the $m_{W_R}–m_{N_R}$ plane, for the Dirac $N_R$ neutrino $ee$ channel.

Expected 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $\mu\mu$ channel.

Observed 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $\mu\mu$ channel.

Observed and expected 95% CL exclusion, for the tested signal mass hypotheses in the $m_{W_R}–m_{N_R}$ plane, for the Dirac $N_R$ neutrino $\mu\mu$ channel.

Observed 95% CL upper limit on cross-section times branching ratio to the $ee$ final state for the Keung-Senjanovic process in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $ee$ channel.

Observed 95% CL upper limit on cross-section times branching ratio to the $\mu\mu$ final state for the Keung-Senjanovic process in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $\mu\mu$ channel.

Observed 95% CL upper limit on cross-section times branching ratio to the $\mu\mu$ final state for the Keung-Senjanovic process in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $ee$ channel.

Observed 95% CL upper limit on cross-section times branching ratio to the $\mu\mu$ final state for the Keung-Senjanovic process in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $\mu\mu$ channel.

Efficiencies times acceptance for signal region selection as a function of the signal $W_R$ and $N_R$ masses for the SS $e^{\pm}e^{\pm}$ channel.

Efficiencies times acceptance for signal region selection as a function of the signal $W_R$ and $N_R$ masses for the SS $\mu^{\pm}\mu^{\pm}$ channel.

Efficiencies times acceptance for signal region selection as a function of the signal $W_R$ and $N_R$ masses for the OS $e^{\pm}e^{\mp}$ channel.

Efficiencies times acceptance for signal region selection as a function of the signal $W_R$ and $N_R$ masses for the OS $\mu^{\pm}\mu^{\mp}$ channel.

Photon-jet pT balance distributions (1/Ng)(dN/dxJg) in pp events (blue, reproduced on all panels) and Pb+Pb events (red) with each panel denoting a different centrality selection. These panels show results with pTg = 158-200 GeV. Total systematic uncertainties are shown as boxes, while statistical uncertainties are shown with vertical bars.

Selected comparisons of the nominal results in pp (blue) and 0-10% Pb+Pb (red) collisions with the central values obtained using a different photon-jet signal definition. Comparison of the nominal results (with DeltaPhi > 7pi/8) with those obtained using DeltaPhi > 3pi/4 for the pTg = 63.1-79.6 GeV range. Boxes indicate total systematic uncertainties, while vertical bars indicate statistical uncertainties.

Selected comparisons of the nominal results in pp (blue) and 0-10% Pb+Pb (red) collisions with the central values obtained using a different photon-jet signal definition. Comparison of the nominal results (inclusive jet selection) with those obtained using a photon-plus-leading-jet selection for the pTg = 100-158 GeV range. Boxes indicate total systematic uncertainties, while vertical bars indicate statistical uncertainties.

The expected upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 4\gamma$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow\gamma\gamma)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$. Additionally, the expected limits are not provided for a small number of points, indicated with a hyphen, because of a technical failure with the computation.

The observed upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 6\pi^0$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow 3\pi^0)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$.

The expected upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 6\pi^0$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow 3\pi^0)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$. Additionally, the expected limits are not provided for a small number of points, indicated with a hyphen, because of a technical failure with the computation.

Observed 95% CL upper limits on the visible cross section as a function of $m_X$ and the fraction of events in the low-$\Delta E$ category.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.1 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.5 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.7 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 1 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 2 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 5 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 10 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.5 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.7 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 1 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 2 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 5 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 10 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.1 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.5 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.7 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 1 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 2 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 5 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 10 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.5 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.7 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 1 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 2 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 5 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 10 GeV.

Selection efficiency for photons originating from the BSM process $X\rightarrow\gamma\gamma$, where the $X$ particle is a high-mass narrow-width scalar particle originating from the gluon--gluon fusion process.

Fraction of photons with a value of shower shape variable $\Delta E$ lower than the threshold, for photons originating from the BSM process $X\rightarrow\gamma\gamma$, where the $X$ particle is a high-mass narrow-width scalar particle originating from the gluon--gluon fusion process.

Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.

Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.

$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

1$\tau$ MediumMass SR eff.

Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.

1$\tau$ MediumMass SR acceptance.

Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

2$\tau$ Compressed SR eff.

2$\tau$ Compressed SR acceptance.

Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

2$\tau$ HighMass SR eff.

2$\tau$ HighMass SR acceptance.

Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

2$\tau$ multibin SR eff.

2$\tau$ multibin SR acceptance.

Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

2$\tau$ GMSB SR eff.

2$\tau$ GMSB SR acceptance.

Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

1$\tau$ Compressed SR eff.

1$\tau$ Compressed SR acceptance.

$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

1$\tau$ MediumMass SR eff.

1$\tau$ MediumMass SR acceptance.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

2$\tau$ Compressed SR eff.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR eff.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR eff.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR eff.

2$\tau$ GMSB SR acceptance.

Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.

Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Acceptance and efficiency for a representative set of pair-produced gluino signal samples. The mass of the gluino ($m(\tilde{g})$), its lifetime ($\tau(\tilde{g})$) and the mass of the neutralino ($m(\tilde{\chi}^{0})$) are given in the first three columns. The Pythia 6.4.27 signal samples shown in this table are not reweighted to match the transverse momentum of the gluino-gluino system as simulated by MadGraph5_aMC@NLO. The acceptance is defined as the fraction of events passing a loose set of fiducial requirements. The full simulation efficiency (Full sim. $\epsilon$) is defined as the ratio of the number of reconstructed events, as expected by the full ATLAS simulation, and the number of events passing the fiducial requirements. The parameterised simulation efficiency (Param. sim. $\epsilon$) is defined as the ratio of the number of events estimated using a set of parametrised efficiencies (see auxiliary Figures 9,10,11,12) and the number of events passing the fiducial requirements alone.

The reconstructed candidate track mass distributions for observed data, predicted background, and the expected contribution from two signal models in the metastable R-hadron signal region. The yellow band around the background estimation includes both the statistical and systematic uncertainties.

The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 10$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.

Observed 95% lower limits on the gluino mass in the gluino lifetime--mass plane. The excluded area is to the left of the curves.

Expected 95% lower limits on the gluino mass in the gluino lifetime--mass plane. The excluded area is to the left of the curves.

The relationship between generated and reconstructed mass for gluino $R$-hadrons. Above 1500 GeV, the reconstructed mass falls below the generated mass due to bias in the reconstructed momentum. The uncertainty on the reconstructed mass is dominated by momentum uncertainty. The black dots represent the reconstructed mass computed as the most probable value of a Gaussian fit function, with the error bars showing its statistical uncertainty, while the orange band is the full-width at half maximum of the reconstructed mass distribution.

The parameterised efficiency for events to pass metastable event selections (including trigger, E$_{T}^{miss}$, and event cleaning requirements) as a function of the true E$_{T}^{miss}$ in the system, which is calculated at generator level. Event-level efficiencies are evaluated for events which have at least true E$_{T}^{miss} > 50$ GeV. The metastable event efficiencies are evaluated for different radial regions depending on the smallest radial distance, R, at which an R-hadron decays in the detector.

The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.

The number of events in each CR, VR, and SR for the predicted background, for the expected contribution from the signal model normalised to $36.1$ fb$^{-1}$, and in the observed data. The predicted background includes the statistical and systematic uncertainties, respectively. The uncertainty in the signal yield includes all systematic uncertainties except that in the theoretical cross-section.

The observed and expected 95% CL upper limits on model-independent visible cross-sections, along with the observed $p0$ values, for the metastable signal region, as a function of different mass windows, for which the lower bound is shown. The upper boundary on the mass window is 5 TeV for all windows.

The reconstructed candidate track mass distributions for observed data, predicted background, and the expected contribution from two signal models in the stable R-hadron signal region. The yellow band around the background estimation includes both the statistical and systematic uncertainties.

The 95% CL upper limit on the cross-section as a function of mass for stable gluino $R$-hadrons, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.

The parameterised efficiency for events to pass metastable event selections (including trigger, E$_{T}^{miss}$, and event cleaning requirements) as a function of the true E$_{T}^{miss}$ in the system, which is calculated at generator level. Event-level efficiencies are evaluated for events which have at least true E$_{T}^{miss} > 50$ GeV. The stable event efficiencies are evaluated for samples in which no R-hadron decays within the detector.

The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.

The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 1$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.

The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.

The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 3$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.

The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.

The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 30$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.

The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.

The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 50$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple