Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the High-pT jet SR for observed data events

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the High-pT jet SR for expected signal events in the strong gluino pair pair production model with m(gluino)=1.8 TeV, m(chi0)=0.2 TeV, tau(chi0)=0.1 ns

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for observed data events

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for expected signal events in the electroweak pair production model

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Exclusion limits at 95% CL on the production cross section in the electroweak pair production model.

Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m(gluino)=2.4 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m($ ilde{\chi}^0_1$)=1.25 TeV

Acceptance cutflow for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.

Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.

Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.

Acceptance cutflow for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R < 1150 mm

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R [1150, 3870] mm

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R > 3870 mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R < 1150 mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R [1150, 3870] mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R > 3870 mm

Reinterpretation Material: Vertex-level Efficiency for R < 22 mm

Reinterpretation Material: Vertex-level Efficiency for R [22, 25] mm

Reinterpretation Material: Vertex-level Efficiency for R [25, 29] mm

Reinterpretation Material: Vertex-level Efficiency for R [29, 38] mm

Reinterpretation Material: Vertex-level Efficiency for R [38, 46] mm

Reinterpretation Material: Vertex-level Efficiency for R [46, 73] mm

Reinterpretation Material: Vertex-level Efficiency for R [73, 84] mm

Reinterpretation Material: Vertex-level Efficiency for R [84, 111] mm

Reinterpretation Material: Vertex-level Efficiency for R [111, 120] mm

Reinterpretation Material: Vertex-level Efficiency for R [120, 145] mm

Reinterpretation Material: Vertex-level Efficiency for R [145, 180] mm

Reinterpretation Material: Vertex-level Efficiency for R [180, 300] mm

Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.

Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.

Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.

Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR eff.

1$\tau$ MediumMass SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

Cutflow table of the $1\tau$ 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.

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.

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.

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.

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.

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.

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.

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

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 the LSP mass and the gluino mass.

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

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

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.

$E_{\mathrm{T}}^{\mathrm{miss}}$ 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.

$m_{\mathrm{T}}^{\tau}$ 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.

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

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

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

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

$m_{\mathrm{T}}^{\tau}$ 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.

$H_{\mathrm{T}}$ 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.

$m_{\mathrm{T}}^{\mathrm{sum}}$ 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.

$H_{\mathrm{T}}$ 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.

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.

$H_{\mathrm{T}}$ 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.

The observed and expected 95% CL upper limits on model-independent visible cross-sections, along with the observed $p0$ values, for the stable 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 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.

For each gluino lifetime and mass in the signal samples, the lower boundary of the mass window in which at least $70\%$ of the reconstructed signal appears. The upper boundary for all mass windows is 5 TeV.

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 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 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.

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.

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 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 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 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 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 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 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 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 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 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 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 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 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, $p_{T}$. The stable efficiency is evaluated for samples which do not decay within the detector. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.

Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SRC of the low-pT edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the $Z^{*}$ model with m(gluino) = 1000 GeV and m(neutralino1) = 900 GeV is overlaid.

Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SRC-MET of the low-pT edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the $Z^{*}$ model with m(gluino) = 1000 GeV and m(neutralino1) = 900 GeV is overlaid.

Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Observed 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Expected 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.

Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.

Observed 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.

Expected 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.

Observed 95% CL exclusion contours from the on-Z signal regions on the gluino and next-to-lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

Expected 95% CL exclusion contours from the on-Z signal regions on the gluino and next-to-lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

Observed 95% CL exclusion contours from the on-Z signal regions on the squark and next-to-lightest neutralino masses in a SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

Expected 95% CL exclusion contours from the on-Z signal regions on the squark and next-to-lightest neutralino masses in a SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

Observed 95% CL exclusion contours from the on-Z signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino.

Expected 95% CL exclusion contours from the on-Z signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and the lightest neutralino.

Acceptance and efficiency in the on-Z bin for SR-medium for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

Acceptance and efficiency in the on-Z bin for SR-high for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

Acceptance and efficiency over the full $m_{ll}$ range for SR-low for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Acceptance and efficiency over the full $m_{ll}$ range for SR-medium for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Acceptance and efficiency over the full $m_{ll}$ range for SR-high for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Acceptance and efficiency over the full $m_{ll}$ range for SRC for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Acceptance and efficiency over the full $m_{ll}$ range for SRC-MET for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the signal regions, in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the low-p$_{T}$ signal regions, in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the signal regions, in a SUSYscenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the low-p$_{T}$ signal regions, in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson.

Cutflow table for three benchmark signal points from the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, with m(gluino) = 1395 GeV and m(neutralino2) = 505 GeV, m(gluino) = 920 GeV and m(neutralino2) = 230 GeV and m(gluino) = 940 GeV and m(neutralino2) = 660 GeV, in the on-$Z$ $m_{ll}$ bins of SR-medium and SR-high for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Cutflow table for a signal point from the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, with m(gluino) = 1000 GeV and m(neutralino1) = 800 GeV, m(gluino) = 1200 GeV and m(neutralino1) = 500 GeV and m(gluino) = 1400 GeV and m(neutralino1) = 100 GeV, in all m_{ll}$ bins of SR-low, SR-medium and SR-high for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Cutflow table for a signal point from the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, with m(gluino) = 600 GeV and m(neutralino1) = 560 GeV and m(gluino) = 1000 GeV and m(neutralino1) = 960 GeV, in all $m_{ll}$ bins of SRC and SRC-MET for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.

Signal region used to derive the exclusion limit for the SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.

Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.

Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, corresponding to the SR determined to give the best expected limit for a given signal point.

Low-$p_{T}$ signal region used to derive the exclusion limit in the compressed region for the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, corresponding to the SR determined to give the best expected limit for a given signal point.

Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.

Low-$p_{T}$ signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.

Expected 95% CL exclusion contour for Gbb model.

Expected 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.

Observed 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.

Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.

Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.

Expected 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.

Observed 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.

Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.

Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.

Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.

Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.

Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.

Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.

Distribution of ETMISS for SR-Gbb-VC.

Distribution of ETMISS for SR-Gtt-1l-B.

Distribution of ETMISS for SR-1L-II.

Distribution of ETMISS for SR-0L-HI.

Distribution of ETMISS for SR-0L-HH.

Acceptances for Gbb model in SR-Gbb-B.

Acceptances for Gbb model in SR-Gbb-M.

Acceptances for Gbb model in SR-Gbb-C.

Acceptances for Gbb model in SR-Gbb-VC.

Acceptances for Gtt model in SR-Gtt-0l-B.

Acceptances for Gtt model in SR-Gtt-0l-M.

Acceptances for Gtt model in SR-Gtt-0l-C.

Acceptances for Gtt model in SR-Gtt-1l-B.

Acceptances for Gtt model in SR-Gtt-1l-M.

Acceptances for Gtt model in SR-Gtt-1l-C.

Experimental efficiencies for Gbb model in SR-Gbb-B.

Experimental efficiencies for Gbb model in SR-Gbb-M.

Experimental efficiencies for Gbb model in SR-Gbb-C.

Experimental efficiencies for Gbb model in SR-Gbb-VC.

Experimental efficiencies for Gtt model in SR-Gtt-0l-B.

Experimental efficiencies for Gtt model in SR-Gtt-0l-M.

Experimental efficiencies for Gtt model in SR-Gtt-0l-C.

Experimental efficiencies for Gtt model in SR-Gtt-1l-B.

Experimental efficiencies for Gtt model in SR-Gtt-1l-M.

Experimental efficiencies for Gtt model in SR-Gtt-0l-C.

95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model.

95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model.

95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-B.

95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-M.

95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-C.

95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-VC.

95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-B.

95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-M.

95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-C.

95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-B.

95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-M.

95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-C.

Observed 95% CL exclusion contour for Gbb model in SR-Gbb-B.

Expected 95% CL exclusion contour for Gbb model in SR-Gbb-B.

Observed 95% CL exclusion contour for Gbb model in SR-Gbb-M.

Expected 95% CL exclusion contour for Gbb model in SR-Gbb-M.

Observed 95% CL exclusion contour for Gbb model in SR-Gbb-C.

Expected 95% CL exclusion contour for Gbb model in SR-Gbb-C.

Observed 95% CL exclusion contour for Gbb model in SR-Gbb-VC.

Expected 95% CL exclusion contour for Gbb model in SR-Gbb-VC.

Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.

Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.

Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.

Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.

Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.

Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.

Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.

Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.

Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.

Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.

Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.

Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.

Expected number of signal events after each step of the Gbb-0L-B selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.

Expected number of signal events after each step of the Gbb-0L-M selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.

Expected number of signal events after each step of the Gbb-0L-C selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.

Expected number of signal events after each step of the Gbb-0L-VC selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.

Expected number of signal events after each step of the Gtt-1L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.

Expected number of signal events after each step of the Gtt-1L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.

Expected number of signal events after each step of the Gtt-1L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.

Expected number of signal events after each step of the Gtt-0L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.

Expected number of signal events after each step of the Gtt-0L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.

Expected number of signal events after each step of the Gtt-0L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.

Expected 95% CL exclusion contours for the gluino one-step variable-x model.

Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.

Expected 95% CL exclusion contours for the squark one-step x = 1/2 model.

Observed 95% CL exclusion contours for the squark one-step variable-x model.

Expected 95% CL exclusion contours for the squark one-step variable-x model.

Observed 95% CL exclusion contours for the gluino two-step model.

Expected 95% CL exclusion contours for the gluino two-step model.

Observed 95% CL exclusion contours for pMSSM model.

Expected 95% CL exclusion contours for pMSSM model.

$m_{\mathrm{eff}}$ distribution in 2J b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{eff}}$ distribution in 4J low-x b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{eff}}$ distribution in 4J high-x b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{eff}}$ distribution in 6J b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{eff}}$ distribution in 2J b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{eff}}$ distribution in 4J low-x b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{eff}}$ distribution in 4J high-x b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{eff}}$ distribution in 6J b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{eff}}$ distribution in 9J signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{T}}$ distribution for events satisfying all the 2J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 2J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{T}}$ distribution for events satisfying all the 2J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 2J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{T}}$ distribution for events satisfying all the 4J low-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J low-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{T}}$ distribution for events satisfying all the 4J low-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J low-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{T}}$ distribution for events satisfying all the 4J high-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J high-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{T}}$ distribution for events satisfying all the 4J high-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J high-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{T}}$ distribution for events satisfying all the 6J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 6J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{T}}$ distribution for events satisfying all the 6J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 6J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

$m_{\mathrm{T}}$ distribution for events satisfying all the 9J signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

Observed upper limits on the signal cross-section for gluino one-step x = 1/2 model.

Observed upper limits on the signal cross-section for gluino one-step variable-x model.

Observed upper limits on the signal cross-section for squark one-step x = 1/2 model.

Observed upper limits on the signal cross-section for squark one-step variable-x model.

Observed upper limits on the signal cross-section for gluino two-step model.

Observed upper limits on the signal cross-section for pMSSM model.

Acceptance in 2J discovery signal region for gluino one-step x = 1/2 model.

Acceptance in 2J discovery signal region for squark one-step x = 1/2 model.

Acceptance in 4J low-x discovery signal region for gluino one-step variable-x model.

Acceptance in 4J low-x discovery signal region for squark one-step variable-x model.

Acceptance in 4J high-x discovery signal region for gluino one-step variable-x model.

Acceptance in 4J high-x discovery signal region for squark one-step variable-x model.

Acceptance in 6J discovery signal region for gluino one-step x = 1/2 model.

Acceptance in 6J discovery signal region for squark one-step x = 1/2 model.

Acceptance in 9J discovery signal region for pMSSM model.

Acceptance in 9J discovery signal region for gluino two-step model.

Efficiency in 2J discovery signal region for gluino one-step x = 1/2 model.

Efficiency in 2J discovery signal region for squark one-step x = 1/2 model.

Efficiency in 4J low-x discovery signal region for gluino one-step variable-x model.

Efficiency in 4J low-x discovery signal region for squark one-step variable-x model.

Efficiency in 4J high-x discovery signal region for gluino one-step variable-x model.

Efficiency in 4J high-x discovery signal region for squark one-step variable-x model.

Efficiency in 6J discovery signal region for gluino one-step x = 1/2 model.

Efficiency in 6J discovery signal region for squark one-step x = 1/2 model.

Efficiency in 9J discovery signal region for pMSSM model.

Efficiency in 9J discovery signal region for gluino two-step model.

Cutflow table for the 2J discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).

Cutflow table for the 4J high-x discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).

Cutflow table for the 4J low-x discovery signal region (targetting gluino decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).

Cutflow table for the 4J low-x discovery signal region (targetting squark decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).

Cutflow table for the 6J discovery signal region (targetting gluino decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).

Cutflow table for the 6J discovery signal region (targetting squark decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).

Cutflow table for the 9J discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).

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

Expected 95% CL limit for the pMSSM grid.

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

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

Observed 95% CL limit for the 2Step grid.

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

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

Expected 95% CL limit for the 2Step grid.

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

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

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

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

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

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

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

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

Observed 95% CL limit for the RPV grid.

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

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

Expected 95% CL limit for the RPV grid.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-11j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-11j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-11j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

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

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

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

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

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

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

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

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

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

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

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 340 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 500 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with ten jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eleven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with twelve-or-more jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with five jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with six jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with five jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with six jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

Observed exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.

Expected exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.

Observed exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Expected exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Observed exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Expected exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.

Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.

Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.

Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.

Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.

Observed upper limits on the model cross-section in units of pb as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.

Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.

Acceptance as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Efficiency as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Acceptance as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Efficiency as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Cut flow for a model of gluino pair production where the gluino decays to two (u, d, s, c) quarks and the neutralino, which then decays to two (u, d, s, c) quarks and a lepton via a lambda' RPV coupling, where each RPV decay can produce any of the four first and second generation leptons (e, mu, nu_e, nu_mu) with equal probability (m_gluino = 1800 GeV, m_neutralino = 900 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of gluino pair production where each gluino decays to a top quark and a top squark, with the top squark decaying to an s- and a b- quark via a non-zero lambda''_323 RPV coupling (m_gluino = 1600 GeV, m_stop = 1000 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of gluino pair production where each gluino decays via an off-shell top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino -> uds) via the RPV coupling lambda''_112 (m_gluino = 2000 GeV, m_neutralino = 941 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of right-handed top squark pair production with the top squark decaying to the lightest supersymmetric particle (LSP) which is considered to be purely higgsino. The higgsino-like LSP decays through the non-zero RPV coupling lambda''_323 (m_stop = 975 GeV, m_neutralino = 600 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane. The curve shows the observed limit on the corresponding SUSY particle masses obtained by comparing the excluded cross section with theoretical cross sections.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane. The curve shows the observed limit on the corresponding SUSY particle masses obtained by comparing the excluded cross section with $+1\sigma$ theoretical cross sections.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane. The curve shows the observed limit on the corresponding SUSY particle masses obtained by comparing the excluded cross section with $-1\sigma$ theoretical cross sections.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane. The curve shows the expected limit on the corresponding SUSY particle masses obtained by comparing the excluded cross section with theoretical cross sections.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane. The curve shows the expected limit on the corresponding SUSY particle masses corresponding to a $+1\sigma$ variation of the experimental uncertainty.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane. The curve shows the expected limit on the corresponding SUSY particle masses corresponding to a $-1\sigma$ variation of the experimental uncertainty.

Observed excluded region (95\% CL), shown in blue, in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane for a model combining T5tttt, gluino pair production, followed by gluino decay to an on-shell top squark, together with a model for direct top squark pair production. The top squarks decay via the two-body process $\tilde{t}\rightarrow t\tilde{\chi}^0_1$. The neutralino and top squark masses are related by the constraint $m_{\tilde{t}} = m_{\tilde{\chi}^0_1} + 175$ GeV.

Expected excluded region (95\% CL), shown in blue, in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane for a model combining T5tttt, gluino pair production, followed by gluino decay to an on-shell top squark, together with a model for direct top squark pair production. The top squarks decay via the two-body process $\tilde{t}\rightarrow t\tilde{\chi}^0_1$. The neutralino and top squark masses are related by the constraint $m_{\tilde{t}} = m_{\tilde{\chi}^0_1} + 175$ GeV.