Selection efficiencies in % for the signal in the top squark search, estimated from the simulation.

The final $S_{\text{T}}$ distribution for the leptoquark search with the $\text{e}\tau_{\text{h}}$ and $\mu\tau_{\text{h}}$ channels combined. The last bin contains the overflow events.

The final $S_{\text{T}}$ distribution for the top squark search with the $\text{e}\tau_{\text{h}}$ and $\mu\tau_{\text{h}}$ channels combined. The last bin contains the overflow events.

The expected and observed combined upper limits on the third-generation LQ pair production cross section $\sigma$ times the square of the branching fraction, $\mathcal{B}^2$, at 95% CL, as a function of the LQ mass. These limits also apply to top squarks decaying directly via the coupling $\lambda^{\prime}_{333}$.

The expected and observed combined upper limits on the top squark pair production cross section $\sigma$ times the square of the branching fraction, $\mathcal{B}^2$, at 95% CL, as a function of the top squark mass. These limits apply to top squarks with a chargino-mediated decay through the coupling $\lambda^{\prime}_{3jk}$.

The expected and observed 95% CL upper limits on the branching fraction for the leptoquark decay to a tau lepton and a bottom quark, as a function of the leptoquark mass. A search for top squark pair production [EPJC 73(2013)2677] has the same kinematic signature as the leptoquark decay to a tau neutrino and a top quark. This search is reinterpreted to provide the expected and observed 95% CL upper limits for low values of $\mathcal{B}$, assuming the leptoquark only decays to third-generation fermions.

Number of data events (20.3 fb$^{-1}$), number of predicted events from the fit, statistical uncertainty on the fit, systematic uncertainty on the choice of control region, and on the choice of fit function versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ lower bin edge for inclusive jet multiplicity $N_{\textrm{Jet}} \geq 6$. The total uncertainty is obtained by adding the three uncertainties linearly.

Number of data events (20.3 fb$^{-1}$), number of predicted events from the fit, statistical uncertainty on the fit, systematic uncertainty on the choice of control region, and on the choice of fit function versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ lower bin edge for inclusive jet multiplicity $N_{\textrm{Jet}} \geq 7$. The total uncertainty is obtained by adding the three uncertainties linearly.

Number of data events (20.3 fb$^{-1}$), number of predicted events from the fit, statistical uncertainty on the fit, systematic uncertainty on the choice of control region, and on the choice of fit function versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ lower bin edge for inclusive jet multiplicity $N_{\textrm{Jet}} \geq 8$. The total uncertainty is obtained by adding the three uncertainties linearly.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 3$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 4$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 5$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 6$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 7$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 8$.

Mean reconstruction efficiencies $(\epsilon)$ and RMS of the reconstruction efficiencies for various black hole and string ball models.

Expected and observed $am_{T2}$ distribution for bCd_high1 SR, before applying the $am_{T2}>200$ GeV requirement. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Expected and observed leading b-jet $p_T$ distribution for bCd_high2 SR, before applying the leading b-jet $p_T>170$ GeV requirement. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Expected and observed $E_T^{miss}$ distribution for tNbC_mix SR, before applying the $E_T^{miss}>270$ GeV requirement. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Expected and observed lepton $p_T$ distribution for bCa_low SR. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Expected and observed lepton $p_T$ distribution for bCa_med SR. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Expected and observed $am_T2$ distribution for bCb_med1 SR. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Expected and observed $am_T2$ distribution for bCb_high SR. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Best expected signal region for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1$ three-body scenario ($\tilde t_1\to bW\chi^0_1$). This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1$ four-body scenario ($\tilde t_1\to bff'\chi^0_1$). This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=150$ GeV. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=106$ GeV. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+5$ GeV. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\tilde t_1}-10$ GeV. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\tilde t_1}=300$ GeV. This mapping is used for the final combined exclusion limits.

Upper limits on the model cross-section for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Observed exclusion contour for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Expected exclusion contour for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Upper limit on signal events for the $\tilde t_1$ three-body scenario ($\tilde t_1\to bW\chi^0_1$).

Observed exclusion contour for the $\tilde t_1$ three-body scenario ($\tilde t_1\to bW\chi^0_1$).

Expected exclusion contour for the $\tilde t_1$ three-body scenario ($\tilde t_1\to bW\chi^0_1$).

Upper limit on signal events for the $\tilde t_1$ four-body scenario ($\tilde t_1\to bff'\chi^0_1$).

Observed exclusion contour for the $\tilde t_1$ four-body scenario ($\tilde t_1\to bff'\chi^0_1$).

Expected exclusion contour for the $\tilde t_1$ four-body scenario ($\tilde t_1\to bff'\chi^0_1$).

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=150$ GeV.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=150$ GeV.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=150$ GeV.

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=106$ GeV.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=106$ GeV.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=106$ GeV.

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+5$ GeV.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+5$ GeV.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+5$ GeV.

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\tilde t_1}-10$ GeV.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\tilde t_1}-10$ GeV.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\tilde t_1}-10$ GeV.

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\tilde t_1}=300$ GeV.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\tilde t_1}=300$ GeV.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\tilde t_1}=300$ GeV.

Acceptance of tN_diag SR ($E_T^{miss}>150$ GeV, $m_T>140$ GeV) for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. 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 of tN_med SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. 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 of tN_boost SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. 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 of bCb_med2 SR ($am_{T2}>250$ GeV, $m_T>60$ GeV) for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. 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 of bCc_diag SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. 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 of bCd_bulk SR ($am_{T2}>175$ GeV, $m_T>120$ GeV) for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. 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 of bCd_high1 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. 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 of bCd_high2 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. 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 of bCa_med for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. 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 of bCa_low for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. 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 of bCb_med1 for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. 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 of bCb_high for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. 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 of 3-body SR ($80<am_{T2}<90$ GeV, $m_T>120$ GeV) for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$). 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 of tNbC_mix SR for the asymmetric scenario ($\tilde t_1$, $\tilde t_1\to t\chi^0_1$, b $\chi^\pm_1$) with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. 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 of tN_diag SR ($E_T^{miss}>150$ GeV, $m_T>140$ GeV) for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. 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 of tN_med SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. 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 of tN_boost SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. 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 of bCb_med2 SR ($am_{T2}>250$ GeV, $m_T>60$ GeV) for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. 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 of bCc_diag SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. 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 of bCd_bulk SR ($am_{T2}>175$ GeV, $m_T>120$ GeV) for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. 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 of bCd_high1 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. 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 of bCd_high2 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. 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 of bCa_med for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. 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 of bCa_low for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. 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 of bCb_med1 for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. 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 of bCb_high for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. 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 of 3-body SR ($80<am_{T2}<90$ GeV, $m_T>120$ GeV) for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$). 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 of tNbC_mix SR for the asymmetric scenario ($\tilde t_1$, $\tilde t_1\to t\chi^0_1$, b $\chi^\pm_1$) with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. 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).

Number of generated events for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Number of generated events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Number of generated events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV; $E_T^{miss}$(gen)$>60$ GeV.

Number of generated events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV; $E_T^{miss}$(gen)$>250$ GeV.

Number of generated events for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$).

Number of generated events for the asymmetric scenario ($\tilde t_1$, $\tilde t_1\to t\chi^0_1$, b $\chi^\pm_1$) with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Cross-section for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Cross-section for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Cross-section for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Cross-section for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$).

Cross-section for the asymmetric scenario ($\tilde t_1$, $\tilde t_1\to t\chi^0_1$, b $\chi^\pm_1$) with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Combined experimental systematic uncertainty of expected tN_diag SR yields for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$, using the 2 highest $E_T^{miss}$ and 2 highest $m_T$ bins.

Combined experimental systematic uncertainty of expected tN_med SR yields for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Combined experimental systematic uncertainty of expected tN_boost SR yields for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Combined experimental systematic uncertainty of expected bCb_med2 SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$, using the 2 highest $am_{T2}$ and 2 highest $m_T$ bins.

Combined experimental systematic uncertainty of expected bCc_diag SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Combined experimental systematic uncertainty of expected bCd_bulk SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$, using the 2 highest $am_{T2}$ and 2 highest $m_T$ bins.

Combined experimental systematic uncertainty of expected bCd_high1 SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Combined experimental systematic uncertainty of expected bCd_high2 SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Combined experimental systematic uncertainty of expected bCa_med SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Combined experimental systematic uncertainty of expected bCa_low SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Combined experimental systematic uncertainty of expected bCb_med1 SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Combined experimental systematic uncertainty of expected bCb_high SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Combined experimental systematic uncertainty of expected 3-body SR yields for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$), using the 2 lowest $am_{T2}$ and 2 highest $m_T$ bins.

Combined experimental systematic uncertainty of expected tNbC_mix SR yields for the asymmetric scenario ($\tilde t_1$, $\tilde t_1\to t\chi^0_1$, b $\chi^\pm_1$) with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed CLs in tN_diag SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Observed CLs in tN_med SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Observed CLs in tN_boost SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Observed CLs in bCb_med2 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed CLs in bCc_diag SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed CLs in bCd_bulk SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed CLs in bCd_high1 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed CLs in bCd_high2 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed CLs in bCa_med SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Observed CLs in bCa_low SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Observed CLs in bCb_med1 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Observed CLs in bCb_high SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Observed CLs in 3-body SR for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$).

Observed CLs in tNbC_mix SR for the mixed scenario (50% $\tilde t_1\to t\chi^0_1$, 50% $\tilde t_1\to b\chi^0_1$).

Expected CLs in tN_diag SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Expected CLs in tN_med SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Expected CLs in tN_boost SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Expected CLs in bCb_med2 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Expected CLs in bCc_diag SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Expected CLs in bCd_bulk SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Expected CLs in bCd_high1 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Expected CLs in bCd_high2 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Expected CLs in bCa_med SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Expected CLs in bCa_low SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Expected CLs in bCb_med1 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Expected CLs in bCb_high SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Expected CLs in 3-body SR for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$).

Expected CLs in tNbC_mix SR for the mixed scenario (50% $\tilde t_1\to t\chi^0_1$, 50% $\tilde t_1\to b\chi^\pm_1$).

Distribution of the transverse mass of the $W$-candidate $m_{\rm T}^{W}$ for the one lepton and two $b$-jets channel in SRlbb-1 and SRlbb-2, $m_{bb}$ sidebands. The background histograms are obtained from the background-only fit, and their uncertainty represents the total background uncertainty after the fit. The last bin includes overflow.

Distribution of the number of $b$-jets for the one lepton and two $b$-jets channel in SRlbb-1 and SRlbb-2 without the b-jet multiplicity requirement, central $m_{bb}$ bin. The background histograms are obtained from the background-only fit, and their uncertainty represents the total background uncertainty after the fit.

Distribution of the invariant mass of the $b$-jets $m_{bb}$ for the one lepton and two $b$-jets channel in the SRlbb-1 and SRlbb-2. The background histograms are obtained from the background-only fit, and their uncertainty represents the total background uncertainty after the fit.

Distribution of missing transverse momentum $E_{\rm T}^{\rm miss}$ in the one lepton and two photons signal regions SR$\ell\gamma\gamma$-1 and SR$\ell\gamma\gamma$-2 for the Higgs-mass window ($120\lt m_{\gamma\gamma} \lt 130$ GeV). The final column (background) is a simulation-based cross check. The contributions from non-Higgs backgrounds are scaled by 10 GeV / 50 GeV = 0.2 from the $m_{\gamma\gamma}$ sideband ($100 \lt m_{\gamma\gamma} \lt 120$ GeV and $130 \lt m_{\gamma\gamma} \lt 160$ GeV) into the Higgs-mass window. The last bin includes overflow. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

Distribution of the azimuth difference between the $W$ and Higgs boson candidates $\Delta\phi(W,h)$ in the one lepton and two photons signal regions SR$\ell\gamma\gamma$-1 and SR$\ell\gamma\gamma$-2 for the Higgs-mass window ($120\lt m_{\gamma\gamma} \lt 130$ GeV). The final column (background) is a simulation-based cross check. The contributions from non-Higgs backgrounds are scaled by 10 GeV / 50 GeV = 0.2 from the $m_{\gamma\gamma}$ sideband ($100 \lt m_{\gamma\gamma} \lt 120$ GeV and $130 \lt m_{\gamma\gamma} \lt 160$ GeV) into the Higgs-mass window. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

Distribution of the transverse mass of the $W$ and photon system $m_{\rm{T}}^{W\gamma_1}$ in the one lepton and two photons signal regions SR$\ell\gamma\gamma$-1 and SR$\ell\gamma\gamma$-2 for the Higgs-mass window ($120\lt m_{\gamma\gamma} \lt 130$ GeV). The final column (background) is a simulation-based cross check. The contributions from non-Higgs backgrounds are scaled by 10 GeV / 50 GeV = 0.2 from the $m_{\gamma\gamma}$ sideband ($100 \lt m_{\gamma\gamma} \lt 120$ GeV and $130 \lt m_{\gamma\gamma} \lt 160$ GeV) into the Higgs-mass window. The last bin includes overflow. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

Distribution of the transverse mass of the $W$ and photon system $m_{\rm{T}}^{W\gamma_2}$ in the one lepton and two photons signal regions SR$\ell\gamma\gamma$-1 and SR$\ell\gamma\gamma$-2 for the Higgs-mass window ($120\lt m_{\gamma\gamma} \lt 130$ GeV). The final column (background) is a simulation-based cross check. The contributions from non-Higgs backgrounds are scaled by 10 GeV / 50 GeV = 0.2 from the $m_{\gamma\gamma}$ sideband ($100 \lt m_{\gamma\gamma} \lt 120$ GeV and $130 \lt m_{\gamma\gamma} \lt 160$ GeV) into the Higgs-mass window. The last bin includes overflow. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

Results of the background-only fit to the diphoton invariant mass, $m_{\gamma\gamma}$, distribution in the one lepton and two photons signal region SR$l\gamma\gamma$-1. The contributions from SM Higgs boson production are constrained to the MC prediction and associated systematic uncertainties. The fit is performed on events with 100 GeV $ \lt m_{\gamma\gamma} \lt $ 160 GeV, with events in SR$l\gamma\gamma$-1 or SR$l\gamma\gamma$-2 in the Higgs-mass window (120 GeV $\le m_{\gamma\gamma} \le$ 130 GeV) excluded from the fit.

Results of the background-only fit to the diphoton invariant mass, $m_{\gamma\gamma}$, distribution in the one lepton and two photons signal region SR$l\gamma\gamma$-2. The contributions from SM Higgs boson production are constrained to the MC prediction and associated systematic uncertainties. The fit is performed on events with 100 GeV $ \lt m_{\gamma\gamma} \lt $ 160 GeV, with events in SR$l\gamma\gamma$-1 or SR$l\gamma\gamma$-2 in the Higgs-mass window (120 GeV $\le m_{\gamma\gamma} \le$ 130 GeV) excluded from the fit.

Results of the background-only fit to the diphoton invariant mass, $m_{\gamma\gamma}$, distribution in the one lepton and two photons validation region VR$l\gamma\gamma$-1. The contributions from SM Higgs boson production are constrained to the MC prediction and associated systematic uncertainties. The fit is performed on events with 100 GeV $ \lt m_{\gamma\gamma} \lt $ 160 GeV, with events in SR$l\gamma\gamma$-1 or SR$l\gamma\gamma$-2 in the Higgs-mass window (120 GeV $\le m_{\gamma\gamma} \le$ 130 GeV) excluded from the fit.

Results of the background-only fit to the diphoton invariant mass, $m_{\gamma\gamma}$, distribution in the one lepton and two photons validation region VR$l\gamma\gamma$-2. The contributions from SM Higgs boson production are constrained to the MC prediction and associated systematic uncertainties. The fit is performed on events with 100 GeV $ \lt m_{\gamma\gamma} \lt $ 160 GeV, with events in SR$l\gamma\gamma$-1 or SR$l\gamma\gamma$-2 in the Higgs-mass window (120 GeV $\le m_{\gamma\gamma} \le$ 130 GeV) excluded from the fit.

Distribution of effective mass $m_{\rm eff}$ in the validation region of the same-sign $e\mu$ channel. This validation region is defined by requiring one, two, or three jets, and reversing the $m_{lj}$, $m_{ljj}$ criteria. The distribution of a signal hypothesis is also shown.

Distribution of effective mass $m_{\rm eff}$ for the same-sign dilepton channel in the signal regions with one jet SR$ll$-1. SR$ll$-1 is the sum of SR$ee$-1, SR$e\mu$-1, and SR$\mu\mu$-1. All selection criteria are applied, except for the one on $m_{\rm eff}$. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(130,0)$ GeV. The last bin includes overflow.

Distribution of effective mass $m_{\rm eff}$ for the same-sign dilepton channel in the signal regions with two or three jets SR$ll$-2. SR$ll$-2 is the sum of SR$ee$-2, SR$e\mu$-2, and SR$\mu\mu$-2. All selection criteria are applied, except for the one on $m_{\rm eff}$. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(130,0)$ GeV. The last bin includes overflow.

Distribution of largest transverse mass $m_{\rm T}^{\rm max}$ for the same-sign dilepton channel in the signal regions with one jet SR$ll$-1. SR$ll$-1 is the sum of SR$ee$-1, SR$e\mu$-1, and SR$\mu\mu$-1. All selection criteria are applied, except for the one on $m_{\rm T}^{\rm max}$. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(130,0)$ GeV. The last bin includes overflow.

Distribution of largest transverse mass $m_{\rm T}^{\rm max}$ for the same-sign dilepton channel in the signal regions with two or three jets SR$ll$-2. SR$ll$-2 is the sum of SR$ee$-2, SR$e\mu$-2, and SR$\mu\mu$-2. All selection criteria are applied, except for the one on $m_{\rm T}^{\rm max}$. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(130,0)$ GeV. The last bin includes overflow.

Distribution of invariant mass of lepton and jet $m_{lj}$ for the same-sign dilepton channel in the signal regions with one jet SR$ll$-1. SR$ll$-1 is the sum of SR$ee$-1, SR$e\mu$-1, and SR$\mu\mu$-1. All selection criteria are applied, except for the one on $m_{lj}$. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(130,0)$ GeV. The last bin includes overflow.

Distribution of invariant mass of lepton and di-jet $m_{ljj}$ for the same-sign dilepton channel in the signal regions with two or three jets SR$ll$-2. SR$ll$-2 is the sum of SR$ee$-2, SR$e\mu$-2, and SR$\mu\mu$-2. All selection criteria are applied, except for the one on $m_{ljj}$. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(130,0)$ GeV. The last bin includes overflow.

One lepton and two $b$-jets channel: observed and expected 95% CL upper limits on the cross section normalised by the simplified model prediction as a function of the common mass $m_{\tilde{\chi}_1^\pm \tilde{\chi}^0_2}$ for $m_{\tilde{\chi}^0_1}=0$.

One lepton and two photons channel: observed and expected 95% CL upper limits on the cross section normalised by the simplified model prediction as a function of the common mass $m_{\tilde{\chi}_1^\pm \tilde{\chi}^0_2}$ for $m_{\tilde{\chi}^0_1}=0$.

Same-sign dilepton channel: observed and expected 95% CL upper limits on the cross section normalised by the simplified model prediction as a function of the common mass $m_{\tilde{\chi}_1^\pm \tilde{\chi}^0_2}$ for $m_{\tilde{\chi}^0_1}=0$.

Combination: observed and expected 95% CL upper limits on the cross section normalised by the simplified model prediction as a function of the common mass $m_{\tilde{\chi}_1^\pm \tilde{\chi}^0_2}$ for $m_{\tilde{\chi}^0_1}=0$. This combination is obtained using the result from the ATLAS three-lepton search, J. High Energy Phys. 04 (2014) 169, in addition to the three channels reported in this paper.

One lepton and two b-jets channel: Expected 95% CL exclusion contour for chargino neutralino production via Wh.

One lepton and two b-jets channel: Observed 95% CL exclusion contour for chargino neutralino production via Wh.

One lepton and two photons channel: Expected 95% CL exclusion contour for chargino neutralino production via Wh.

One lepton and two photons channel: Observed 95% CL exclusion contour for chargino neutralino production via Wh.

Same-sign dilepton channel: Expected 95% CL exclusion contour for chargino neutralino production via Wh.

Same-sign dilepton channel: Observed 95% CL exclusion contour for chargino neutralino production via Wh.

Combination: Expected 95% CL exclusion contour for chargino neutralino production via Wh.

Combination: Observed 95% CL exclusion contour for chargino neutralino production via Wh.

Combination: excluded model cross-section at 95% CL IN PB.

Acceptance SR$\ell\gamma\gamma$-1.

Acceptance SR$\ell\gamma\gamma$-2.

Efficiency SR$\ell\gamma\gamma$-1.

Efficiency SR$\ell\gamma\gamma$-2.

$m_{\gamma\gamma}$ distribution in the SR$l\gamma\gamma$-1 region for the full $m_{\gamma\gamma}$ window. The last column (background) is from a simulation-based cross check. $Z\gamma$ events, with $Z\rightarrow{ee}$ and one electron mis-identified as a photon, are included in the $Z\gamma(\gamma)$ background. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

$m_{\gamma\gamma}$ distribution in the SR$l\gamma\gamma$-2 region for the full $m_{\gamma\gamma}$ window. The last column (background) is from a simulation-based cross check. $Z\gamma$ events, with $Z\rightarrow{ee}$ and one electron mis-identified as a photon, are included in the $Z\gamma(\gamma)$ background. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

$m_{\gamma\gamma}$ distribution in the VR$l\gamma\gamma$-1 region for the full $m_{\gamma\gamma}$ window. The last column (background) is from a simulation-based cross check. $Z\gamma$ events, with $Z\rightarrow{ee}$ and one electron mis-identified as a photon, are included in the $Z\gamma(\gamma)$ background. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

$m_{\gamma\gamma}$ distribution in the VR$l\gamma\gamma$-2 region for the full $m_{\gamma\gamma}$ window. The last column (background) is from a simulation-based cross check. $Z\gamma$ events, with $Z\rightarrow{ee}$ and one electron mis-identified as a photon, are included in the $Z\gamma(\gamma)$ background. The distributions of a signal hypothesis are also shown for $m(\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2},\tilde{\chi}^{0}_{1})=(165,35)$ GeV.

Acceptance for SRlbb-1, central $m_{bb}$ bin.

Acceptance for SRlbb-1, $m_{bb}$ sideband.

Acceptance for SRlbb-2, central $m_{bb}$ bin.

Acceptance for SRlbb-2, $m_{bb}$ sideband.

Efficiency for SRlbb-1, central $m_{bb}$ bin.

Efficiency for SRlbb-1, $m_{bb}$ sideband.

Efficiency for SRlbb-2, central $m_{bb}$ bin.

Efficiency for SRlbb-2, $m_{bb}$ sideband.

Acceptance for the same-sign $ee$ channel with one jet.

Acceptance for the same-sign $ee$ channel with two or three jets.

Acceptance for the same-sign $e\mu$ channel with one jet.

Acceptance for the same-sign $e\mu$ channel with two or three jets.

Acceptance for the same-sign $\mu\mu$ channel with one jet.

Acceptance for the same-sign $\mu\mu$ channel with two or three jets.

Efficiency for the same-sign $ee$ channel with one jet.

Efficiency for the same-sign $ee$ channel with two or three jets.

Efficiency for the same-sign $e\mu$ channel with one jet.

Efficiency for the same-sign $e\mu$ channel with two or three jets.

Efficiency for the same-sign $\mu\mu$ channel with one jet.

Efficiency for the same-sign $\mu\mu$ channel with two or three jets.

The observed and expected $E_T^{miss}$ distribution in the dimuon SR-Z. The negigible estimated contribution from Z+jets is omitted in these distributions. The last bin contains the overflow.

The observed and expected dielectron invariant mass distribution in SR-loose. The last bin contains the overflow.

The observed and expected dimuon invariant mass distribution in SR-loose. The last bin contains the overflow.

The observed and expected dielectron invariant mass distribution in the two-jet $b$-veto SR. The last bin contains the overflow.

The observed and expected dimuon invariant mass distribution in the two-jet $b$-veto SR. The last bin contains the overflow.

The observed and expected dielectron invariant mass distribution in the four jet b-veto SR. The last bin contains the overflow.

The observed and expected dimuon invariant mass distribution in the four-jet $b$-veto SR. The last bin contains the overflow.

The observed and expected dielectron invariant mass distribution in the two-jet $b$-tag SR. The last bin contains the overflow.

The observed and expected dimuon invariant mass distribution in two-jet $b$-tag SR. The last bin contains the overflow.

The observed and expected dielectron invariant mass distribution in the four-jet $b$-tag SR. The last bin contains the overflow.

The observed and expected dimuon invariant mass distribution in the four-jet $b$-tag SR. The last bin contains the overflow.

Expected 95% exclusion contour for the GGM model with $\tan(\beta)=1.5$ in SR-Z.

Observed 95% exclusion contour for the GGM model with $\tan(\beta)=1.5$ in SR-Z.

Expected 95% exclusion contour for the GGM model with $\tan(\beta)=30$ in SR-Z.

Observed 95% exclusion contour for the GGM model with $\tan(\beta)=30$ in SR-Z.

Expected 95% exclusion contour for the two-step first- and second-generation squark simplified model with sleptons in the two-jet $b$-veto SR.

Observed 95% exclusion contour for the two-step first- and second-generation squark simplified model with sleptons in the two-jet $b$-veto SR.

Expected 95% exclusion contour for the two-step gluino simplified model with sleptons in the four-jet $b$-veto SR.

Observed 95% exclusion contour for the two-step gluino simplified model with sleptons in the four-jet $b$-veto SR.

Number of generated events in the two-step gluino simplified model with sleptons.

Production cross-section in the two-step gluino simplified model with sleptons.

Number of generated events in the two-step first- and second-generation squark simplified model with sleptons.

Production cross-section in the two-step first- and second-generation squark simplified model with sleptons.

Number of generated events in the GGM model with $\tan(\beta)=1.5$.

Production cross-section in the GGM model with $\tan(\beta)=1.5$.

Number of generated events in the GGM model with $\tan(\beta)=30$.

Production cross-section in the GGM model with $\tan(\beta)=30$.

Total experimental uncertainty [%] for the two-step gluino simplified model with sleptons.

Total experimental uncertainty [%] for the GGM model with $\tan(\beta)=1.5$.

Total experimental uncertainty for the GGM model with $\tan(\beta)=30$.

Signal acceptance for the GGM model with $\tan(\beta)=1.5$ in the combined electron and muon SR-Z.

Signal acceptance for the GGM model with $\tan(\beta)=30$ in the combined electron and muon SR-Z.

Signal efficiency for the GGM model with $\tan(\beta)=1.5$ in the dielectron SR-Z.

Signal efficiency for the GGM model with $\tan(\beta)=30$ in the dielectron SR-Z.

Signal efficiency for the GGM model with $\tan(\beta)=1.5$ in the dimuon SR-Z.

Signal efficiency for the GGM model with $\tan(\beta)=30$ in the dimuon SR-Z.

Signal efficiency for the GGM model with $\tan(\beta)=1.5$ in the electron and muon combined SR-Z.

Signal efficiency for the GGM model with $\tan(\beta)=30$ in the the electron and muon combined SR-Z.

Signal acceptance for the two-step first- and second-generation squarks simplified model with sleptons in the two-jet $b$-veto SR.

Signal acceptance for the two-step gluino simplified model with sleptons in the four-jet $b$-veto SR.

Signal efficiency for the two-step first- and second-generation squarks simplified model with sleptons in the two-jet $b$-veto SR.

Signal efficiency for the two-step gluino simplified model with sleptons in the four-jet $b$-veto SR.

Upper limits on the signal cross-section at 95% CL for the GGM model with $\tan(\beta)=1.5$.

Observed CL$_{\text{S}}$ for the GGM model with $\tan(\beta)=1.5$.

Expected CL$_{\text{S}}$ for the GGM model with $\tan(\beta)=1.5$.

Upper limits on the signal cross-section at 95% CL for the GGM model with $\tan(\beta)=30$.

Observed CL$_{\text{S}}$ for the GGM model with $\tan(\beta)=30$.

Expected CL$_{\text{S}}$ for the GGM model with $\tan(\beta)=30$.

Upper limits on the signal stength at 95% CL for the two-step first- and second-generation squark simplified model with sleptons. The excluded signal strength is defined as the ratio of the observed excluded production cross section to the expected production cross section calculated at NLO+NLL.

Upper limits on the signal stength at 95% CL for the two-step gluino simplified model with sleptons. The excluded signal strength is defined as the ratio of the observed excluded production cross section to the expected production cross section calculated at NLO+NLL.

Observed CL$_{\text{S}}$ for the two-step first- and second-generation squark simplified model with sleptons.

Expected CL$_{\text{S}}$ for the two-step first- and second-generation squark simplified model with sleptons.

Observed CL$_{\text{S}}$ for the two-step gluino simplified model with sleptons.

Expected CL$_{\text{S}}$ for the two-step gluino simplified model with sleptons.

Cutflow table for three benchmark signal points in SR-Z for the $ee$ and $\mu\mu$ channels separately. The three signal points are taken from the $\tan\beta = 1.5$ grid. 100000 events were generated for each of these points. Shown here are both the unweighted number of events and the number of events normalised to 20.3 fb$^{-1}$. The total experimental systematic uncertainty on the signal yields is indicated at the last cut, along with the corresponding observed and expected $CL_S$ values.

Cutflow table for three benchmark signal points in the two jet b-veto SR of the off-$Z$ search for the $ee$ and $\mu\mu$ channels separately. Shown here are both the unweighted number of events and the number of events normalised to 20.3$^{-1}$. Except for the last two rows indicating the dilepton mass requirements, quoted event yields include all requirements from the top of the table down to the given row.

Cutflow table for three benchmark signal points in the four jet b-veto SR of the off-$Z$ search for the $ee$ and $\mu\mu$ channels separately. Shown here are both the unweighted number of events and the number of events normalised to 20.3 fb$^{-1}$. Except for the last two rows indicating the dilepton mass requirements, quoted event yields include all requirements from the top of the table down to the given row.

Observed and expected $E_T^{miss}$ distribution in soft dimuon signal region. The last bin includes the overflow.

Observed and expected $m_{eff}^{incl}$ distribution in hard single-lepton 3-jet signal region. The last bin includes the overflow.

Observed and expected $m_{eff}^{incl}$ distribution for hard single-lepton 5-jet signal region. The last bin includes the overflow.

Observed and expected $E_{T}^{miss}$ distribution for hard single-lepton 6-jet signal region. The last bin includes the overflow.

Observed and expected $M_{R}'$ distribution for hard same-flavour dilepton low-multiplicity signal region. The last bin includes the overflow.

Observed and expected $M_{R}'$ distribution for hard same-flavour dilepton 3-jet signal region. The last bin includes the overflow.

Observed and expected $M_{R}'$ distribution for hard opposite-flavour dilepton low-multiplicity signal region. The last bin includes the overflow.

Observed and expected $M_{R}'$ distribution for hard opposite-flavour dilepton 3-jet opposite-flavour signal region. The last bin includes the overflow.

Observed 95% exclusion contour for the mSUGRA/CMSSM model with $\tan\beta=30$, $A_{0}=-2m_{0}$ and $\mu > 0$.

Expected 95% exclusion contour for the mSUGRA/CMSSM model with $\tan\beta=30$, $A_{0}=-2m_{0}$ and $\mu > 0$.

Observed 95% exclusion contour for the bRPV MSUGRA/CMSSM model.

Expected 95% exclusion contour for the bRPV MSUGRA/CMSSM model.

Observed 95% exclusion contour for the natural gauge mediation with a stau NLSP model (nGM).

Expected 95% exclusion contour for the natural gauge mediation with a stau NLSP model (nGM).

Observed 95% exclusion contour for the non-universal higgs masses with gaugino mediation model (NUHMG).

Expected 95% exclusion contour for the non-universal higgs masses with gaugino mediation model (NUHMG).

Observed 95% exclusion contour for the minimal UED model from the combination of the hard dilepton and soft dilepton analyses.

Expected 95% exclusion contour for the minimal UED model from the combination of the hard dilepton and soft dilepton analyses.

Observed 95% exclusion contour for the minimal UED model from the hard dilepton analysis.

Expected 95% exclusion contour for the minimal UED model from the hard dilepton analysis.

Observed 95% exclusion contour for the minimal UED model from the soft dilepton analysis.

Expected 95% exclusion contour for the minimal UED model from the soft dilepton analysis.

Observed 95% exclusion contour for the simplified model with gluino-mediated top squark production where the top squark is assumed to decay exclusively via $\tilde{t} \rightarrow c \tilde{\chi}^{0}_{1}$.

Expected 95% exclusion contour for the simplified model with gluino-mediated top squark production, where the top squark is assumed to decay exclusively via $\tilde{t} \rightarrow c \tilde{\chi}^{0}_{1}$.

Observed 95% exclusion contour for the simplified model with gluino-mediated top squark production where the gluinos are assumed to decay exclusively through a virtual top squark, $\tilde{g} \rightarrow tt+\tilde{\chi}^{0}_{1}$.

Expected 95% exclusion contour for the simplified model with gluino-mediated top squark production where the gluinos are assumed to decay exclusively through a virtual top squark, $\tilde{g} \rightarrow tt+\tilde{\chi}^{0}_{1}$.

Observed 95% exclusion contour for the gluino simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Expected 95% exclusion contour for the gluino simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Observed 95% exclusion contour for the gluino simplified model from the hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Expected 95% exclusion contour for the gluino simplified model from the hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Observed 95% exclusion contour for the gluino simplified model from the soft single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Expected 95% exclusion contour for the gluino simplified model from the soft single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Observed 95% exclusion contour for the the first- and second-generation squark simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) = 1/2.

Expected 95% exclusion contour for the the first- and second-generation squark simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) = 1/2.

Observed 95% exclusion contour for the the first- and second-generation squark simplified model from the hard single-lepton analysis for the case in which the chargino mass is fixed at x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) = 1/2.

Expected 95% exclusion contour for the the first- and second-generation squark simplified model from the hard single-lepton analysis for the case in which the chargino mass is fixed at x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) = 1/2.

Observed 95% exclusion contour for the the first- and second-generation squark simplified model from the soft single-lepton analysis for the case in which the chargino mass is fixed at x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) = 1/2.

Expected 95% exclusion contour for the the first- and second-generation squark simplified model from the soft single-lepton analysis for the case in which the chargino mass is fixed at x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) = 1/2.

Observed 95% exclusion contour for the gluino simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected 95% exclusion contour for the gluino simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% exclusion contour for the gluino simplified model from the hard single-lepton analysis for the case in which x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected 95% exclusion contour for the gluino simplified model from the hard single-lepton analysis for the case in which x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% exclusion contour for the gluino simplified model from the soft single-lepton analysis for the case in which x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected 95% exclusion contour for the gluino simplified model from the soft single-lepton analysis for the case in which x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% exclusion contour for the first- and second-generation squark simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected 95% exclusion contour for the first- and second-generation squark simplified model from the combination of soft single-lepton and hard single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% exclusion contour for the first- and second-generation squark simplified model from the hard single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected 95% exclusion contour for the first- and second-generation squark simplified model from the hard single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% exclusion contour for the first- and second-generation squark simplified model from the soft single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected 95% exclusion contour for the first- and second-generation squark simplified model from the soft single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% exclusion contour for the two-step gluino simplified model with sleptons from the combination of the hard dilepton and hard single-lepton analyses.

Expected 95% exclusion contour for the two-step gluino simplified model with sleptons from the combination of the hard dilepton and hard single-lepton analyses.

Observed 95% exclusion contour for the two-step gluino simplified model with sleptons from the hard single-lepton analysis.

Expected 95% exclusion contour for the two-step gluino simplified model with sleptons from the hard single-lepton analysis.

Observed 95% exclusion contour for the two-step gluino simplified model with sleptons from the hard dilepton analysis.

Expected 95% exclusion contour for the two-step gluino simplified model with sleptons from the hard dilepton analysis.

Observed 95% exclusion contour for the two-step first- and second-generation squark simplified model with sleptons from the hard dilepton analysis.

Expected 95% exclusion contour for the two-step first- and second-generation squark simplified model with sleptons from the hard dilepton analysis.

Observed 95% exclusion contour for the two-step gluino simplified model without sleptons from the hard single-lepton analysis.

Expected 95% exclusion contour for the two-step gluino simplified model without sleptons from the hard single-lepton analysis.

Number of generated events in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Production cross-section in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Number of generated events in the the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV. squark decaying to quark neutralino1 with varying x.

Production cross-section in the the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Number of generated evens in the minimal UED model.

Production cross-section in the minimal UED model in pb.

Number of generated events in the two-step first- and second-generation squark simplified model with sleptons.

Production cross-section in the two-step first- and second-generation squark simplified model with sleptons.

Acceptance for soft single-lepton 3-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Efficiency for soft single-lepton 3-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Acceptance for soft single-lepton 5-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Efficiency for soft single-lepton 5-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Acceptance for soft single-lepton 3-jet inclusive signal region in the gluino simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Efficiency for the soft single-lepton 3-jet inclusive signal region in the gluino simplified model for the case in x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected CLs from the combination of the soft single-lepton and hard single-lepton analyses in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Expected CLs from the combination of the soft single-lepton and hard single-lepton analyses in the gluino simplified model for the case in which the chargino mass is varied and the LSP mass is set at 60 GeV. The chargino mass is parameterised using x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)).

Observed CLs from the combination of the soft single-lepton and hard single-lepton analyses in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Observed CLs from the combination of the soft single-lepton and hard single-lepton analyses in the gluino simplified model for the case in which the chargino mass is varied and the LSP mass is set at 60 GeV. The chargino mass is parameterised using x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)).

Acceptance for soft dimuon signal region in the minimal UED model (mUED).

Efficiency for soft dimuon signal region in minimal UED model (mUED).

Acceptance for hard dilepton 3-jet opposite-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Efficiency for hard dilepton 3jet opposite-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Acceptance for hard dilepton 3-jet same-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Efficiency for hard dilepton 3-jet same-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Acceptance for hard dilepton low-multiplicity opposite-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Efficiency for hard dilepton low-multiplicity opposite-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Acceptance for hard dilepton low-multiplicity same-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Efficiency for hard dilepton low-multiplicity same-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Best expected signal region in the minimal UED model (mUED).

Expected CLs from hard dilepton analysis in the two-step first- and second-generation squark simplified model with sleptons.

Observed CLs from the hard dilepton analysis in the two-step first- and second-generation squark simplified model with sleptons.

Expected CLs from the combination of the soft dimuon and hard dilepton analyses in the minimal UED model (mUED).

Observed CLs from the combination of the soft dimuon and hard dilepton analyses in the minimal UED model (mUED).

Acceptance for hard single-lepton 3-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Efficiency for hard single-lepton 3-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Acceptance for hard single-lepton 5-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Efficiency for hard single-lepton 5-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Acceptance for hard single-lepton 6-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Efficiency for hard single-lepton 6-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Acceptance for hard single-lepton 3-jet signal region in the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Efficiency for hard single-lepton 3-jet signal region in the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Acceptance for hard single-lepton 5-jet signal region in the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Efficiency for hard single-lepton 5-jet signal region in the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Acceptance for hard single-lepton 6-jet signal region in the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Efficiency for hard single-lepton 6-jet signal region in the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% upper limit on the visible cross-section in the gluino simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Observed 95% upper limit on the visible cross-section in the first- and second-generation squark simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% upper limit on the visible cross-section in the first- and second-generation squark simplified model with sleptons from the hard dilepton analysis.

Observed 95% upper limit on the visible cross-section in the minimal UED model (mUED) from the combination of the soft dimuon and hard dilepton analyses.

The LAMBDA reconstruction and selection efficiency EFF as a function of PT and XF.

The LAMBDABAR reconstruction and selection efficiency EFF as a function of PT and XF.

Observed and expected numbers of events with exactly three leptons with the scalar sum of jet transverse momentum values HT < 200 GeV. "On-Z" refers to events with at least one E+ E- or MU+ MU- (OSSF) pair with dilepton mass between 75 and 105 GeV, while "Off-Z" refers to events with one or two OSSF pairs, none of which fall in this mass range. The OSSFN designation refers to the number of E+ E- and MU+ MU- pairs in the event. Search channels binned in ET have been combined into coarse ET bins for the purposes of presentation.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> HIGGS GRAVITINO) = BR(NEUTRALINO1 --> Z GRAVITINO) = 0.5 for strong plus electroweak production.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> HIGGS GRAVITINO) = 1.0 for strong plus electroweak production.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0 for strong plus electroweak production.

The product of acceptance and efficiency for the calculation of the 95% C.L. limit for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> HIGGS GRAVITINO) = BR(NEUTRALINO1 --> Z0 GRAVITINO) = 0.5. The chargino-Higgsino mass is fixed at 150 GeV.

The product of acceptance and efficiency for the calculation of the 95% C.L. limit for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> HIGGS GRAVITINO) = BR(NEUTRALINO1 --> Z0 GRAVITINO) = 0.5. The chargino-Higgsino mass is fixed at 350 GeV.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> HIGGS GRAVITINO) = 1.0. The chargino-Higgsino mass is fixed at 150 GeV.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> HIGGS GRAVITINO) = 1.0. The chargino-Higgsino mass is fixed at 350 GeV.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0. The chargino-Higgsino mass is fixed at 150 GeV.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0. The chargino-Higgsino mass is fixed at 350 GeV.

The product of acceptance and efficiency for the calculation of the 95% C.L. limit on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 150 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z GRAVITINO) = 1.0 and strong plus weak production.

The product of acceptance and efficiency for the calculation of the 95% C.L. limit on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 250 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0 and strong plus weak production.

The product of acceptance and efficiency for the calculation of the 95% C.L. limit on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 350 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0 and strong plus weak production.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the slepton co-NLSP model in the gluino-chargino (wino-like chargino) mass plane.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the stau-NLSP and stau-NNLSP scenario in the degenerate smuon- and selectron- stau mass plane.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the T1tttt model in the gluino-neutralino mass plane.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the T6ttWW model in the sbottom-chargino mass plane.

Observed 95% C.L. exclusion contour for the T1tttt scenario.

Observed - 1sig(theoretical) 95% C.L. exclusion contour for the T1tttt scenario.

Observed + 1sig(theoretical) 95% C.L. exclusion contour for the T1tttt scenario.

Expected 95% C.L. exclusion contour for the T1tttt scenario.

Expected - 1sig 95% C.L. exclusion contour for the T1tttt scenario.

Expected + 1sig 95% C.L. exclusion contour for the T1tttt scenario.

Observed 95% C.L. exclusion contour for the T6ttWW scenario.

Observed - 1sig(theoretical) 95% C.L. exclusion contour for the T6ttWW scenario.

Observed + 1sig(theoretical) 95% C.L. exclusion contour for the T6ttWW scenario.

Expected 95% C.L. exclusion contour for the T6ttWW scenario.

Expected - 1sig 95% C.L. exclusion contour for the T6ttWW scenario.

Expected + 1sig 95% C.L. exclusion contour for the T6ttWW scenario.

Observed and expected 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> HIGGS GRAVITINO) = BR(NEUTRALINO1 --> Z GRAVITINO) = 0.5 for strong plus electroweak production.

Observed and expected 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> HIGGS GRAVITINO) = 1.0 for strong plus electroweak production. Successive instances of SIG(OBS) = SIG(EXP) =0 have been rebinned over M(STOP) to reduce the size of the table.

Observed and expected 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> Z0 GLUINO) = 1.0 for strong plus electroweak production.

Observed 95% C.L. limits on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 150 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z GRAVITINO) = 1.0 and strong plus weak production.

Observed 95% C.L. limits on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 250 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z GRAVITINO) = 1.0 and strong plus weak production.

Observed 95% C.L. limits on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 350 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z GRAVITINO) = 1.0 and strong plus weak production.

Observed and expected 95% C.L. limits for the slepton co-NLSP model in the gluino-chargino (wino-like chargino) mass plane are shown.

Observed and expected 95% C.L. limits for the stau-NLSP and stau-NNLSP scenario in the degenerate smuon- and selectron- stau mass plane are shown. Successive instances of SIG(OBS) = SIG(EXP) =0 have been rebinned over M(SELECTRON) to reduce the size of the table.

Observed and expected 95% C.L. limits for the T1tttt model in the gluino-neutralino mass plane are shown.

Observed and expected 95% C.L. limits for the T6ttWW model in the sbottom-chargino mass plane are given.

The effective mass distribution in VR2Z.

The ETmiss distribution in SR0noZa.

The effective mass distribution in SR0noZa.

The ETmiss distribution in SR1noZa.

The effective mass distribution in SR1noZa.

The ETmiss distribution in SR2noZa.

The effective mass distribution in SR2noZa.

The ETmiss distribution in SR0noZb.

The effective mass distribution in SR0noZb.

The ETmiss distribution in SR1noZb.

The effective mass distribution in SR1noZb.

The ETmiss distribution in SR2noZb.

The effective mass distribution in SR2noZb.

The ETmiss distribution in SR0Z.

The effective mass distribution in SR0Z.

The ETmiss distribution in SR1Z.

The effective mass distribution in SR1Z.

The ETmiss distribution in SR2Z.

The effective mass distribution in SR2Z.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the R-slepton RPC model.

Expected 95% CL exclusion contour for the R-slepton RPC model.

Observed and expected 95% CL cross-section upper limits for the Stau RPC model, together with the theoretically predicted cross-section.

Observed and expected 95% CL cross-section upper limits for the Z RPC model, together with the theoretically predicted cross-section.

Observed 95% CL exclusion contour for the GGM tan beta = 1.5 model.

Expected 95% CL exclusion contour for the GGM tan beta = 1.5 model.

Observed 95% CL exclusion contour for the GGM tan beta = 30 model.

Expected 95% CL exclusion contour for the GGM tan beta = 30 model.

Observed 95% CL cross-section upper limit for the RPV chargino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV chargino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV gluino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV gluino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Lslepton NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Lslepton NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Rslepton NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Rslepton NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV sneutrino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV sneutrino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the R-slepton RPC model, and the selection of Z-veto signal regions used to set limits in this model. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bbb' means that the regions SR0noZb, SR1noZb and SR2noZb were used, in addition to the three Z-rich regions (SR0-2Z). For the RPC stau and Z models, the ``aaa' combination of regions was used throughout.

Performance of the SR0noZa selection in the R-slepton RPC model: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR0noZb selection in the RPV chargino NLSP model with lambda_121 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR1noZa selection in the RPV sneutrino NLSP model with lambda_233 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR1noZb selection in the RPV gluino NLSP model with lambda_133 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR2noZa selection in the RPV sneutrino NLSP model with lambda_233 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR2noZb selection in the RPV gluino NLSP model with lambda_133 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR0Z selection in the GGM tan beta = 30 model: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Cut flows for a representative selection of SUSY signal points in the Z-veto signal regions. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise.

Cut flows for a representative selection of SUSY signal points in the Z-rich signal regions. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses (or the value of mu in the case of GGM models). The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise.

Cut flows by lepton channel for a representative selection of SUSY signal points in the SR0noZa signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The RPC R-slepton model is used, with (m2,m1) = (450,300) GeV.

Cut flows by lepton channel for a representative selection of SUSY signal points in the SR1noZb signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The RPV gluino NLSP model is used, with lambda_133 != 0 and (m2,m1) = (800,400) GeV.

Cut flows by lepton channel for a representative selection of SUSY signal points in the SR0Z signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the value of mu. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The GGM tan beta = 30 model is used, with (m2,m1) = (200,1000) GeV.