(1) Number of generated MC events for the spin 1/2 top partner signal grid (2) Relative Cross section uncertainties for the spin 1/2 top partner signal grid.

(1) Acceptance of the same flavour selection for the spin 1/2 top partner signal grid (2) Selection efficiency of the same flavour selection for the spin 1/2 top partner signal grid (3) Product of the acceptance and efficiency of the same flavour selection for the spin 1/2 top partner signal grid (4) Relative experimental uncertainties on the acceptance times efficiency of the same flavour selection for the spin 1/2 top partner signal grid.

(1) Acceptance of the different flavour selection for the spin 1/2 top partner signal grid (2) Selection efficiency of the different flavour selection for the spin 1/2 top partner signal grid (3) Product of the acceptance and efficiency of the different flavour selection for the spin 1/2 top partner signal grid (4) Relative experimental uncertainties on the acceptance times efficiency of the different flavour selection for the spin 1/2 top partner signal grid.

(1) Observed CLs values for the scalar top signal grid (2) Expected CLs values for the scalar top signal grid.

(1) Observed CLs values for the spin 1/2 top partner signal grid (2) Expected CLs values for the spin 1/2 top partner signal grid.

Cross section limits [pb] for the scalar top signal grid.

Cross section limits [pb] for the spin 1/2 top partner signal grid.

Observed 95% CL limit for stop grid as a function of the scalar top and neutralino masses.

Observed 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying signal cross section of +1sigma.

Observed 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying signal cross section of -1sigma.

Expected 95% CL limit for stop grid as a function of the scalar top and neutralino masses.

Expected 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying the uncertainty of +1sigma.

Expected 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying the uncertainty of -1sigma.

Observed 95% CL limit for top partner grid as a function of the top partner and neutralino masses.

Observed 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying signal cross section of +1sigma.

Observed 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying signal cross section of -1sigma.

Expected 95% CL limit for top partner grid as a function of the top partner and neutralino masses.

Expected 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying the uncertainty of +1sigma.

Expected 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying the uncertainty of -1sigma.

The stop pair production cross section and its uncertainty due to PDF, factorization and the renormalization scales.

The expected limit contour in the GLUINO-NEUTRALINO plane.

The observed limit contour in the SQUARK-NEUTRALINO plane.

The expected limit contour in the SQUARK-NEUTRALINO plane.

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.

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 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.

Numbers of observed and background events for SR3L low for each bin of the distribution in Meff. The table corresponds to Fig. 4(d). The statistical and systematic uncertainties are combined for the predicted numbers.

Numbers of observed and background events for SR3L high for each bin of the distribution in Meff. The table corresponds to Fig. 4(e). The statistical and systematic uncertainties are combined for the predicted numbers.

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

The efficiencies are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

The efficiencies are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.

The efficiencies are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into b s and gluinos decay into t stop (see Fig. 5d in the paper).

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

The efficiencies are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

The acceptances (in percent, %) are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

The acceptances (in percent, %) are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.

The acceptances (in percent, %) are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

The acceptances (in percent, %) are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

The limits on observed cross section are calculated for all simplified models. The simplified models are for direct pair production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair-production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

The signal event yields are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

The signal event yields are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop)-20 GeV.

The signal event yields are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

The signal event yields are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

Experimental uncertainties on the signal event yields are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

Experimental uncertainties on the signal event yields are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.

Experimental uncertainties on the signal event yields are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

Experimental uncertainties on the signal event yields are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

Statistical uncertainties on the signal event yields are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

Statistical uncertainties on the signal event yields are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.

Statistical uncertainties on the signal event yields are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

Statistical uncertainties on the signal event yields are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W ^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

The confidence levels are calculated for all simplified models. For each model, the observed and expected values are given. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.

The confidence levels are calculated for all simplified models. For each model, the observed and expected values are given. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).

The confidence levels are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluion), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).

The confidence levels are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the expected and observed values are given. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).

The confidence levels are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the expected and observed values are given. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.

The confidence levels are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the expected and observed values are given.

The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).

The confidence levels are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the expected and observed values are given. The model assumes tan(beta)=30, A0=2m0, and mu>0.

Selection acceptance times efficiency as a function of WPRIME mass at truth level for left- and right-handed WPRIME MC. The total efficiency curves correspond to the sum of the efficiencies of the one b-tag and two b-tag categories.

Cutflow (efficiency with respect to total number of events in %) for several WPRIME masses in the left-handed and in the right-handed model for hadronic top-quark decays.

Overview of the signal acceptance times efficiency (A x Eff) for the hadronic top-quark decay for both categories, the predicted cross section times branching ratio to TOP BOTTOM, as well as the observed 95% CL limit on the cross section times branching ratio for several WPRIME masses in the left-handed and in the right-handed model. The expected signal event yields in the two categories for 20.3 fb-1 of 8 TeV data are also shown.

Transverse momentum distribution for the second leading lepton for events in the SR2 signal region for DATA and SM predictions.

Transverse momentum distribution for the third leading lepton for events in the SR1 signal region for DATA and SM predictions.

Transverse momentum distribution for the third leading lepton for events in the SR2 signal region for DATA and SM predictions.

Missing transverse energy for events in the SR1 signal region for DATA and SM predictions.

Missing transverse energy for events in the SR2 signal region for DATA and SM predictions.

Invariant mass of the same-flavour-opposite-sign (SFOS) lepton pair for events in the SR1 signal region for DATA and SM predictions.

The Cross Section in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.

The Cross Section in signal region SR1 for the SUSY simplified model grid.

The Number of generated Events in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.

The Number of generated Events in signal region SR1 for the SUSY simplified model grid.

The Efficiency in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.

The Efficiency in signal region SR1 for the SUSY simplified model grid.

The Acceptance in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.

The Acceptance in signal region SR1 for the SUSY simplified model grid.

The Acceptance*Efficiency in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.

The Acceptance*Efficiency in signal region SR1 for the SUSY simplified model grid.

The Systematic Uncertainty of the data (excluding the Monte Carlo) in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.

The Systematic Uncertainty of the data (excluding the Monte Carlo) in signal region SR1 for the SUSY simplified model grid.

CL values for the pMSSM with M1=100 GeV model grid for the SR1 signal region.

CL values for the simplified model model grid for the SR1 signal region.

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.

Ratio of the Z'NU to Z'SSM acceptance times efficiency (ACC*EFF) in the lep-had channel as a function of sin^2phi and the Z' mass.

Z' SSM acceptance (ACC) and product of acceptance and efficiency (ACC*EFF) for the had-had and lep-had selections as a function of the Z' mass.

Number of expected Z'SSM signal (NS), background (NB) and observed (N) events passing the total transverse mass ($m_{\rm T}^{\rm tot}$) threshold in the had-had and lep-had channels.

Median expected and observed 95% CL upper limits on the cross-section times branching fraction to tau+tau- for Z'SSM production for the exclusive had-had and lep-had channels, and for both channels combined.

Observed 95% CL upper limits on the cross-section times branching fraction to tau+tau- for Z'L and Z'R production for the combination of the had-had and lep-had channels.

Observed 95% CL lower limit on the Z'NU mass as a function of sin^2(phi).

Expected 95% CL exclusion contour for the Gbb signal.

Observed 95% CL exclusion contour for the Gbb signal.

Expected 95% CL exclusion contour for the Gtt combination.

Observed 95% CL exclusion contour for the Gtt combination.

Acceptances for the Gbb model in SR-Gbb-A. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.

Acceptances for the Gbb model in SR-Gbb-B. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.

Acceptances for the Gbb model in SR-Gbb-C. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.

Acceptances for the Gtt model in SR-Gtt-0L-A. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.

Acceptances for the Gtt model in SR-Gtt-0L-B. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.

Acceptances for the Gtt model in SR-Gtt-0L-C. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.

Acceptances for the Gtt model in SR-Gtt-1L-A. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.

Acceptances for the Gtt model in SR-Gtt-1L-B. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.

Acceptance times efficiency for the Gbb model in SR-Gbb-A.

Acceptance times efficiency for the Gbb model in SR-Gbb-B.

Acceptance times efficiency for the Gbb model in SR-Gbb-C.

Acceptance times efficiency for the Gtt model in SR-Gtt-0L-A.

Acceptance times efficiency for the Gtt model in SR-Gtt-0L-B.

Acceptance times efficiency for the Gtt model in SR-Gtt-0L-C.

Acceptance times efficiency for the Gtt model in SR-Gtt-1L-A.

Acceptance times efficiency for the Gtt model in SR-Gtt-1L-B.

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

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-C.

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

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-C.

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

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

Signal region yielding the best expected sensitivity for each point of the parameter space in the Gbb model.

Signal region yielding the best expected sensitivity for each point of the parameter space in the Gtt model for the 0-lepton channel.

Signal region yielding the best expected sensitivity for each point of the parameter space in the Gtt model for the 1-lepton channel.

Combination of two 0-lepton and 1-lepton signal regions yielding the best expected sensitivity for each point of the parameter space in the Gtt model.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 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 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 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.

Observed 95% CL limit for the pMSSM grid.

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

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.

+1 sigma excursion of the expected 95% CL limit for the pMSSM grid.

-1 sigma excursion of the expected 95% CL limit for the pMSSM grid.

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.

+1 sigma excursion of the expected 95% CL limit for the 2Step grid.

-1 sigma excursion of the expected 95% CL limit for the 2Step grid.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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.

Degree of multijet closure for signal and vaidation regions with at no b-jet requirement. 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 bins labelled in bold are signal regions, while the others are validation regions. 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 with at least 1 b-jet. 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 bins labelled in bold are signal regions, while the others are validation regions. 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 with at least 2 b-jets. 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 bins labelled in bold are signal regions, while the others are validation regions. 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).

Summary of all 15 signal regions (post-fit).

Signal region yielding the best-expected CLs value, the best expected CLs value, and the corresponding observed CLs value for the 2Step grid.

Signal region yielding the best-expected CLs value, the best expected CLs value, and the corresponding observed CLs value for the pMSSM grid.

95% CLs observed upper limit on model cross-section for 2-step signal points for the best-expected signal region.

Performance of the 8j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 9j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 9j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 9j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 10j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 10j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 10j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 7j80-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 7j80-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 7j80-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j80-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j80-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j80-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 9j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 9j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 9j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 10j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 10j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 10j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 7j80-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 7j80-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 7j80-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j80-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j80-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

Performance of the 8j80-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.

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).

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Signal acceptance for SR2jl in squark direct decay model grid.

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

Signal acceptance for SR2jm in squark direct decay model grid.

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

Signal acceptance for SR2jt in squark direct decay model grid.

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

Signal acceptance for SR4jt in squark direct decay model grid.

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

Signal acceptance for SR5j in squark direct decay model grid.

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

Signal acceptance for SR6jm in squark direct decay model grid.

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

Signal acceptance for SR6jt in squark direct decay model grid.

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

Signal acceptance for SR2jl in gluino direct decay model grid.

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

Signal acceptance for SR2jm in gluino direct decay model grid.

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

Signal acceptance for SR2jt in gluino direct decay model grid.

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

Signal acceptance for SR4jt in gluino direct decay model grid.

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

Signal acceptance for SR5j in gluino direct decay model grid.

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

Signal acceptance for SR6jm in gluino direct decay model grid.

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

Signal acceptance for SR6jt in gluino direct decay model grid.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Missing transverse momentum distribution after SR3b selection, beside the $E_\mathrm{T}^\mathrm{miss}$ requirement. The results in the signal region correspond to the last inclusive bin. The systematic uncertainties include theory uncertainties for the backgrounds with prompt SS/3L and the full systematic uncertainties for data-driven backgrounds. For illustration the distribution for a benchmark SUSY scenario ($pp\to \tilde g\tilde g$, $\tilde g\to t\bar t\tilde\chi_1^0$, $m_{\tilde g}=1.2$ TeV, $m_{\tilde\chi_1^0}=0.7$ TeV) is also shown.

Observed exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qq(\tilde\ell\ell/\tilde\nu\nu)$ decays. All limits are computed at 95% CL.

Expected exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qq(\tilde\ell\ell/\tilde\nu\nu)$ decays. All limits are computed at 95% CL.

Upper limits on signal cross-sections as function of the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qq(\tilde\ell\ell/\tilde\nu\nu)$ decays, obtained using the signal efficiency and acceptance specific to each model. All limits are computed at 95% CL.

Observed exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qqWZ\tilde\chi_1^0$ decays. All limits are computed at 95% CL.

Expected exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qqWZ\tilde\chi_1^0$ decays. All limits are computed at 95% CL.

Upper limits on signal cross-sections as function of the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qqWZ\tilde\chi_1^0$ decays, obtained using the signal efficiency and acceptance specific to each model. All limits are computed at 95% CL.

Observed exclusion limits on the $\tilde b_1$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde b_1\tilde b_1^*$ pair production with exclusive $\tilde b_1\to t\tilde\chi_1^-$ decays. All limits are computed at 95% CL.

Expected exclusion limits on the $\tilde b_1$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde b_1\tilde b_1^*$ pair production with exclusive $\tilde b_1\to t\tilde\chi_1^-$ decays. All limits are computed at 95% CL.

Upper limits on signal cross-sections as function of the $\tilde b_1$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde b_1\tilde b_1^*$ pair production with exclusive $\tilde b_1\to t\tilde\chi_1^-$ decays, obtained using the signal efficiency and acceptance specific to each model. All limits are computed at 95% CL.

Observed exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to t\bar t\tilde\chi_1^0$ decays. All limits are computed at 95% CL.

Expected exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to t\bar t\tilde\chi_1^0$ decays. All limits are computed at 95% CL.

Upper limits on signal cross-sections as function of the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to t\bar t\tilde\chi_1^0$ decays, obtained using the signal efficiency and acceptance specific to each model. All limits are computed at 95% CL.

SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to q\bar q(\tilde\ell\ell/\tilde\nu\nu)$ decay: signal acceptance (in %) in the signal region SR0b3j. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to q\bar q(\tilde\ell\ell/\tilde\nu\nu)$ decay: reconstruction efficiency (in %) in the signal region SR0b3j. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to q\bar qWZ\tilde\chi_1^0$ decay: signal acceptance (in %) in the signal region SR0b5j. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to q\bar qWZ\tilde\chi_1^0$ decay: reconstruction efficiency (in %) in the signal region SR0b5j. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde b_1\tilde b_1^*$ production and $\tilde b_1\to tW\tilde\chi_1^0$ decay: signal acceptance (in %) in the signal region SR1b. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde b_1\tilde b_1^*$ production and $\tilde b_1\to tW\tilde\chi_1^0$ decay: reconstruction efficiency (in %) in the signal region SR1b. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to t\bar t\tilde\chi_1^0$ decay: signal acceptance (in %) in the signal region SR3b. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to t\bar t\tilde\chi_1^0$ decay: reconstruction efficiency (in %) in the signal region SR3b. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].

Acceptance times efficiency for the tight channel of the Razor analysis for the direct squark-squark model.

Acceptance for the 1tau channel of the Taus+jets+MET analysis for the gluino simplified model.

Efficiency for the 1tau channel of the Taus+jets+MET analysis for the gluino simplified model.

Acceptance for the 2tau channel of the Taus+jets+MET analysis for the gluino simplified model.

Efficiency for the 2tau channel of the Taus+jets+MET analysis for the gluino simplified model.

Acceptance for the 1tau channel of the Taus+jets+MET analysis for the squark simplified model.

Efficiency for the 1tau channel of the Taus+jets+MET analysis for the squark simplified model.

Acceptance for the 2tau channel of the Taus+jets+MET analysis for the squark simplified model.

Efficiency for the 2tau channel of the Taus+jets+MET analysis for the squark simplified model.

Observed limit on the cross-section times branching ratio in fb at 95% CL for the direct squark-squark model.

Observed limit on the cross-section times branching ratio in fb at 95% CL for the gluino simplified model, obtained by the Taus+jets+MET analysis.

Observed limit on the cross-section times branching ratio in fb at 95% CL for the squark simplified model, obtained by the Taus+jets+MET analysis.

Observed 95% CL cross section times branching ratio upper limit on pMSSM qLqL production with M1=60 GeV and $m_{\tilde g}=$1.6 TeV interpreted by the 0L analysis including its two dedicated signal regions.

Observed 95% CL cross section times branching ratio upper limit on pMSSM qLqL production with M2=(M1+mqL)/2 and $m_{\tilde g}=$1.6 TeV interpreted by the 0L analysis including its two dedicated signal regions.

Observed 95% CL cross section times branching ratio upper limit on pMSSM qLqL production with M1=60 GeV with $m_{\tilde g}=$2.2 TeV interpreted by the 0L analysis including its two dedicated signal regions.

Observed 95% CL cross section times branching ratio upper limit on pMSSM qLqL production with M2=(M1+mqL)/2 and $m_{\tilde g}=$2.2 TeV interpreted by the 0L analysis including its two dedicated signal regions.

Observed 95% CL cross section times branching ratio upper limit on pMSSM qLqL production with M1=60 GeV and $m_{\tilde g}=$3.0 TeV interpreted by the 0L analysis including its two dedicated signal regions.

Observed 95% CL cross section times branching ratio upper limit on pMSSM qLqL production with M2=(M1+mqL)/2 and $m_{\tilde g}=$3.0 TeV interpreted by the 0L analysis including its two dedicated signal regions.

Observed and expected limits on the cross-section times branching ratio in fb at 95% CL for the gluino-mediated stop model with off-shell stops, for mass points with four- or five-body gluino decays, obtained by the SS/3L and 0/1L3B analyses.

: Cut flow for signal regions 0L_4jt+ and 0L_5jt of baseline signal points normalized to 20.3 fb$^\mathrm{-1}$. The point used for the 0L_4jt+ cutflow is mqL = 1150 GeV, M1 = 60 GeV, M2 = 1000 GeV, m(gluino) = 2200 GeV. The point used for the 0L_5jt cutflow is mqL = 950 GeV, M1 = 100 GeV, M2 = 525 GeV, m(gluino) = 2200 GeV.

Cut flow for the 1L(H)_7-jet SR (electron channel) for the main background from the $t\bar{t}$ production. The events are normalized to 20.3 fb$^\mathrm{-1}$.

Cut flow for the 1L(H)_7-jet SR (muon channel) for the main background from the $t\bar{t}$ production. The events are normalized to 20.3 fb$^\mathrm{-1}$.

Cut flow for 1L(H)_7-jet SR (electron channel). The signal point is taken from the gluino simplified model with 1-step decay via charginos and parameters $m_{\tilde{g}}$ = 1145 GeV, $m_{{\tilde \chi}_{1}^{\pm}}$ = 785 GeV, $m_{\tilde{\chi}_{1}^{0}}$ = 425 GeV; 20000 events were generated for this point. The events are normalized to 20.3 fb$^\mathrm{-1}$.

Cut flow for 1L(H)_7-jet SR (muon channel). The signal point is taken from the gluino simplified model with 1-step decay via charginos and parameters $m_{\tilde{g}}$ = 1145 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 785 GeV, $m_{\tilde{\chi}_{1}^{0}}$ = 425 GeV; 20000 events were generated for this point. The events are normalized to 20.3 fb$^\mathrm{-1}$.

Cut flow for 1L(H)_7-jet SR (electron channel). The signal point is taken from the gluino simplified model with 1-step decay via charginos and parameters $m_{\tilde{g}}$ = 1025 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 545 GeV, $m_{\tilde{\chi}_{1}^{0}}$ = 65 GeV; 20000 events were generated for this point. The events are normalized to 20.3 fb$^\mathrm{-1}$.

Cut flow for 1L(H)_7-jet SR (muon channel). The signal point is taken from the gluino simplified model with 1-step decay via charginos and parameters $m_{\tilde{g}}$ = 1025 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 545 GeV, $m_{\tilde{\chi}_{1}^{0}}$ = 65 GeV; 20000 events were generated for this point. The events are normalized to 20.3 fb$^\mathrm{-1}$.

Cut flow for 0LRaz_SR$_{\rm loose}$ and 0LRaz_SR$_{\rm tight}$ signal regions of baseline signal point ($m(\tilde{q}, \tilde{\chi}_1^0)=(850, 100)$ GeV) normalized to 20.3 fb$^{-1}$. 5000 events were generated for ths point.

Distributions of $s_{\text{T}}$ in the single-tau one-bin SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.

Distributions of $m_{\text{T}}(\tau)$ in the single-tau one-bin SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.

Distributions of $\Sigma m_{\text{T}}(b_{1,2})$ in the single-tau $p_{\text{T}}(\tau)$-binned SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.

Distributions of $p_{\text{T}}(\tau)$ in the single-tau $p_{\text{T}}(\tau)$-binned SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.

Observed event yields in data ('Observed') and expected event yields for SM background processes obtained from the background-only fit ('Total bkg.' and rows below) in the signal regions of the di-tau and single-tau channels. The quoted uncertainties include both the statistical and systematic uncertainties and are truncated at zero yield. By construction, no $t\bar{t}$ (2 real $\tau$) events can pass the selections in the single-tau channel. As the individual uncertainties are correlated, they do not add in quadrature to equal the total background uncertainty.

From left to right: upper limits at the 95% confidence level (CL) on the visible cross section ($\sigma_\text{vis}$) and on the number of signal events ($S_{\text{obs}}^{95}$). The third column ($S_{\text{exp}}^{95}$) shows the upper limit at the 95% CL on the number of signal events, given the expected number (and $\pm 1\,\sigma$ excursions on the expectation) of background events. The last two columns indicate the confidence level observed for the background-only hypothesis ($\text{CL}_{b}$), the discovery $p$-value ($p(s=0)$) and the significance ($Z$). In the di-tau SR, where fewer events are observed than predicted by the fitted background estimate, the $p$-value is capped at 0.5.

Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for the minimal-coupling scenario. The limits are derived from the binned single-tau signal region.

Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for the minimal-coupling scenario. The limits are derived from the binned single-tau signal region.

Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for vector leptoquarks with additional gauge couplings. The limits are derived from the binned single-tau signal region.

Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for vector leptoquarks with additional gauge couplings. The limits are derived from the binned single-tau signal region.

Exclusion contours at the 95% confidence level for the stop-stau signal model as a function of the masses of the top squark $m(\tilde{t}_{1})$ and of the tau slepton $m(\tilde{\tau}_{1})$. Expected and observed limits are shown for the present search in comparison to observed limits from previous ATLAS analyses based on data from Run-1 of the LHC at $\sqrt{s} = 8$ TeV [Eur. Phys. J. C 76 (2016)] and on a partial dataset from Run 2 at $\sqrt{s} = 13$ TeV [Phys. Rev. D 98 (2018) 032008]. The green band indicates the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments.

Exclusion contours at the 95% confidence level for the stop-stau signal model as a function of the masses of the top squark $m(\tilde{t}_{1})$ and of the tau slepton $m(\tilde{\tau}_{1})$. Expected and observed limits are shown for the present search in comparison to observed limits from previous ATLAS analyses based on data from Run-1 of the LHC at $\sqrt{s} = 8$ TeV [Eur. Phys. J. C 76 (2016)] and on a partial dataset from Run 2 at $\sqrt{s} = 13$ TeV [Phys. Rev. D 98 (2018) 032008]. The green band indicates the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments.

Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{u}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for up-type leptoquarks $\text{LQ}_{3}^{\text{u}})$ with charge $+2/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.

Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{u}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for up-type leptoquarks $\text{LQ}_{3}^{\text{u}})$ with charge $+2/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.

Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{d}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for down-type leptoquarks $\text{LQ}_{3}^{\text{d}})$ with charge $-1/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.

Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{d}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for down-type leptoquarks $\text{LQ}_{3}^{\text{d}})$ with charge $-1/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.

Upper limits on the signal cross section at the 95 % confidence level for the stop-stau signal model.

Upper limits on the signal cross section at the 95 % confidence level for the scalar third-generation leptoquark signal model with up-type leptoquarks.

Upper limits on the signal cross section at the 95 % confidence level for the scalar third-generation leptoquark signal model with down-type leptoquarks.

Upper limits on the signal cross section at the 95 % confidence level for the vector third-generation leptoquark signal model with minimal coupling (MC).

Upper limits on the signal cross section at the 95 % confidence level for the vector third-generation leptoquark signal model with additional gauge couplings (YM).

Acceptance of the one-bin signal region of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the one-bin signal region of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the signal region of the di-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the signal region of the di-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the one-bin signal region of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the one-bin signal region of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the signal region of the di-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the signal region of the di-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.