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.

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.

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.

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% $\tilde t_1\to b\chi^\pm_1$).

Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Despite listing this as an exclusive final state (as there must be at least one b-jets), there is no explicit selection on the presence of additional light-flavour jets. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 300, 500 and 800 GeV and $\tan\beta$ = 10 in the hMSSM scenario are also provided.

Observed and predicted mTtot distribution for the b-inclusive selection in the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. In the paper, the first bin is cut off at 60 GeV for aesthetics but contains underflows down to 50 GeV as in the HepData table. The last bin includes overflows. The prediction for a SSM Zprime with masses of 1500, 2000 and 2500 GeV are also provided.

Observed and predicted mTtot distribution for the b-inclusive selection in the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The prediction for a SSM Zprime with masses of 1500, 2000 and 2500 GeV are also provided.

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

Observed and expected 95% CL upper limits on the Drell Yan production cross section times ditau branching fraction as a function of the Zprime boson mass.

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

Ratio of the 95% CL upper limits on the production cross section times branching fraction for alternate Zprime models with respect to the SSM, both observed and expected are shown.

Acceptance, acceptance times efficiency and b-tag category fraction for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.

Acceptance, acceptance times efficiency and b-tag category fraction for a scalar boson produced by b-associated production as a function of the scalar boson mass.

Acceptance and acceptance times efficiency for a heavy gauge boson produced by Drell Yan as a function of the gauge boson mass.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

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

Fractions of selected events for several signal MC samples with a mass difference $\Delta m = 100$ GeV, illustrating how $\mathcal{A}\times\varepsilon$ varies with the model parameters.

Two-dimensional distribution of $m_{\mathrm{DV}}$ and track multiplicity for DVs in data events and events of a $R$-hadron signal sample with $m_{\tilde{g}} = 1.4$ TeV, $m_{\tilde{\chi}_{1}^{0}} = 100$ GeV and $\tau_{\tilde{g}} = 1$ ns that satisfy all signal region event selection criteria.

Two-dimensional distribution of $m_{\mathrm{DV}}$ and track multiplicity for DVs in data events and events of a $R$-hadron signal sample with $m_{\tilde{g}} = 1.4$ TeV, $m_{\tilde{\chi}_{1}^{0}} = 1.32$ TeV and $\tau_{\tilde{g}} = 1$ ns that satisfy all signal region event selection criteria.

Observed cross section upper 95% CL limits as a function of $m_{\tilde{g}}$ and $\tau$ for $m_{\tilde{\chi}_{1}^{0}}=100$ GeV. For the mass limits see the entry of Figure 8b.

Upper 95% CL limits on the signal cross section for $m_{\tilde{g}}=1.4$ TeV and fixed $m_{\tilde{\chi}_{1}^{0}}=100$ GeV as a function of lifetime $\tau$.

Vertex reconstruction efficiency as a function of radial position $R$ with and without the special LRT processing for one $R$-hadron signal sample with $m_{\tilde{g}} = 1.2$ TeV, $m_{\tilde{\chi}_{1}^{0}} = 100$ GeV and $\tau_{\tilde{g}} = 1$ ns. The efficiency is defined as the probability for a true LLP decay to be matched with a reconstructed DV fulfilling the vertex preselection criteria in events with a reconstructed primary vertex.

Upper 95% CL limits on the signal cross section for $m_{\tilde{g}}=2.0$ TeV and fixed $m_{\tilde{\chi}_{1}^{0}}=100$ GeV as a function of lifetime $\tau$.

Vertex reconstruction efficiency as a function of radial position $R$ for two $R$-hadron signal samples with $m_{\tilde{g}} = 1.2$ TeV, $\tau_{\tilde{g}} = 1$ ns and different neutralino masses. The efficiency is defined as the probability for a true LLP decay to be matched with a reconstructed DV fulfilling the vertex preselection criteria in events with a reconstructed primary vertex.

Lower 95% CL limits on $m_{\tilde{g}}$ for fixed $m_{\tilde{\chi}_{1}^{0}}=100$ GeV as a function of lifetime $\tau$.

Fractions of selected events for several signal MC samples with a gluino lifetime $\tau = 1$ ns, illustrating how $\mathcal{A}\times\varepsilon$ varies with the model parameters.

Upper 95% CL limits on the signal cross section for $m_{\tilde{g}}=1.4$ TeV and fixed $\Delta m=100$ GeV as a function of lifetime $\tau$.

Fractions of selected events for several signal MC samples with a mass difference $\Delta m = 100$ GeV, illustrating how $\mathcal{A}\times\varepsilon$ varies with the model parameters.

Upper 95% CL limits on the signal cross section for $m_{\tilde{g}}=2.0$ TeV and fixed $\Delta m=100$ GeV as a function of lifetime $\tau$.

Two-dimensional distribution of $m_{\mathrm{DV}}$ and track multiplicity for DVs in data events and events of a $R$-hadron signal sample with $m_{\tilde{g}} = 1.4$ TeV, $m_{\tilde{\chi}_{1}^{0}} = 100$ GeV and $\tau_{\tilde{g}} = 1$ ns that satisfy all signal region event selection criteria.

Lower 95% CL limit on $m_{\tilde{g}}$ for fixed $\Delta m=100$ GeV as a function of lifetime $\tau$.

Two-dimensional distribution of $m_{\mathrm{DV}}$ and track multiplicity for DVs in data events and events of a $R$-hadron signal sample with $m_{\tilde{g}} = 1.4$ TeV, $m_{\tilde{\chi}_{1}^{0}} = 1.32$ TeV and $\tau_{\tilde{g}} = 1$ ns that satisfy all signal region event selection criteria.

Upper 95% CL limits on the signal cross section for $m_{\tilde{g}}=1.4$ TeV and fixed $\tau=1$ ns as a function of $m_{\tilde{\chi}_{1}^{0}}$.

Upper 95% CL limits on the signal cross section for $m_{\tilde{g}}=1.4$ TeV and fixed $\Delta m=100$ GeV as a function of lifetime $\tau$.

Upper 95% CL limits on the signal cross section for $m_{\tilde{g}}=2.0$ TeV and fixed $\tau=1$ ns as a function of $m_{\tilde{\chi}_{1}^{0}}$.

Upper 95% CL limits on the signal cross section for $m_{\tilde{g}}=2.0$ TeV and fixed $\Delta m=100$ GeV as a function of lifetime $\tau$.

Observed 95% CL limit as a function of $m_{\tilde{g}}$ and $m_{\tilde{\chi}_{1}^{0}}$ for fixed $\tau=1$ ns.

Lower 95% CL limit on $m_{\tilde{g}}$ for fixed $\Delta m=100$ GeV as a function of lifetime $\tau$.

Two-dimensional distributions of $x$-$y$ positions of vertices observed in the data passing the vertex pre-selection and satisfying all signal region event-level requirements.

Two-dimensional distributions of $x$-$y$ positions of vertices observed in the data passing the vertex pre-selection and satisfying all signal region event-level requirements.

Distribution of the mass $m_{\mathrm{DV}}$ for vertices in data events and in events of five $R$-hadron signal samples with $m_{\tilde{g}} = 1.2$ TeV, $m_{\tilde{\chi}_{1}^{0}} = 100$ GeV and different $\tau_{\tilde{g}}$ that satisfy the signal region event requirements. All DV selections are applied except for the $m_{\mathrm{DV}}$ and track multiplicity requirements.

Distribution of the mass $m_{\mathrm{DV}}$ for vertices in data events and in events of five $R$-hadron signal samples with $m_{\tilde{g}} = 1.2$ TeV, $m_{\tilde{\chi}_{1}^{0}} = 100$ GeV and different $\tau_{\tilde{g}}$ that satisfy the signal region event requirements. All DV selections are applied except for the $m_{\mathrm{DV}}$ and track multiplicity requirements.

Distribution of the track multiplicity $n_{\mathrm{Tracks}}$ for vertices in data events and events of five $R$-hadron signal samples with $m_{\tilde{g}} = 1.2$ TeV, $m_{\tilde{\chi}_{1}^{0}} = 100$ GeV and and different $\tau_{\tilde{g}}$ that satisfy the signal region event requirements. All DV selections are applied except for the $m_{\mathrm{DV}}$ and track multiplicity requirements. The track multiplicity distribution requires vertices to have $m_{\mathrm{DV}}>3$ GeV.

Distribution of the track multiplicity $n_{\mathrm{Tracks}}$ for vertices in data events and events of five $R$-hadron signal samples with $m_{\tilde{g}} = 1.2$ TeV, $m_{\tilde{\chi}_{1}^{0}} = 100$ GeV and and different $\tau_{\tilde{g}}$ that satisfy the signal region event requirements. All DV selections are applied except for the $m_{\mathrm{DV}}$ and track multiplicity requirements. The track multiplicity distribution requires vertices to have $m_{\mathrm{DV}}>3$ GeV.

Observed cross section upper 95% CL limits as a function of $m_{\tilde{g}}$ and $\tau$ for $m_{\tilde{\chi}_{1}^{0}}=100$ GeV. For the mass limits see the entry of Figure 8b.

Observed cross section upper 95% CL limits as a function of $m_{\tilde{g}}$ and $\tau$ for $\Delta m=100$ GeV. For the mass limits see the entry of Figure 9b.

Observed cross section upper 95% CL limits as a function of $m_{\tilde{g}}$ and $\tau$ for $\Delta m=100$ GeV. For the mass limits see the entry of Figure 9b.

Observed cross section upper 95% CL limits as a function of $m_{\tilde{\chi}_{1}^{0}}$ and $m_{\tilde{g}}$ for $\tau = 1$ ns. For the mass limits see the entry of Figure 10b.

Observed cross section upper 95% CL limits as a function of $m_{\tilde{\chi}_{1}^{0}}$ and $m_{\tilde{g}}$ for $\tau = 1$ ns. For the mass limits see the entry of Figure 10b.

Parameterized event selection efficiencies as a function of truth MET for events which have all truth decay vertices occurring before the start of the ATLAS calorimeter. Event-level efficiencies are evaluated for events that have truth MET $> 200$ GeV, pass the trackless jet requirement, and have at least one displaced truth decay within the fiducial volume. To satisfy the event-level efficiency, events must then pass the full event selection.

Parameterized event selection efficiencies as a function of truth MET for events which have all truth decay vertices occurring before the start of the ATLAS calorimeter. Event-level efficiencies are evaluated for events that have truth MET $> 200$ GeV, pass the trackless jet requirement, and have at least one displaced truth decay within the fiducial volume. To satisfy the event-level efficiency, events must then pass the full event selection.

Parameterized event selection efficiencies as a function of truth MET for events which have the furthest truth decay occurring inside the calorimeter. Event-level efficiencies are evaluated for events that have truth MET $> 200$ GeV, pass the trackless jet requirement, and have at least one displaced truth decay within the fiducial volume. To satisfy the event-level efficiency, events must then pass the full event selection.

Parameterized event selection efficiencies as a function of truth MET for events which have the furthest truth decay occurring inside the calorimeter. Event-level efficiencies are evaluated for events that have truth MET $> 200$ GeV, pass the trackless jet requirement, and have at least one displaced truth decay within the fiducial volume. To satisfy the event-level efficiency, events must then pass the full event selection.

Parameterized event selection efficiencies as a function of truth MET for events which have the furthest truth decay occurring after the end of the ATLAS calorimeter. Event-level efficiencies are evaluated for events that have truth MET $> 200$ GeV, pass the trackless jet requirement, and have at least one displaced truth decay within the fiducial volume. To satisfy the event-level efficiency, events must then pass the full event selection.

Parameterized event selection efficiencies as a function of truth MET for events which have the furthest truth decay occurring after the end of the ATLAS calorimeter. Event-level efficiencies are evaluated for events that have truth MET $> 200$ GeV, pass the trackless jet requirement, and have at least one displaced truth decay within the fiducial volume. To satisfy the event-level efficiency, events must then pass the full event selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $4$ mm $< R_{\mathrm{decay}} < 22$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $4$ mm $< R_{\mathrm{decay}} < 22$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $22$ mm $< R_{\mathrm{decay}} < 25$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $22$ mm $< R_{\mathrm{decay}} < 25$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $25$ mm $< R_{\mathrm{decay}} < 29$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $25$ mm $< R_{\mathrm{decay}} < 29$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Upper 95% CL limits on the signal cross section for $m_{\tilde{g}}=1.4$ TeV and fixed $m_{\tilde{\chi}_{1}^{0}}=100$ GeV as a function of lifetime $\tau$.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $29$ mm $< R_{\mathrm{decay}} < 38$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $29$ mm $< R_{\mathrm{decay}} < 38$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Upper 95% CL limits on the signal cross section for $m_{\tilde{g}}=2.0$ TeV and fixed $m_{\tilde{\chi}_{1}^{0}}=100$ GeV as a function of lifetime $\tau$.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $38$ mm $< R_{\mathrm{decay}} < 46$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $38$ mm $< R_{\mathrm{decay}} < 46$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Lower 95% CL limits on $m_{\tilde{g}}$ for fixed $m_{\tilde{\chi}_{1}^{0}}=100$ GeV as a function of lifetime $\tau$.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $46$ mm $< R_{\mathrm{decay}} < 73$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $46$ mm $< R_{\mathrm{decay}} < 73$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $73$ mm $< R_{\mathrm{decay}} < 84$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $73$ mm $< R_{\mathrm{decay}} < 84$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $84$ mm $< R_{\mathrm{decay}} < 111$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $84$ mm $< R_{\mathrm{decay}} < 111$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $111$ mm $< R_{\mathrm{decay}} < 120$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $111$ mm $< R_{\mathrm{decay}} < 120$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Upper 95% CL limits on the signal cross section for $m_{\tilde{g}}=1.4$ TeV and fixed $\tau=1$ ns as a function of $m_{\tilde{\chi}_{1}^{0}}$.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $120$ mm $< R_{\mathrm{decay}} < 145$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $120$ mm $< R_{\mathrm{decay}} < 145$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Upper 95% CL limits on the signal cross section for $m_{\tilde{g}}=2.0$ TeV and fixed $\tau=1$ ns as a function of $m_{\tilde{\chi}_{1}^{0}}$.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $145$ mm $< R_{\mathrm{decay}} < 180$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $145$ mm $< R_{\mathrm{decay}} < 180$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Observed 95% CL limit as a function of $m_{\tilde{g}}$ and $m_{\tilde{\chi}_{1}^{0}}$ for fixed $\tau=1$ ns.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $180$ mm $< R_{\mathrm{decay}} < 300$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Parameterized vertex level efficiencies as a function of number of particles associated to a truth decay vertex, and the vertex invariant mass for truth decays with $180$ mm $< R_{\mathrm{decay}} < 300$ mm. Selected particles are required to have nonzero electric charge, $p_{T}(|Q|=1) > 1$ GeV, and $d_0 > 2$ mm. The per-vertex efficiency is evaluated only for truth vertices that have at least 5 associated tracks, an invariant mass $> 10$ GeV, and are in the region $4$ mm $< R_{\mathrm{decay}} < 300$ mm, and $|Z_{\mathrm{decay}}| < 300$ mm. A truth vertex satisfies the vertex level efficiency if it can be matched to a reconstructed DV which passes the final vertex selection.

Dijet mass spectra after the background only fit with the background prediction in the high-mass region with two b-tags.

Dijet mass spectra after the background only fit with the background prediction in the low-mass region with two b-tags.

The online b-tagging efficiency with respect to the offline b-tagging efficiency as a function of pT. The b-tagging online and offline working points correspond to an efficiency of 60% and 70%, respectively.

Observed and expected 95% credibility-level upper limits on the cross-section for the b* model in the high-mass region with inclusive b-jet selection.

Observed and expected 95% credibility-level upper limits on the cross-section times branching ratio for the SSM and leptophobic Z' models in the low- and high-mass region with two b-tags selection.

Observed and expected 95% credibility-level upper limits on the cross-section for DM Z' models in the low-mass region with two b-tags selection. The Z' is expected to decay to all five quark flavors other than the top quark and the mediator to SM quark coupling (gSM) equal to 0.1 is assumed.

Observed and expected 95% credibility-level upper limits on the cross-section times branching ratio for DM Z'->bb models in the high-mass region with two b-tags selection. The Z' is expected to decay to bb only and the mediator to SM quark coupling (gSM) equal to 0.25 is assumed.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances with intrinsic width smaller than the detector resolution. The width of the Gaussian reconstructed shape is dominated by the dijet mass resolution. The table shows the limits obtained from the high-mass inclusive one b-tag selection.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances with intrinsic width smaller than the detector resolution. The width of the Gaussian reconstructed shape is dominated by the dijet mass resolution. The table shows the limits obtained from the combined low- and high-mass two b-tags selection.

The mass distributions for the inclusive one b-tagged selection and two b-tagged selection using an integrated luminosity of 36.1 $fb^{-1}$. The inclusive one b-tagged Pythia8 MC distribution is normalized to the inclusive one b-tagged data. The two b-tagged Pythia8 MC distribution is normalized to the two b-tagged data. The systematic uncertainty band is dominated by the b-tagging scale factor and the b-jet energy scale.

Signal acceptance times efficiency for inclusive 1 b-tag and 2 b-tag categories as a function of the simulated b* and the Z' masses.

Signal acceptance times efficiency for 2 b-tag categories as a function of the simulated Z' masses.

The flavor composition of the simulated dijet background as a function of dijet mass before tagging. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

The flavor composition of the simulated dijet background as a function of dijet mass with inclusive one b-tag. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

The flavor composition of the simulated dijet background as a function of dijet mass with two b-tags. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 3%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 7%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 10%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 15%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 3%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 7%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 10%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 15%.

Measured differential cross section with associated uncertainties as a function of absolute rapidity of diphoton system. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of multiplicity of jets with transverse momentum pT(jet) > 30 GeV. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of multiplicity of jets with transverse momentum pT(jet) > 30 GeV. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of multiplicity of jets with transverse momentum pT(jet) > 30 GeV. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of multiplicity of jets with transverse momentum pT(jet) > 30 GeV. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of transverse momentum of the leading jet. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of transverse momentum of the leading jet. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of absolute rapidity of the leading jet. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of absolute rapidity of the leading jet. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of scalar transverse momentum sum of all jets. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of scalar transverse momentum sum of all jets. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of transverse momentum of second leading jet. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of transverse momentum of second leading jet. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of rapidity separation of leading two jets. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of rapidity separation of leading two jets. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of azimuthal angle between diphoton and dijet systems. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of azimuthal angle between diphoton and dijet systems. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of cosine of the decay angle in the Collins-Soper frame. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of cosine of the decay angle in the Collins-Soper frame. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of cosine of the decay angle in the Collins-Soper frame. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of cosine of the decay angle in the Collins-Soper frame. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of azimuthal angle between the two leading jets. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of azimuthal angle between the two leading jets. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of diphoton thrust pT. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of diphoton thrust pT. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of rapidity separation of the two photons. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of rapidity separation of the two photons. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of tau of highest-tau jet (see paper for description). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of tau of highest-tau jet (see paper for description). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of scalar sum of tau for all jets (see paper for description). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of scalar sum of tau for all jets (see paper for description). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of absolute rapidity of second leading jet. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of absolute rapidity of second leading jet. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of transverse momentum of third leading jet. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of transverse momentum of third leading jet. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of dijet invariant mass. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of dijet invariant mass. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of transverse momentum of the combined diphoton and dijet system. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of transverse momentum of the combined diphoton and dijet system. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of cosine of the decay angle in the Collins-Soper frame in bins of diphoton transverse momentum. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of cosine of the decay angle in the Collins-Soper frame in bins of diphoton transverse momentum. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of diphoton transverse momentum in jet multiplicity bins. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of diphoton transverse momentum in jet multiplicity bins. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of leading jet transverse momentum for exclusive one-jet events. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of leading jet transverse momentum for exclusive one-jet events. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Diphoton kinematic acceptances in percent for gluon fusion for each fiducial region/variable bin studied in this paper, defined as the probability to fulfil the diphoton kinematic criteria: pT(2gam) < 0.35 (0.25) for the leading (subleading) photon and |eta(gam)|<2.37. The factors are evaluated using the POWHEG event generator with MPI modelling and hadronisation turned off. Consistent results for the diphoton variables are obtained by HRes 2.2. Uncertainties are taken from PDF variations. QCD scale varaitions have a negligible impact on these factors.

Diphoton kinematic acceptances in percent for gluon fusion for each fiducial region/variable bin studied in this paper, defined as the probability to fulfil the diphoton kinematic criteria: pT(2gam) < 0.35 (0.25) for the leading (subleading) photon and |eta(gam)|<2.37. The factors are evaluated using the POWHEG event generator with MPI modelling and hadronisation turned off. Consistent results for the diphoton variables are obtained by HRes 2.2. Uncertainties are taken from PDF variations. QCD scale varaitions have a negligible impact on these factors.

Isolation efficiencies in percent for gluon fusion H -> 2gam for each fiducial region/variable bin measured in this analysis. The isolation efficiency is defined as the probability for both photons to fulfil the isolation criteria (ETiso < 14 GeV as described in the text) for events that pass the diphoton kinematic criteria. Uncertainties are assigned in the same way as for the non-perturbative correction factors: by varying the fragmentation and underlying event modelling. These factors can be multiplied by the kinematic acceptance factors (see table~ ef{tab:fid_acceptance}) to extrapolate an inclusive gluon fusion Higgs prediction to the fiducial volume used in this analysis.

Isolation efficiencies in percent for gluon fusion H -> 2gam for each fiducial region/variable bin measured in this analysis. The isolation efficiency is defined as the probability for both photons to fulfil the isolation criteria (ETiso < 14 GeV as described in the text) for events that pass the diphoton kinematic criteria. Uncertainties are assigned in the same way as for the non-perturbative correction factors: by varying the fragmentation and underlying event modelling. These factors can be multiplied by the kinematic acceptance factors (see table~ ef{tab:fid_acceptance}) to extrapolate an inclusive gluon fusion Higgs prediction to the fiducial volume used in this analysis.

Non-perturbative correction factors in percent accounting for the impact of hadronisation and the underlying event activity for all measured variables and fiducial regions. Uncertainties are evaluated by deriving these factors using different generators and tunes as described in the text.

Non-perturbative correction factors in percent accounting for the impact of hadronisation and the underlying event activity for all measured variables and fiducial regions. Uncertainties are evaluated by deriving these factors using different generators and tunes as described in the text.

Fiducial cross sections in fb from WH, ZH and ttH combined, in each variable bin and fiducial region.

Fiducial cross sections in fb from WH, ZH and ttH combined, in each variable bin and fiducial region.

Statistical bin-to-bin correlations between the 24 bins used in the analysis described in Phys.Lett. B753 (2016) 69-85 (arXiv:1508.02507). See Figure 3 of this paper for the bins used.

Measured differential cross section with associated uncertainties as a function of COS(THETA*). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of DELTAYRAP(2GAMMA). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of MULT(JET,PT>30 GEV). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of MULT(JET,PT>50 GEV). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(JET1). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(JET2). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of HT. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of YRAP(JET1). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of YRAP(JET2). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of M(2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of DELTAYRAP(2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of ABSDPHI(2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of DPHI(2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of DPHI(2GAMMA,2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of TAUJET. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of SUM(TAUJET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA) [NJET=0,PT>30 GEV]. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA) [NJET=1,PT>30 GEV]. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA) [NJET=2,PT>30 GEV]. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA) [NJET>=3,PT>30 GEV]. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

The measured cross sections or cross section limits of the diphoton, VBF-enhanced, Nlepton $\geq$ 1, high $E_{T}^{miss}$, and ttH-enhanced fiducial regions are shown.

Measured differential cross section with associated uncertainties as a function of diphoton transverse momentum in bins of ABS(COS(THETA*)). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.Each systematic uncertainty sources is fully uncorrelated with the other sources.

Non-perturbative correction factors in percent accounting for the impact of hadronisation and the underlying event activity for all measured variables and fiducial regions. Regions of phase space where no reliable estimate could be obtained are listed as 100 without uncertainties. Uncertainties are evaluated by deriving these factors using different generators and tunes as described in the text. No factor are given for the Nlepton $\geq$ 1 and High-$E_{T}^{miss}$ fiducial regions as the gluon fusion contamination in both is negligible.

Isolation efficiencies in percent for gluon fusion $H\rightarrow\gamma\gamma$ for each fiducial region/variable bin measured in this analysis. The isolation efficiency is defined as the probability for both photons to fulfil the isolation criteria (as described in Section 9.1) for events that pass the diphoton kinematic criteria. Regions of phase space where no reliable estimate could be obtained are listed as 100 without uncertainties. Uncertainties are assigned in the same way as for the non-perturbative correction factors: by varying the fragmentation and underlying event modelling. These factors can be multiplied by the kinematic acceptance factors (see Table 29) to extrapolate an inclusive gluon fusion Higgs prediction to the fiducial volume used in this analysis. No factors for the Nlepton $\geq$ 1 and High $E_{T}^{miss}$ fiducial regions are provided as the gluon fusion contamination is negligible.

Combined non-perturbative (Table 27) and particle-level isolation correction factors (Table 28) in percent accounting for the impact of hadronisation and the underlying event activity for all measured variables and fiducial regions. Regions of phase space where no reliable estimate could be obtained are listed as 100 without uncertainties. The uncertainties on the combined values properly take into account the correlations between both multiplicative factors.

Diphoton kinematic acceptances in percent for gluon-gluon fusion for the diphoton fiducial region and all differential variable bins studied in this paper, defined as the probability to fulfill the diphoton kinematic criteria: $p_{T}$/$m_{\gamma\gamma}$ < 0.35 (0.25) for the leading (subleading) photon and $|\eta_{\gamma\gamma}|$ < 2.37. The factors are evaluated using the Powheg NNLOPSevent generator. Uncertainties are taken from PDF variations. QCD scale variations have a negligible impact on these factors. The range of each bin is given in Table 26.

observed statistical correlations between pTyy, Njets, mjj, |DeltaPhijj| and pTj1

ggH default MC + XH predictions

XH ( = VBF + VH + ttH + bbH ) MC predictions

Best-fit values and uncertainties of the production-mode cross sections times branching ratio.

Best-fit values and uncertainties of the simplified template cross sections times branching ratio.

Observed correlations between the measured simplified template cross sections, including both the statistical and systematic uncertainties.

Best-fit values and uncertainties of the simplified template cross sections times branching ratio.

Observed correlations between the measured simplified template cross sections, including both the statistical and systematic uncertainties.

Observed correlations between the measured simplified template cross sections, including both the statistical and systematic uncertainties.