A2 for the yZ-integrated measurement (unregularised).

A3 for the yZ-integrated measurement (unregularised).

A4 for the yZ-integrated measurement (unregularised).

A5 for the yZ-integrated measurement (unregularised).

A6 for the yZ-integrated measurement (unregularised).

A7 for the yZ-integrated measurement (unregularised).

Covariance matrix of all measurements and uncertainties (unregularised).

A0-A2 for the yZ-integrated measurement (regularised).

A0 for the yZ-integrated measurement (regularised).

A1 for the yZ-integrated measurement (regularised).

A2 for the yZ-integrated measurement (regularised).

A3 for the yZ-integrated measurement (regularised).

A4 for the yZ-integrated measurement (regularised).

A5 for the yZ-integrated measurement (regularised).

A6 for the yZ-integrated measurement (regularised).

A7 for the yZ-integrated measurement (regularised).

Covariance matrix of all measurements and uncertainties (regularised).

A0-A2 for the 0<|yZ|<1 measurement (unregularised).

A0 for the 0<|yZ|<1 measurement (unregularised).

A1 for the 0<|yZ|<1 measurement (unregularised).

A2 for the 0<|yZ|<1 measurement (unregularised).

A3 for the 0<|yZ|<1 measurement (unregularised).

A4 for the 0<|yZ|<1 measurement (unregularised).

A5 for the 0<|yZ|<1 measurement (unregularised).

A6 for the 0<|yZ|<1 measurement (unregularised).

A7 for the 0<|yZ|<1 measurement (unregularised).

Covariance matrix of all measurements and uncertainties (unregularised).

A0-A2 for the 0<|yZ|<1 measurement (regularised).

A0 for the 0<|yZ|<1 measurement (regularised).

A1 for the 0<|yZ|<1 measurement (regularised).

A2 for the 0<|yZ|<1 measurement (regularised).

A3 for the 0<|yZ|<1 measurement (regularised).

A4 for the 0<|yZ|<1 measurement (regularised).

A5 for the 0<|yZ|<1 measurement (regularised).

A6 for the 0<|yZ|<1 measurement (regularised).

A7 for the 0<|yZ|<1 measurement (regularised).

Covariance matrix of all measurements and uncertainties (regularised).

A0-A2 for the 1<|yZ|<2 measurement (unregularised).

A0 for the 1<|yZ|<2 measurement (unregularised).

A1 for the 1<|yZ|<2 measurement (unregularised).

A2 for the 1<|yZ|<2 measurement (unregularised).

A3 for the 1<|yZ|<2 measurement (unregularised).

A4 for the 1<|yZ|<2 measurement (unregularised).

A5 for the 1<|yZ|<2 measurement (unregularised).

A6 for the 1<|yZ|<2 measurement (unregularised).

A7 for the 1<|yZ|<2 measurement (unregularised).

Covariance matrix of all measurements and uncertainties (unregularised).

A0-A2 for the 1<|yZ|<2 measurement (regularised).

A0 for the 1<|yZ|<2 measurement (regularised).

A1 for the 1<|yZ|<2 measurement (regularised).

A2 for the 1<|yZ|<2 measurement (regularised).

A3 for the 1<|yZ|<2 measurement (regularised).

A4 for the 1<|yZ|<2 measurement (regularised).

A5 for the 1<|yZ|<2 measurement (regularised).

A6 for the 1<|yZ|<2 measurement (regularised).

A7 for the 1<|yZ|<2 measurement (regularised).

Covariance matrix of all measurements and uncertainties (regularised).

A2 for the 2<|yZ|<3.5 measurement (unregularised).

A3 for the 2<|yZ|<3.5 measurement (unregularised).

A5 for the 2<|yZ|<3.5 measurement (unregularised).

A7 for the 2<|yZ|<3.5 measurement (unregularised).

Covariance matrix of all measurements and uncertainties (unregularised).

A2 for the 2<|yZ|<3.5 measurement (regularised).

A3 for the 2<|yZ|<3.5 measurement (regularised).

A5 for the 2<|yZ|<3.5 measurement (regularised).

A7 for the 2<|yZ|<3.5 measurement (regularised).

Covariance matrix of all measurements and uncertainties (regularised).

A0 for the 2<|yZ|<3.5 measurement (unregularised).

A4 for the 2<|yZ|<3.5 measurement (unregularised).

Covariance matrix of all measurements and uncertainties (unregularised).

A0 for the 2<|yZ|<3.5 measurement (regularised).

A4 for the 2<|yZ|<3.5 measurement (regularised).

Covariance matrix of all measurements and uncertainties (regularised).

Expected 95% CL exclusion contour for the Gbb signal.

Observed 95% CL exclusion contour for the Gbb signal.

Expected 95% CL exclusion contour for the Gtt combination.

Observed 95% CL exclusion contour for the Gtt combination.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

$R_{pPb}$ as a function of $p_{T}$ integrated over rapidity range $-1.8<y*<1.3$ for the 0--90% centrality interval for the three geometric models: (a) Glauber, (b) Glauber-Gribov with $\omega_{\sigma}=0.11$ and (c) Glauber-Gribov with $\omega_{\sigma}=0.2$.

$R_{pPb}$ values as a function of $p_{T}$ in the 0--90% centrality interval averaged over $|y*|<0.5$.The $\langle T_{Pb} \rangle$ value for the ATLAS centrality correction is calculated with the Glauber model. The total systematic uncertainties, which include the uncertainty in $\langle T_{Pb} \rangle$, are indicated by lines of the same colour. Strict quantitative agreement is not expected as each measurement uses different rapidity intervals for the centrality determination and apply different event selection criteria to reject diffractive collisions.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields integrated over $-1.8<y*<1.3$ for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields integrated over $-1.8<y*<1.3$ for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields integrated over $-1.8<y*<1.3$ for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{CP}$ as a function of $p_{T}$ extracted from the invariant yields integrated over $|\eta|<2.3$ for seven centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{CP}$ as a function of $p_{T}$ extracted from the invariant yields integrated over $|\eta|<2.3$ for seven centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{CP}$ as a function of $p_{T}$ extracted from the invariant yields integrated over $|\eta|<2.3$ for seven centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

NLO cross sections and selection efficiencies (assuming $\beta$ = 1) for different signal points.

The distribution of the missing transverse momentum is shown in soft-lepton 2-jet W+jets control regions after normalising the ttbar and W+jets background processes in the simultaneous fit.

Expected background yields as obtained in the background-only fits in all hard-lepton and soft-lepton validation together with observed data are given. Uncertainties in the fitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties.

Expected background yields as obtained in the background-only fits in all hard-lepton and soft-lepton signal together with observed data are given. Uncertainties in the fitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties.

Distributions of mt for the hard-lepton 4-jet low-x signal region. The requirement on the variable plotted is removed from the definitions of the signal regions, where the arrow indicates the position of the cut in the signal region. The lower panels of the plots show the ratio of the observed data to the total background prediction as derived in the background-only fit. The uncertainty bands plotted include all statistical and systematic uncertainties as discussed in Section 7. The component `Others' is the sum of Z+jets and ttbar+V. The last bin includes the overflow.

Distributions of met/meff for the 4-jet high-x signal region. The requirement on the variable plotted is removed from the definitions of the signal regions, where the arrow indicates the position of the cut in the signal region. The lower panels of the plots show the ratio of the observed data to the total background prediction as derived in the background-only fit. The uncertainty bands plotted include all statistical and systematic uncertainties as discussed in Section 7. The component `Others' is the sum of Z+jets and ttbar+V. The last bin includes the overflow.

Distributions of mt for the hard-lepton 5-jet signal region. The requirement on the variable plotted is removed from the definitions of the signal regions, where the arrow indicates the position of the cut in the signal region. The lower panels of the plots show the ratio of the observed data to the total background prediction as derived in the background-only fit. The uncertainty bands plotted include all statistical and systematic uncertainties as discussed in Section 7. The component `Others' is the sum of Z+jets and ttbar+V. The last bin includes the overflow.

Distributions of mt for the hard-lepton 6-jet signal region. The requirement on the variable plotted is removed from the definitions of the signal regions, where the arrow indicates the position of the cut in the signal region. The lower panels of the plots show the ratio of the observed data to the total background prediction as derived in the background-only fit. The uncertainty bands plotted include all statistical and systematic uncertainties as discussed in Section 7. The component `Others' is the sum of Z+jets and ttbar+V. The last bin includes the overflow.

Distributions of met for the soft-lepton 2-jet signal region. The requirement on the variable plotted is removed from the definitions of the signal regions, where the arrow indicates the position of the cut in the signal region. The lower panels of the plots show the ratio of the observed data to the total background prediction as derived in the background-only fit. The uncertainty bands plotted include all statistical and systematic uncertainties as discussed in Section 7. The component `Others' is the sum of Z+jets and ttbar+V. The last bin includes the overflow.

Distributions of met for the soft-lepton 5-jet signal region. The requirement on the variable plotted is removed from the definitions of the signal regions, where the arrow indicates the position of the cut in the signal region. The lower panels of the plots show the ratio of the observed data to the total background prediction as derived in the background-only fit. The uncertainty bands plotted include all statistical and systematic uncertainties as discussed in Section 7. The component `Others' is the sum of Z+jets and ttbar+V. The last bin includes the overflow.

The observed combined 95% CL exclusion limits in the the gluino simplified models using for each model point the signal region with the best expected sensitivity. The limits are presented in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ models.

The expected combined 95% CL exclusion limits in the the gluino simplified models using for each model point the signal region with the best expected sensitivity. The limits are presented in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ models.

The yellow band ($+ 1 \sigma$) of the combined 95% CL exclusion limits in the the gluino simplified models using for each model point the signal region with the best expected sensitivity. The limits are presented in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ models. The yellow band represents the $\pm 1 \sigma$ variation of the median expected limit due to the experimental and theoretical uncertainties.

The yellow band ($- 1 \sigma$) of the combined 95% CL exclusion limits in the the gluino simplified models using for each model point the signal region with the best expected sensitivity. The limits are presented in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ models. The yellow band represents the $\pm 1 \sigma$ variation of the median expected limit due to the experimental and theoretical uncertainties.

The observed combined 95% CL exclusion limits in the the gluino simplified models using for each model point the signal region with the best expected sensitivity. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

The expected combined 95% CL exclusion limits in the the gluino simplified models using for each model point the signal region with the best expected sensitivity. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

The yellow band ($+ 1 \sigma$) of the combined 95% CL exclusion limits in the the gluino simplified models using for each model point the signal region with the best expected sensitivity. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$. The yellow band represents the $\pm 1 \sigma$ variation of the median expected limit due to the experimental and theoretical uncertainties.

The yellow band ($- 1 \sigma$) of the combined 95% CL exclusion limits in the the gluino simplified models using for each model point the signal region with the best expected sensitivity. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$. The yellow band represents the $\pm 1 \sigma$ variation of the median expected limit due to the experimental and theoretical uncertainties.

The observed limits for the soft-lepton 2-jet signal region. The limits are presented in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ models.

The expected limits for the soft-lepton 2-jet signal region. The limits are presented in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ models.

The observed limits for the hard-lepton 4-jet low-x signal region. The limits are presented in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ models.

The expected limits for the hard-lepton 4-jet low-x signal region. The limits are presented in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ models.

The observed limits for the hard-lepton 5-jet signal region. The limits are presented in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ models.

The expected limits for the hard-lepton 5-jet signal region. The limits are presented in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ models.

The observed limits for the hard-lepton 6-jet signal region. The limits are presented in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ models.

The expected limits for the hard-lepton 6-jet signal region. The limits are presented in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ models.

The observed limits for the soft-lepton 5-jet signal region. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

The expected limits for the soft-lepton 5-jet signal region. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

The observed limits for the hard-lepton 4-jet low-x signal region. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

The expected limits for the hard-lepton 4-jet low-x signal region. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

The observed limits for the hard-lepton 4-jet high-x signal region. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

The expected limits for the hard-lepton 4-jet high-x signal region. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

The observed limits for the hard-lepton 5-jet signal region. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

The expected limits for the hard-lepton 5-jet signal region. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

The observed limits for the hard-lepton 6-jet signal region. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

The expected limits for the hard-lepton 6-jet signal region. The limits are presented in the (gluino, x) plane for the chargino = 60 GeV models where $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

Number of generated events in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$.

Number of generated events in the (gluino, x) plane for the chargino = 60 GeV models.

Production cross-section in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$.

Production cross-section in the (gluino, x) plane for the chargino = 60 GeV models.

Acceptance times efficiency obtained in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (hard-lepton 4-jet low-x).

Acceptance times efficiency in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (hard-lepton 4-jet high-x).

Acceptance times efficiency in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (hard-lepton 5-jet).

Acceptance times efficiency in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (hard-lepton 6-jet).

Acceptance times efficiency in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (soft-lepton 2-jet).

Acceptance times efficiency obtained in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (hard-lepton 4-jet low-x).

Acceptance times efficiency in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (hard-lepton 4-jet high-x).

Acceptance times efficiency in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (hard-lepton 5-jet).

Acceptance times efficiency in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (hard-lepton 6-jet).

Acceptance times efficiency in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (soft-lepton 5-jet).

The observed CLs values as obtained in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (hard-lepton 4-jet low-x).

The observed CLs values as obtained in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (hard-lepton 4-jet high-x).

The observed CLs values as obtained in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (hard-lepton 5-jet).

The observed CLs values as obtained in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (hard-lepton 6-jet).

The observed CLs values as obtained in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (soft-lepton 2-jet).

The expected CLs values as obtained in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (hard-lepton 4-jet low-x).

The expected CLs values as obtained in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (hard-lepton 4-jet high-x).

The expected CLs values as obtained in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (hard-lepton 5-jet).

The expected CLs values as obtained in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (hard-lepton 6-jet).

The expected CLs values as obtained in the different signal regions in the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$ (soft-lepton 2-jet).

The observed CLs values as obtained in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (hard-lepton 4-jet low-x).

The observed CLs values as obtained in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (hard-lepton 4-jet high-x).

The observed CLs values as obtained in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (hard-lepton 5-jet).

The observed CLs values as obtained in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (hard-lepton 6-jet).

The observed CLs values as obtained in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (soft-lepton 5-jet).

The expected CLs values as obtained in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (hard-lepton 4-jet low-x).

The expected CLs values as obtained in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (hard-lepton 4-jet high-x).

The expected CLs values as obtained in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (hard-lepton 5-jet).

The expected CLs values as obtained in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (hard-lepton 6-jet).

The expected CLs values as obtained in the different signal regions in the (gluino, x) plane for the chargino = 60 GeV models (soft-lepton 5-jet).

The signal region yielding in the best expected limit is indicated for every signal point used in the the gluino simplified models for the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$.

The signal region yielding in the best expected limit is indicated for every signal point used in the the gluino simplified models for the (gluino, x) mass plane where for the chargino = 60 GeV and $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

Model-dependent 95% CL upper limits on the visible cross-section in addition to the observed and expected exclusion limits for the (gluino, chargino) mass plane for the scenario where the mass of the chargino is fixed to $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1)) = 1/2$.

Model-dependent 95% CL upper limits on the visible cross-section in addition to the observed and expected exclusion limits for the (gluino, x) mass plane where for the chargino = 60 GeV and $x=(m(\tilde\chi^\pm_1)-m(\tilde\chi^0_1))/(m(\tilde g) - m(\tilde\chi^0_1))$.

Simulated background event samples: the corresponding generator, parton shower, cross-section normalisation, PDF set and underlying-event tune are shown.

Overview of the selection criteria for the soft-lepton signal regions. The symbol $p_{T}^{l}$ refers to signal leptons.

Overview of the selection criteria for the hard-lepton signal regions. The symbol $p_{T}^{l}$ refers to signal leptons.

Background fit results for the hard-lepton and soft-lepton signal regions, for an integrated luminosity of 3.2 fb-1. Uncertainties in the fitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties. The uncertainties in this table are symmetrised for propagation purposes but truncated at zero to remain within the physical boundaries.

Breakdown of upper limits. The columns show from left to right: the name of the respective signal region; the 95% confidence level (CL) upper limits on the visible cross-section and on the number of signal events the 95% CL upper limit on the number of signal events, given the expected number (and $\pm 1 \sigma$ variations on the expectation) of background events; the two-sided CLb value, i.e. the confidence level observed for the background-only hypothesis and the one-sided discovery p-value (p(s = 0)). The discovery p-values are capped to 0.5 in the case of observing less events than the fitted background estimates.

Table shows the data, fitted background and expected signal event counts for a benchmark signal point in each bin of the mt distribution shown in figure 5 (top left). The fit results are shown for an integrated luminosity of 3.2 fb-1.

Table shows the data, fitted background and expected signal event counts for a benchmark signal point in each bin of the met/meff distribution shown in figure 5 (top right). The fit results are shown for an integrated luminosity of 3.2 fb-1.

Table shows the data, fitted background and expected signal event counts for a benchmark signal point in each bin of the mt distribution shown in figure 5 (middle left). The fit results are shown for an integrated luminosity of 3.2 fb-1.

Table shows the data, fitted background and expected signal event counts for a benchmark signal point in each bin of the mt distribution shown in figure 5 (middle right). The fit results are shown for an integrated luminosity of 3.2 fb-1.

Table shows the data, fitted background and expected signal event counts for a benchmark signal point in each bin of the met distribution shown in figure 5 (bottom left). The fit results are shown for an integrated luminosity of 3.2 fb-1.

Table shows the data, fitted background and expected signal event counts for a benchmark signal point in each bin of the met distribution shown in figure 5 (bottom right). The fit results are shown for an integrated luminosity of 3.2 fb-1.

Cutflow table for the hard-lepton signal regions with representative target signal models. The weighted numbers are normalized to 3.2 fb-1 and rounded to the statistical error.

Cutflow table for the hard-lepton signal regions with representative target signal models. The weighted numbers are normalized to 3.2 fb-1 and rounded to the statistical error.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Signal acceptance for SR2jl in squark direct decay model grid.

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

Signal acceptance for SR2jm in squark direct decay model grid.

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

Signal acceptance for SR2jt in squark direct decay model grid.

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

Signal acceptance for SR4jt in squark direct decay model grid.

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

Signal acceptance for SR5j in squark direct decay model grid.

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

Signal acceptance for SR6jm in squark direct decay model grid.

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

Signal acceptance for SR6jt in squark direct decay model grid.

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

Signal acceptance for SR2jl in gluino direct decay model grid.

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

Signal acceptance for SR2jm in gluino direct decay model grid.

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

Signal acceptance for SR2jt in gluino direct decay model grid.

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

Signal acceptance for SR4jt in gluino direct decay model grid.

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

Signal acceptance for SR5j in gluino direct decay model grid.

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

Signal acceptance for SR6jm in gluino direct decay model grid.

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

Signal acceptance for SR6jt in gluino direct decay model grid.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The inclusive prompt photon cross section with systematic and statistical uncertainties for the region 1.81<|eta(gamma)| < 2.37.

The measured cross-sections for $Wj$ production in four bins of $\eta^{\mu}$. The uncertainties shown are statistical, systematic and due to the luminosity determination.

The measured cross-sections for $Wj$ production in four bins of $\eta^{\rm jet}$. The uncertainties shown are statistical, systematic and due to the luminosity determination.

The measured cross-sections for $Wj$ production in five bins of $p^{\rm jet}_T$. The uncertainties shown are statistical, systematic and due to the luminosity determination.

The measured cross-sections for $Z^0 j$ production in four bins of $y^Z$. The uncertainties shown are statistical, systematic and due to the luminosity determination.

The measured cross-sections for $Z^0 j$ production in four bins of $\eta^{\rm jet}$. The uncertainties shown are statistical, systematic and due to the luminosity determination.

The measured cross-sections for $Z^0 j$ production in bins of $p^{\rm jet}_T$. The uncertainties shown are statistical, systematic and due to the luminosity determination.

The measured cross-sections for $Z^0 j$ production in bins of $|\Delta\phi|$. The uncertainties shown are statistical, systematic and due to the luminosity determination.

The correlation matrix for the systematic uncertainties on the $W^+j$ production cross-section measurements presented in Table 1 in bins of $\eta^{\mu}$, where the rows and columns correspond to the individual bins.

The correlation matrix for the systematic uncertainties on the $W^-j$ production cross-section measurements presented in Table 1 in bins of $\eta^{\mu}$, where the rows and columns correspond to the individual bins.

The correlation matrix for the systematic uncertainties on the $W^+j$ production cross-section measurements presented in Table 5 in bins of $\eta^{\rm jet}$, where the rows and columns correspond to the individual bins.

The correlation matrix for the systematic uncertainties on the $W^-j$ production cross-section measurements presented in Table 5 in bins of $\eta^{\rm jet}$, where the rows and columns correspond to the individual bins.

The correlation matrix for the systematic uncertainties on the $W^+j$ production cross-section measurements presented in Table 3 in bins of $p_T^{\rm jet}$, where the rows and columns correspond to the individual bins.

The correlation matrix for the systematic uncertainties on the $W^-j$ production cross-section measurements presented in Table 3 in bins of $p_T^{\rm jet}$, where the rows and columns correspond to the individual bins.

The correlation matrix for the systematic uncertainties on the $Z^0 j$ production cross-section measurements presented in Table 4 as a function of $y^Z$, where the rows and columns correspond to the individual bins.

The correlation matrix for the systematic uncertainties on the $Z^0 j$ production cross-section measurements presented in Table 5 as a function of $\eta^{\rm jet}$, where the rows and columns correspond to the individual bins.

The correlation matrix for the systematic uncertainties on the $Z^0 j$ production cross-section measurements presented in Table 6 as a function of $p_T^{\rm jet}$, where the rows and columns correspond to the individual bins.

The correlation matrix for the systematic uncertainties on the $Z^0 j$ production cross-section measurements presented in Table 7 as a function of $|\Delta\phi|$, where the rows and columns correspond to the individual bins.

The correlation matrix for the systematic uncertainties on the $W^+j$ and $W^-j$ production cross-section measurements presented in Table 1 in bins of $\eta^\mu$. The matrix is used to calculate the ratio and asymmetry of $W^+j$ and $W^-j$ production as a function of $\eta^\mu$.

The correlation matrix for the systematic uncertainties on the $W^+j$, $W^-j$ and $Z^0 j$ production cross-section measurements presented in Tables 2 and 5 in bins of $\eta^{\rm jet}$. The matrix is used to calculate the ratios of $Wj$ to $Z^0 j$ production and the charge ratio and asymmetry of $Wj$ production in the total fiducial region.

The leptonic asymmetry dependence on the invariant mass of top-antitop system ($m_{t\bar{t}}$) in the fiducial volume.

The leptonic asymmetry dependence on the longitudinal boost of the top-antitop system ($\beta_z^{t\bar{t}}$) in the fiducial volume.

The leptonic asymmetry dependence on the transverse momentum of the top-antitop system ($p_T^{t\bar{t}}$) in the fiducial volume.

The top-antitop inclusive asymmetry in the fiducial volume.

The top-antitop asymmetry dependence on the invariant mass of top-antitop system ($m_{t\bar{t}}$) in the fiducial volume.

The top-antitop asymmetry dependence on the longitudinal boost of the top-antitop system ($\beta_z^{t\bar{t}}$) in the fiducial volume.

The top-antitop asymmetry dependence on the transverse momentum of the top-antitop system ($p_T^{t\bar{t}}$) in the fiducial volume.