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.

Expected and observed 95% CL upper limits on the cross section times branching fraction, $\sigma_{\mathrm{VBF}}(H^{\pm\pm}) \times \mathrm{{\it B}}(H^{\pm\pm} \to W^{\pm}W^{\pm})$, as a function of doubly charged Higgs boson mass.

Expected and observed 95% CL upper limits on $s_H$ in the Georgi--Machacek model as a function of doubly charged Higgs boson mass.

Observed and expected 95% CL limits on the coefficients for higher-order (dimension-eight) operators in the effective field theory Lagrangian.

Main systematic uncertainties in the analysis.

Signal efficiency from the generator level fiducial definition to the reconstruction level selection for the dilepton mass variable.

Selection acceptance times efficiency for VBF H -> ZZ -> vvqq as a function of the Higgs boson mass, combining the HP and LP signal regions.

Selection acceptance times efficiency for DY W' -> ZW -> llqq as a function of the W' mass, combining the HP and LP signal regions of the ZV -> llJ selection and the b-tagged and untagged regions of the ZV -> lljj selection.

Selection acceptance times efficiency for VBF W' -> ZW -> llqq as a function of the W' mass, combining the HP and LP signal regions of the ZV -> llJ selection and the b-tagged and untagged regions of the ZV -> lljj selection.

Selection acceptance times efficiency for DY W' -> ZW -> vvqq as a function of the W' mass, combining the HP and LP signal regions.

Selection acceptance times efficiency for VBF W' -> ZW -> vvqq as a function of the W' mass, combining the HP and LP signal regions.

Selection acceptance times efficiency for G* -> ZZ -> llqq as a function of the W' mass, combining the HP and LP signal regions of the ZV -> llJ selection and the b-tagged and untagged regions of the ZV -> lljj selection.

Selection acceptance times efficiency for G* -> ZZ -> vvqq as a function of the W' mass, combining the HP and LP signal regions.

Observed and expected 95% CL upper limits on $\sigma\times$BR($H\to ZZ$) at $\sqrt{s} = 13$ TeV for ggF production of a heavy Higgs boson as a function of its mass, combining $\ell\ell qq$ and $\nu\nu qq$ searches.

Observed and expected 95% CL upper limits on $\sigma\times$BR($H\to ZZ$) at $\sqrt{s} = 13$ TeV for VBF production of a heavy Higgs boson as a function of its mass, combining $\ell\ell qq$ and $\nu\nu qq$ searches.

Observed and expected 95% CL upper limits on $\sigma\times$BR($W'\to ZW$) at $\sqrt{s} = 13$ TeV for Drell-Yan production of a $W'$ boson in the HVT model as a function of its mass, combining $\ell\ell qq$ and $\nu\nu qq$ searches.

Observed and expected 95% CL upper limits on $\sigma\times$BR($W'\to ZW$) at $\sqrt{s} = 13$ TeV for VBF production of a $W'$ boson in the HVT model as a function of its mass, combining $\ell\ell qq$ and $\nu\nu qq$ searches.

Observed and expected 95% CL upper limits on $\sigma\times$BR($G_{\mathrm{KK}}\to ZZ$) at $\sqrt{s} = 13$ TeV for the production of a bulk RS graviton with couplings of $k/\overline{M}_{\mathrm{Pl}}=1$.

Observed and expected 95% CL upper limits on $\sigma\times$BR($G_{\mathrm{KK}}\to ZZ$) at $\sqrt{s} = 13$ TeV for the production of a bulk RS graviton with couplings of $k/\overline{M}_{\mathrm{Pl}}=0.5$.

DM exclusion limit in the two-dimensional phase space of WIMP mass m_χ vs mediator mass m_med determined using the combined ee+μμ channel. Both the observed and expected limits are presented, and the 1σ uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_χ'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs, and the other grey line gives the perturbative limit (arXiv 1603.04156). The relic density line (arXiv 1603.04156) illustrates the combination of m_χ and m_med that would explain the observed DM relic density.

DM exclusion limit in the two-dimensional phase space of WIMP mass m_χ vs mediator mass m_med determined using the combined ee+μμ channel. Both the observed and expected limits are presented, and the 1σ uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_χ'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs, and the other grey line gives the perturbative limit (arXiv 1603.04156). The relic density line (arXiv 1603.04156) illustrates the combination of m_χ and m_med that would explain the observed DM relic density.

DM exclusion limit in the two-dimensional phase space of WIMP mass m_χ vs mediator mass m_med determined using the combined ee+μμ channel. Both the observed and expected limits are presented, and the 1σ uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_χ'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs, and the other grey line gives the perturbative limit (arXiv 1603.04156). The relic density line (arXiv 1603.04156) illustrates the combination of m_χ and m_med that would explain the observed DM relic density.

The 95% CL upper limits on the production cross-section of the ZH process with the prompt Z→ ee and Z→ μμ decays and the invisible Higgs boson decays as a function of m_H, obtained from the combined ee+μμ channel. The observed and expected limits are given, as well as the ±1σ and ±2σ error bands on the expected limits. The signal process is only modelled for the qq initial state, and the theory uncertainties on the signal prediction are not considered.

DM exclusion limit in the two-dimensional phase space of m_χ vs m_med set using the combined ee+μμ channel. The DM model assumes a vector mediator, a fermionic WIMP, and the coupling parameters g_q = 0.25 and g_χ = 1. Both the observed and expected limits are presented, and the 1σ uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_χ'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs. The relic density line [arXiv 1603.04156] illustrates the combination of m_χ and m_med that would explain the observed DM relic density.

DM exclusion limit in the two-dimensional phase space of m_χ vs m_med set using the combined ee+μμ channel. The DM model assumes a vector mediator, a fermionic WIMP, and the coupling parameters g_q = 0.25 and g_χ = 1. Both the observed and expected limits are presented, and the 1σ uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_χ'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs. The relic density line [arXiv 1603.04156] illustrates the combination of m_χ and m_med that would explain the observed DM relic density.

DM exclusion limit in the two-dimensional phase space of m_χ vs m_med set using the combined ee+μμ channel. The DM model assumes a vector mediator, a fermionic WIMP, and the coupling parameters g_q = 0.25 and g_χ = 1. Both the observed and expected limits are presented, and the 1σ uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_χ'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs. The relic density line [arXiv 1603.04156] illustrates the combination of m_χ and m_med that would explain the observed DM relic density.

DM exclusion limit in the two-dimensional phase space of m_χ vs m_med set using the combined ee+μμ channel. The DM model assumes a vector mediator, a fermionic WIMP, and the coupling parameters g_q = 0.25 and g_χ = 1. Both the observed and expected limits are presented, and the 1σ uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_χ'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs. The relic density line [arXiv 1603.04156] illustrates the combination of m_χ and m_med that would explain the observed DM relic density.

Limits on the WIMP and proton scattering cross section as a function of WIMP mass, obtained for simplified dark matter models with an axial-vector mediator (left) and a vector mediator (right). The solid black line shows the observed limit at the 90% confidence level from this search. The left plot incorporates the latest results from these competitive direct-search experiments, LUX [arXiv 1705.03380], PICO-2L [Phys. Rev. Lett. 114 (2015) 231302], and PICO-60 [arXiv 1702.07666]. The right plot incorporates the latest results from the following experiments, CRESST-II [Eur. Phys. J. C76 (2016) 25], CDMSlite [Phys. Rev. Lett. 116 (2016) 071301], PandaX-II [Phys. Rev. Lett. 117 (2016) 121303], LUX [Phys. Rev. Lett. 118 (2017) 021303], and XENON1T [arXiv 1705.06655].

Limits on the WIMP and proton scattering cross section as a function of WIMP mass, obtained for simplified dark matter models with an axial-vector mediator (left) and a vector mediator (right). The solid black line shows the observed limit at the 90% confidence level from this search. The left plot incorporates the latest results from these competitive direct-search experiments, LUX [arXiv 1705.03380], PICO-2L [Phys. Rev. Lett. 114 (2015) 231302], and PICO-60 [arXiv 1702.07666]. The right plot incorporates the latest results from the following experiments, CRESST-II [Eur. Phys. J. C76 (2016) 25], CDMSlite [Phys. Rev. Lett. 116 (2016) 071301], PandaX-II [Phys. Rev. Lett. 117 (2016) 121303], LUX [Phys. Rev. Lett. 118 (2017) 021303], and XENON1T [arXiv 1705.06655].

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

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

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

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

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

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

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

Observed 95% CL exclusion contours for pMSSM model.

Expected 95% CL exclusion contours for pMSSM model.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Acceptance in 9J discovery signal region for pMSSM model.

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

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

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

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

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

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

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

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

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

Efficiency in 9J discovery signal region for pMSSM model.

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

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

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

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

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

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

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

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

The $m_{\mathrm{T2}}$ distribution in the multi-jet background VR-F for SR-lowMass. The stacked histograms show the contribution of the non-multi-jet SM backgrounds from MC simulation. The multi-jet contribution is estimated from data using the ABCD method. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The last bin in the left panels includes the overflow events.

The $E_{\mathrm T}^{\mathrm{miss}}$ distribution in the multi-jet background VR-F for SR-highMass. The stacked histograms show the contribution of the non-multi-jet SM backgrounds from MC simulation. The multi-jet contribution is estimated from data using the ABCD method. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The last bin in the left panels includes the overflow events.

The $m_{\mathrm{T2}}$ distribution in the multi-jet background VR-F for SR-highMass. The stacked histograms show the contribution of the non-multi-jet SM backgrounds from MC simulation. The multi-jet contribution is estimated from data using the ABCD method. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The last bin in the left panels includes the overflow events.

The $E_{\mathrm T}^{\mathrm{miss}}$ distribution in the $W$-VR region. The SM backgrounds other than multi-jet production are estimated from MC simulation. The contribution of $W$+jets events is scaled to the fit result. The multi-jet contribution is estimated from data using the $OS--SS$ method. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate. The last bin includes the overflow events.

The $m_{\mathrm{T2}}$ distribution in the $W$-VR region. The SM backgrounds other than multi-jet production are estimated from MC simulation. The contribution of $W$+jets events is scaled to the fit result. The multi-jet contribution is estimated from data using the $OS--SS$ method. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate. The last bin includes the overflow events.

The $m_{\mathrm{T2}}$ distribution in the $Z$-VR region. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is estimated from data using the ABCD method, using CRs obtained with the same technique used for the SRs. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate. The last bin includes the overflow events except for the upper left panel.

The $m_{\mathrm{T2}}$ distribution in the Top-VR region. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is estimated from data using the ABCD method, using CRs obtained with the same technique used for the SRs. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate. The last bin includes the overflow events except for the upper left panel.

The $m_{\mathrm{T2}}$ distribution in the $WW$-VR region. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is negligible and not considered. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate. The last bin includes the overflow events except for the upper left panel.

The $m_{\mathrm{T2}}$ distribution in the $ZZ$-VR region. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is negligible and not considered. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate. The last bin includes the overflow events except for the upper left panel.

The $m_{\mathrm{T2}}$ distribution before the $m_{\mathrm{T2}}$ requirement is applied for SR-lowMass region, where the arrow indicates the position of the cut in the signal region. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalisation factors. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the total SM background estimate. The last bin includes the overflow events.

The $m_{\mathrm{T2}}$ distribution before the $m_{\mathrm{T2}}$ requirement is applied for SR-highMass region, where the arrow indicates the position of the cut in the signal region. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalisation factors. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the total SM background estimate. The last bin includes the overflow events.

Observed exclusion contours in chargino pair production model.

Expected exclusion contours in chargino pair production model.

Observed exclusion contours in chargino chargino and chargino neutralino production model.

Expected exclusion contours in chargino chargino and chargino neutralino production model.

Observed upper limits on the model cross-section in units of pb as a function of the chargino and neutralino masses in chargino chargino pair production.

Observed upper limits on the model cross-section in units of pb as a function of the chargino and neutralino masses in chargino chargino and chargino neutralino pair production.

Best signal region used in chargino chargino and chargino neutralino pair production, H is corresponding to SR-highMass and L is SR-lowMass.

Observed CLs significance in variable-x model of chargino chargino pair production for compressed mass scenario.

Expected CLs significance in variable-x model of chargino chargino pair production for compressed mass scenario.

Observed CLs significance in variable-x model of chargino chargino pair production for large mass splitting scenario.

Expected CLs significance in variable-x model of chargino chargino pair production for large mass splitting scenario.

Observed CLs significance in variable-x model of chargino chargino and chargino neutralino pair production for compressed mass scenario.

Expected CLs significance in variable-x model of chargino chargino and chargino neutralino pair production for compressed mass scenario.

Observed CLs significance in variable-x model of chargino chargino and chargino neutralino pair production for large mass splitting scenario.

Expected CLs significance in variable-x model of chargino chargino and chargino neutralino pair production for large mass splitting scenario.

Acceptance in SR-lowMass for CHARGINO1 NEUTRALINO2 production.

Acceptance in SR-highMass for CHARGINO1 NEUTRALINO2 production.

Acceptance in SR-highMass for CHARGINO1 CHARGINO1 production.

Efficiency in SR-lowMass for CHARGINO1 NEUTRALINO2 production.

Efficiency in SR-highMass for CHARGINO1 NEUTRALINO2 production.

Efficiency in SR-highMass for CHARGINO1 CHARGINO1 production.

Cut flow for the reference point 1 (CHARGINO1 NEUTRALINO2 production) in SR-lowMass. The column labelled $N_{raw}$ shows the results for the generated number of events, while $N_{weighted}$ includes all correction factors applied to simulation, and is normalised to 36.1 fb$^{-1}$. The quoted uncertainties are statistical only. At the step ``at least two medium tau candidates, matched to trigger objects' the following requirements are applied: the event is recorded using either the asymmetric di-tau trigger or the di-tau+$E_{\mathrm T}^{\mathrm{miss}}$ trigger, and the two matched tau candidates must be of medium quality. If the event has been selected by the asymmetric di-tau trigger, the two tau candidates are required to have ${p}_{\mathrm{T}, \tau_1}>$ 95 GeV and ${p}_{\mathrm{T}, \tau_2}>$ 65 GeV. If the event has been selected by the di-tau+$E_{\mathrm T}^{\mathrm{miss}}$ trigger, the two tau candidates are required to have ${p}_{\mathrm{T}, \tau_1}>$ 50 GeV, ${p}_{\mathrm{T}, \tau_2}>$ 40 GeV, and $E_{\mathrm T}^{\mathrm{miss}}$ > 150 GeV is required.}

Cut flow for the reference point 2 (CHARGINO1 CHARGINO1 production) in SR-highMass. The column labelled $N_{raw}$ shows the results for the generated number of events, while $N_{weighted}$ includes all correction factors applied to simulation, and is normalised to 36.1 fb$^{-1}$. The quoted uncertainties are statistical only. At the step ``at least two medium tau candidates, matched to trigger objects' the following requirements are applied: the event is recorded using either the asymmetric di-tau trigger or the di-tau+$E_{\mathrm T}^{\mathrm{miss}}$ trigger, and the two matched tau candidates must be of medium quality. If the event has been selected by the asymmetric di-tau trigger, the two tau candidates are required to have ${p}_{\mathrm{T}, \tau_1}>$ 95 GeV and ${p}_{\mathrm{T}, \tau_2}>$ 65 GeV. If the event has been selected by the di-tau+$E_{\mathrm T}^{\mathrm{miss}}$ trigger, the two tau candidates are required to have ${p}_{\mathrm{T}, \tau_1}>$ 50 GeV, ${p}_{\mathrm{T}, \tau_2}>$ 40 GeV, and $E_{\mathrm T}^{\mathrm{miss}}$ > 150 GeV is required.}

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the particle level as a function of y(top).

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the particle level as a function of pt(ttbar).

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the particle level as a function of y(ttbar).

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the particle level as a function of m(ttbar).

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the particle level as a function of dphi(ttbar).

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the parton level as a function of pt(top).

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the parton level as a function of y(top).

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the parton level as a function of pt(ttbar).

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the parton level as a function of y(ttbar).

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the parton level as a function of m(ttbar).

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the parton level as a function of dphi(ttbar).

Statistical covariance matrix for the normalized differential tt cross section in dilepton channel at particle level as a function of the transverse momentum pt(let).

Statistical covariance matrix for the normalized differential tt cross section in dilepton channel at particle level as a function of the transverse momentum pt(jet).

Statistical covariance matrix for the normalized differential tt cross section in dilepton channel at particle level as a function of the transverse momentum pt(top) of the top quark or antiquark.

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the particle level as a function of y(top) of the top quark or antiquark.

Statistical covariance matrix for the normalized differential tt cross section in dilepton channel at particle level as a function of the transverse momentum pt(ttbar) of the top quark and antiquark.

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the particle level as a function of y(ttbar) of the top quark and antiquark.

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the particle level as a function of m(ttbar) of the top quark and antiquark.

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the particle level as a function of dphi(ttbar) of the top quark and antiquark.

Statistical covariance matrix for the normalized differential tt cross section in dilepton channel at parton level as a function of the transverse momentum pt(top) of the top quark or antiquark.

Statistical covariance matrix for the normalized differential tt cross section in dilepton channel at parton level as a function of the transverse momentum y(top) of the top quark or antiquark.

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the parton level as a function of pt(ttbar) of the top quark and antiquark.

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the parton level as a function of y(ttbar) of the top quark and antiquark.

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the parton level as a function of m(ttbar) of the top quark and antiquark.

Normalized differential ttbar cross sections with statistical and systematic uncertainties at the parton level as a function of dphi(ttbar) of the top quark and antiquark.

Dijet mass distributions for data in the (a) WW signal region.

Dijet mass distributions for data in the (b) WZ signal region.

Dijet mass distributions for data in the (c) ZZ signal region.

Dijet mass distributions for data in the (d) WZ+WW signal region.

Dijet mass distributions for data in the (e) WW+ZZ signal region.

Upper limits at the 95% CL on the cross section times branching ratio for WW+WZ production as a function of V' mass

Upper limits at the 95% CL on the cross section times branching ratio for WW+ZZ production as a function of GKK mass for the bulk RS model with k/M̄Pl=1.

Upper limits at the 95% CL on the cross section times branching ratio for (c) WW+ZZ production as a function of scalar mass.

Upper limits at the 95% CL on the cross section times branching ratio for WW production as a function of V' mass

Upper limits at the 95% CL on the cross section times branching ratio for WZ production as a function of V' mass

Upper limits at the 95% CL on the cross section times branching ratio for WW production as a function of GKK mass for the bulk RS model with k/M̄Pl=0.5.

Upper limits at the 95% CL on the cross section times branching ratio for ZZ production as a function of GKK mass for the bulk RS model with k/M̄Pl=0.5.

Upper limits at the 95% CL on the cross section times branching ratio for WW production as a function of GKK mass for the bulk RS model with k/M̄Pl=1.

Upper limits at the 95% CL on the cross section times branching ratio for ZZ production as a function of GKK mass for the bulk RS model with k/M̄Pl=1.

Upper limits at the 95% CL on the cross section times branching ratio for WW+ZZ production as a function of GKK mass for the bulk RS model with k/M̄Pl=0.5.

Upper limits at the 95% CL on the cross section times branching ratio for WW production as a function of scalar mass.

Upper limits at the 95% CL on the cross section times branching ratio for ZZ production as a function of scalar mass.

The mjj distribution in data and simulated events after requiring all selection criteria in the e+e- channel. The various signal hypotheses displayed have been scaled to a cross section of 5 pb for display purposes.

The mjj distribution in data and simulated events after requiring all selection criteria in the e^{+/-}mu^{-/+} channel. The various signal hypotheses displayed have been scaled to a cross section of 5 pb for display purposes.

The mjj distribution in data and simulated events after requiring all selection criteria in the mu+mu- channel. The various signal hypotheses displayed have been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events after requiring all selection criteria, in the e+e− channel. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised resonant DNN output is evaluated at mX=400GeV. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events after requiring all selection criteria, in the e+e− channel. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised nonresonant DNN output is evaluated at \kappa_\lambda=1, \kappa_t=1. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events after requiring all selection criteria, in the e^{+/-}mu^{-/+} channel. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised resonant DNN output is evaluated at mX=400GeV. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events after requiring all selection criteria, in the e^{+/-}mu^{-/+} channel. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised nonresonant DNN output is evaluated at \kappa_\lambda=1, \kappa_t=1. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events after requiring all selection criteria, in the mu+mu− channel. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised resonant DNN output is evaluated at mX=400GeV. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events after requiring all selection criteria, in the mu+mu− channel. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised nonresonant DNN output is evaluated at \kappa_\lambda=1, \kappa_t=1. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events, for the e+e- channel, in three different mjj regions. The parameterised resonant DNN output is evaluated at mX=400GeV. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events, for the e+e- channel, in three different mjj regions. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised nonresonant DNN output is evaluated at \kappa_\lambda=1, \kappa_t=1. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events, for the e^{+/-}mu^{-/+} channel, in three different mjj regions. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised resonant DNN output is evaluated at mX=400GeV. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events, for the e^{+/-}mu^{-/+} channel, in three different mjj regions. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised nonresonant DNN output is evaluated at \kappa_\lambda=1, \kappa_t=1. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events, for the mu+mu- channel, in three different mjj regions. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised resonant DNN output is evaluated at mX=400GeV. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events, for the mu+mu- channel, in three different mjj regions. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised nonresonant DNN output is evaluated at \kappa_\lambda=1, \kappa_t=1. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

Expected and observed 95% CL upper limits on the product of the production cross section for X and branching fraction for X -> HH -> bbVV -> bblnulnu, as a function of mX. These limits are computed using the asymptotic CLs method, combining all channels, for the spin-0 hypothesis.

Expected and observed 95% CL upper limits on the product of the production cross section for X and branching fraction for X -> HH -> bbVV -> bblnulnu, as a function of mX. These limits are computed using the asymptotic CLs method, combining all channels, for the spin-2 hypothesis.

expected and observed 95% CL upper limits on the product of the Higgs boson pair production cross section and branching fraction for HH -> bbVV -> bblnulnu as a function of kappa_top/kappa_lambda.

Exclusions in the (\kappa_top, \kappa_\lambda) plane. Parameters excluded at 95% CL with the observed data, and expected exclusions and the 68 and 95% bands.