Best fit values of $\sigma(gg\to H\to ZZ)$, $\sigma_i/\sigma_{gg\mathrm{F}}$, and $\mathrm{B}^f/\mathrm{B}^{ZZ}$ relative to their SM prediction from the combined analysis of the $\sqrt{s}$=7 and 8 TeV data. The results are shown for the combination of ATLAS and CMS, and also separately for each experiment, together with their total uncertainties and their breakdown into the four components described in the text. The expected uncertainties in the measurements are also shown.

Best fit values of $\sigma(gg\to H\to WW)$, $\sigma_i/\sigma_{gg\mathrm{F}}$, and $\mathrm{B}^f/\mathrm{B}^{WW}$ from the combined analysis of the $\sqrt{s}$=7 and 8 TeV data. The values involving cross sections are given for $\sqrt{s}$=8 TeV, assuming the SM values for $\sigma_i(7 \mathrm{TeV})/\sigma_i(8 \mathrm{TeV})$. The results are shown for the combination of ATLAS and CMS, and also separately for each experiment, together with their total uncertainties and their breakdown into the four components described in the text. The expected uncertainties in the measurements are also shown.

Best fit values of $\sigma(gg\to H\to WW)$, $\sigma_i/\sigma_{gg\mathrm{F}}$, and $\mathrm{B}^f/\mathrm{B}^{WW}$ relative to their SM prediction from the combined analysis of the $\sqrt{s}$=7 and 8 TeV data. The results are shown for the combination of ATLAS and CMS, and also separately for each experiment, together with their total uncertainties and their breakdown into the four components described in the text. The expected uncertainties in the measurements are also shown.

Best fit values of $\kappa_{gZ}= \kappa_{g}\cdot\kappa_{Z} / \kappa_{H}$ and of the ratios of coupling modifiers, as defined in the most generic parameterisation described in the context of the $\kappa$ framework, from the combined analysis of the $\sqrt{s}$=7 and 8 TeV data. The results are shown for the combination of ATLAS and CMS and also separately for each experiment, together with their total uncertainties and their breakdown into the four components described in the text. The uncertainties in $\lambda_{tg}$ and $\lambda_{WZ}$, for which a negative solution is allowed, are calculated around the overall best fit value. The expected total uncertainties in the measurements are also shown. For those parameters with no sensitivity to the sign, only the absolute values are shown.

Measured global signal strength $\mu$ and its total uncertainty, together with the breakdown of the uncertainty into its four components as defined in the text. The results are shown for the combination of ATLAS and CMS, and separately for each experiment. The expected uncertainty, with its breakdown, is also shown.

Measured signal strengths $\mu$ and their total uncertainties for different Higgs boson production processes. The results are shown for the combination of ATLAS and CMS, and separately for each experiment, for the combined $\sqrt{s}$=7 and 8 TeV data. The expected uncertainties in the measurements are also displayed. These results are obtained assuming that the Higgs boson branching fractions are the same as in the SM.

Measured signal strengths $\mu$ and their total uncertainties for different Higgs boson decay channels. The results are shown for the combination of ATLAS and CMS, and separately for each experiment, for the combined $\sqrt{s}$=7 and 8 TeV data. The expected uncertainties in the measurements are also displayed. These results are obtained assuming that the Higgs boson production process cross sections at $\sqrt{s}$ = 7 and 8 TeV are the same as in the SM.

Results of the ten-parameter fit of $\mu_F^f = \mu_{gg\mathrm{F}+ttH}^f$ and $\mu_V^f = \mu_{\mathrm{VBF}+VH}^f$ for each of the five decay channels. The results are shown for the combination of ATLAS and CMS, together with their measured and expected uncertainties. The measured results are also shown separately for each experiment.

Results of the six-parameter fit of the global ratio $\mu_V/\mu_F = \mu_{\mathrm{VBF}+VH}/\mu_{gg\mathrm{F}+ttH}$ together with $\mu_F^f$ for each of the five decay channels. The results are shown for the combination of ATLAS and CMS, together with their measured and expected uncertainties. The measured results are also shown separately for each experiment.

Fit results allowing BSM loop couplings, assuming that $|\kappa_{V}| \le$ 1, where $\kappa_{V}$ denotes $\kappa_{Z}$ or $\kappa_{W}$, and that $\mathrm{B_{BSM}} \ge$ 0. The results for the combination of ATLAS and CMS are reported with their measured and expected uncertainties. Also shown are the results from each experiment. For the parameters with both signs allowed, the other 1$\sigma$ interval is shown on a second line. For those parameters with no sensitivity to the sign, only the absolute values are shown.

Fit results allowing BSM loop couplings, assuming that there are no additional BSM contributions to the Higgs boson width, i.e. $\mathrm{B_{BSM}}=0$. The results for the combination of ATLAS and CMS are reported with their measured and expected uncertainties. Also shown are the results from each experiment. For the parameters with both signs allowed, the other 1$\sigma$ interval is shown on a second line. When a parameter is constrained and reaches a boundary, namely $\mathrm{B_{BSM}}$ = 0, the uncertainty is not indicated. For those parameters with no sensitivity to the sign, only the absolute values are shown.

Fit results for the parameterisation assuming the absence of BSM particles in the loops ($\mathrm{B_{BSM}}$=0). The results with their measured and expected uncertainties are reported for the combination of ATLAS and CMS, together with the individual results from each experiment. For the parameters with both signs allowed, the other 1$\sigma$ CL interval is shown on a second line. When a parameter is constrained and reaches a boundary, namely $|\kappa_\mu|$ = 0, the uncertainty is not indicated. For those parameters with no sensitivity to the sign, only the absolute values are shown.

Summary of fit results for a parameterisation probing the ratios of coupling modifiers for up-type versus down-type fermions. The results for the combination of ATLAS and CMS are reported together with their measured and expected uncertainties. Also shown are the results from each experiment. The parameter $\kappa_{uu}$ is positive definite since $\kappa_H$ is always assumed to be positive. For the parameter $\lambda_{du}$, for which both signs are allowed, the other 1$\sigma$ CL interval is shown on a second line. Negative values for the parameter $\lambda_{Vu}$ are excluded by more than 4$\sigma$.

Summary of fit results for a parameterisation probing the ratios of coupling modifiers for leptons versus quarks. The results for the combination of ATLAS and CMS are reported together with their measured and expected uncertainties. Also shown are the results from each experiment. The parameter $\kappa_{qq}$ is positive definite since $\kappa_H$ is always assumed to be positive. For the parameter $\lambda_{lq}$, for which there is no sensitivity to the sign, only the absolute values are shown. Negative values for the parameter $\lambda_{Vq}$ are excluded by more than 4$\sigma$.

Correlation matrix obtained from the fit combining the ATLAS and CMS data using the generic parameterisation with 23 parameters, $\sigma_i\cdot\mathrm{B}^f$ for each specific channel $i\to H\to f$. Only 20 parameters are shown because the other three, corresponding to the $H\to ZZ$ decay channel for the $WH$, $ZH$, and $ttH$ production processes, are not measured with a meaningful precision.

Correlation matrix obtained from the fit combining the ATLAS and CMS data using the generic parameterisation with nine parameters, $\sigma(gg\to H\to ZZ)$, $\sigma_i/\sigma_{gg\mathrm{F}}$, and $\mathrm{B}^f/\mathrm{B}^{ZZ}$.

Correlation matrix obtained from the fit combining the ATLAS and CMS data using the generic parameterisation with seven parameters, $\kappa_{gZ}=\kappa_{g}\cdot\kappa_{Z} / \kappa_{H}$ and the ratios of coupling modifiers.

Expected correlation matrix obtained from the fit combining ATLAS and CMS pre-fit Asimov data sets using the generic parameterisation with 23 parameters, $\sigma_i\cdot\mathrm{B}^f$ for each specific channel $i\to H\to f$. Only 20 parameters are shown because the other three, corresponding to the $H\to ZZ$ decay channel for the $WH$, $ZH$, and $ttH$ production processes, are not measured with a meaningful precision.

Expected correlation matrix obtained from the fit combining ATLAS and CMS pre-fit Asimov data sets using the generic parameterisation with nine parameters, $\sigma(gg\to H\to ZZ)$, $\sigma_i/\sigma_{gg\mathrm{F}}$, and $\mathrm{B}^f/\mathrm{B}^{ZZ}$.

Expected correlation matrix obtained from the fit combining ATLAS and CMS pre-fit Asimov data sets using the generic parameterisation with seven parameters, $\kappa_{gZ}=\kappa_{g}\cdot\kappa_{Z} / \kappa_{H}$ and the ratios of coupling modifiers.

ATLAS+CMS combined best-fit and 68% and 95% CL negative log-likelihood contours in the ($\kappa_{g}$,$\kappa_{\gamma}$) plane.

ATLAS best-fit and 68% and 95% CL negative log-likelihood contours in the ($\kappa_{g}$,$\kappa_{\gamma}$) plane.

CMS best-fit and 68% and 95% CL negative log-likelihood contours in the ($\kappa_{g}$,$\kappa_{\gamma}$) plane.

Best-fit and 68% and 95% CL negative log-likelihood contours in the ($\kappa_{F}$,$\kappa_{V}$) plane.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow\gamma\gamma$ channel.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow ZZ$ channel.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow WW$ channel.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow\tau\tau$ channel.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow bb$ channel.

ATLAS best-fit and 68% and 95% CL negative log-likelihood contours in the ($\kappa_{F}$,$\kappa_{V}$) plane.

CMS best-fit and 68% and 95% CL negative log-likelihood contours in the ($\kappa_{F}$,$\kappa_{V}$) plane.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow\gamma\gamma$ channel, assuming $\kappa_{F}>0$.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow ZZ$ channel, assuming $\kappa_{F}>0$.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow WW$ channel, assuming $\kappa_{F}>0$.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow\tau\tau$ channel, assuming $\kappa_{F}>0$.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow bb$ channel, assuming $\kappa_{F}>0$.

Best-fit and 68% and 95% CL negative log-likelihood contours in the ($\mu^{f}_{gg\mathrm{F}+ttH}$,$\mu^{f}_{\mathrm{VBF}+VH}$) plane for the $H\rightarrow\gamma\gamma$ channel.

Best-fit and 68% and 95% CL negative log-likelihood contours in the ($\mu^{f}_{gg\mathrm{F}+ttH}$,$\mu^{f}_{\mathrm{VBF}+VH}$) plane for the $H\rightarrow ZZ$ channel.

Best-fit and 68% and 95% CL negative log-likelihood contours in the ($\mu^{f}_{gg\mathrm{F}+ttH}$,$\mu^{f}_{\mathrm{VBF}+VH}$) plane for the $H\rightarrow WW$ channel.

Best-fit and 68% and 95% CL negative log-likelihood contours in the ($\mu^{f}_{gg\mathrm{F}+ttH}$,$\mu^{f}_{\mathrm{VBF}+VH}$) plane for the $H\rightarrow\tau\tau$ channel.

Best-fit and 68% and 95% CL negative log-likelihood contours in the ($\mu^{f}_{gg\mathrm{F}+ttH}$,$\mu^{f}_{\mathrm{VBF}+VH}$) plane for the $H\rightarrow bb$ channel.

Limit

Limit

Limit

Limit

Limit

Signal acceptance times efficiency as a function of mass for Z' → WW in the HVT model

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

Signal acceptance times efficiency as a function of mass for GKK → WW in the bulk RS model

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

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 (b) WZ signal region.

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

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

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

Signal acceptance times efficiency as a function of mass for Scalar → WW in the heavy scalar model

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

Signal acceptance times efficiency as a function of mass for Z' → WW in the HVT model

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.

Signal acceptance times efficiency as a function of mass for GKK → WW in the bulk RS model

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+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 V' 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 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 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 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 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 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 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.

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

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.

Observed 95% CL upper limits on the production cross section times branching ratio to a photon and a quark or gluon for the ADD model. The limits are placed as a function of M_th. The calculation is performed using ensemble tests for masses in the search range every 500 GeV.

Fiducial acceptance and selection efficiency for the ADD model as a function of M_th.

Fiducial acceptance and selection efficiency for the RS1 model as a function of M_th.

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].

Measured cross sections for isolated-photon plus jet production as a function of $m^{\gamma-\rm jet}$.

Measured cross sections for isolated-photon plus jet production as a function of $|\cos\theta^{\star}|$.

Upper limits on the fiducial cross section times branching ratio to two photons at centre-of-mass energy of 13 TeV of a narrow-width (Γ_X = 4 MeV) spin-0 resonance as a function of its mass m_X.

Upper limits on the production cross section times branching ratio to two photons at centre-of-mass energy of 13 TeV of the lightest KK graviton as a function of its mass m_G* for k/MPl=0.01.

Upper limits on the production cross section times branching ratio to two photons at centre-of-mass energy of 13 TeV of the lightest KK graviton as a function of its mass m_G* for k/MPl=0.10. Only the limits derived with the asymptotic formulae are quoted here.

Upper limits on the production cross section times branching ratio to two photons at centre-of-mass energy of 13 TeV of the lightest KK graviton as a function of its mass m_G* for k/MPl=0.20.

Upper limits on the production cross section times branching ratio to two photons at centre-of-mass energy of 13 TeV of the lightest KK graviton as a function of its mass m_G* for k/MPl=0.30.

Distribution of the diphoton invariant mass for data events passing the spin-0 selection. The data points are plotted at the centre of each bin. The error bars indicate statistical uncertainties. The distribution consists of not only genuine diphoton events, but also events where at least one photon is faked by a jet. There is no data event above 2700 GeV.

Distribution of the diphoton invariant mass for data events passing the spin-2 selection. The data points are plotted at the centre of each bin. The error bars indicate statistical uncertainties. The distribution consists of not only genuine diphoton events, but also events where at least one photon is faked by a jet. There is no data event above 2700 GeV.

Fiducial acceptance and product of the fiducial acceptance times the combined reconstruction and identification efficiency as a function of the mass for a spin-0 resonant signal with narrow width under the spin-0 selection. Only MC statistical uncertainties are included.

Fiducial acceptance and product of the fiducial acceptance times the combined reconstruction and identification efficiency as a function of the mass for a spin-2 resonant signal with k/MPl=0.1 under the spin-2 selection. The definition of fiducial region is provided in JHEP 09 (2016) 001. Only MC statistical uncertainties are included.

Fiducial acceptance and product of the fiducial acceptance times the combined reconstruction and identification efficiency as a function of the mass for an ADD excess (GRW formalism), calculated as the difference between the sum of ADD and SM contributions (including their interference) and the SM contribution, under the spin-2 selection in the signal region M(gamma gamma)>2240 GeV. The definition of fiducial region is provided in JHEP 09 (2016) 001, and M(gamma gamma)>2240 GeV is required in addition. Only MC statistical uncertainties are included.

The $m_{\mathrm{eff}}$ distribution for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement in SR2. Distributions for data, the estimated SM backgrounds, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal region.

Expected 95% CL exclusion limits on wino $W/Z$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on wino $W/Z$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on wino $W/Z$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on wino $W/Z$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on wino $W/h$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on wino $W/h$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on wino $W/h$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on wino $W/h$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on $\tilde{\ell}/\tilde{\nu}$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on $\tilde{\ell}/\tilde{\nu}$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on $\tilde{\ell}/\tilde{\nu}$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on $\tilde{\ell}/\tilde{\nu}$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on gluino NSLP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on gluino NSLP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on gluino NSLP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on gluino NSLP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/Z$ RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0A. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/Z$ RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0A, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/Z$ RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0B. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/Z$ RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0B, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/h$ RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0A. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/h$ RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0A, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/h$ RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0B. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/h$ RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0B, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the slepton/sneutrino masses in the context of the slepton/sneutrino RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0A. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the slepton/sneutrino masses in the context of the slepton/sneutrino RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0A, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the slepton/sneutrino masses in the context of the slepton/sneutrino RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0B. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the slepton/sneutrino masses in the context of the slepton/sneutrino RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0B, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the gluino masses in the context of the gluino RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0A. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the gluino masses in the context of the gluino RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0A, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the gluino masses in the context of the gluino RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0B. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the gluino masses in the context of the gluino RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0B, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}\tilde{\chi}_1^{0}$ masses in the context of the higgsino GGM scenario in SR0C. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}\tilde{\chi}_1^{0}$ masses in the context of the higgsino GGM scenario in SR0D. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the wino $W/Z$ model for $\lambda_{12k} \neq 0$ RPV couplings. For the $\lambda_{12k} \neq 0$ case, the results from SR0B are adopted everywhere in the final exclusion limit contours, as is found to be the most powerful signal region among SR0A and SR0B in the majority of the signal grid points of this model.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the wino $W/Z$ model for $\lambda_{i33} \neq 0$ RPV couplings. A combination of SR0A + SR1 + SR2 or SR0B + SR1 + SR2 is tested to detect the best expected limit; shown on the plot is the region (SR0A or SR0B) which is chosen to provide the best expected limit in combination with SR1 and SR2. The results from the combination SR0B + SR1 + SR2 are finally adopted everywhere in the final exclusion limit contour since they provide the best expected limit.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the wino $W/h$ model for $\lambda_{12k} \neq 0$ RPV couplings. For the $\lambda_{12k} \neq 0$ case, the results from SR0B are adopted everywhere in the final exclusion limit contours, as is found to be the most powerful signal region among SR0A and SR0B in the majority of the signal grid points of this model.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the wino $W/h$ model for $\lambda_{i33} \neq 0$ RPV couplings. A combination of SR0A + SR1 + SR2 or SR0B + SR1 + SR2 is tested to detect the best expected limit; shown on the plot is the region (SR0A or SR0B) which is chosen to provide the best expected limit in combination with SR1 and SR2. The results from the combination SR0B + SR1 + SR2 are finally adopted everywhere in the final exclusion limit contour since they provide the best expected limit.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the slepton/sneutrino model for $\lambda_{12k} \neq 0$ RPV couplings.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the slepton/sneutrino model for $\lambda_{i33} \neq 0$ RPV couplings. A combination of SR0A + SR1 + SR2 or SR0B + SR1 + SR2 is tested to detect the best expected limit; shown on the plot is the region (SR0A or SR0B) which is chosen to provide the best expected limit in combination with SR1 and SR2.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the gluino model for $\lambda_{12k} \neq 0$ RPV couplings.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the gluino model for $\lambda_{i33} \neq 0$ RPV couplings. A combination of SR0A + SR1 + SR2 or SR0B + SR1 + SR2 is tested to detect the best expected limit; shown on the plot is the region (SR0A or SR0B) which is chosen to provide the best expected limit in combination with SR1 and SR2.

The best expected exclusion power between the overlapping SR0C and SR0D at each signal point as is adopted in the limit combination of the GGM higgsino model.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{+}\tilde{\chi}_1^{-}$ $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0A. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/Z$ $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0A. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/h$ $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0A. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the slepton/sneutrino $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0A. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the gluino $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0A. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{+}\tilde{\chi}_1^{-}$ $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0B. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/Z$ $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0B. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/h$ $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0B. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the slepton/sneutrino $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0B. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the gluino $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0B. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the GGM Higgsino models with BR($\tilde{\chi}_1^0 \rightarrow Z \tilde{G}$)=100% and BR($\tilde{\chi}_1^0 \rightarrow Z \tilde{G}$)=50% fulfilling the selection criteria of SR0C. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the GGM Higgsino models with BR($\tilde{\chi}_1^0 \rightarrow Z \tilde{G}$)=100% and BR($\tilde{\chi}_1^0 \rightarrow Z \tilde{G}$)=50% fulfilling the selection criteria of SR0D. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{+}\tilde{\chi}_1^{-}$ $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR1. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/Z$ $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR1. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/h$ $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR1. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the slepton/sneutrino $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR1. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the gluino $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR1. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{+}\tilde{\chi}_1^{-}$ $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR2. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/Z$ $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR2. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/h$ $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR2. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the slepton/sneutrino $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR2. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the gluino $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR2. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Cutflow event yields in regions SR0A and SR0B for RPV models with the $\lambda_{12k} \neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 36.1$ fb$^{-1}$. The "Initial" number indicates the weighted number of events before any selection cut is applied. The last entries show the normalized number of events surviving the selection requirements of SR0A and SR0B.

Cutflow event yields in regions SR0C and SR0D for GGM Higgsino models with BR($\tilde{\chi}_1^0 \rightarrow Z \tilde{G}$)=100% or BR($\tilde{\chi}_1^0 \rightarrow Z \tilde{G}$)=50%, and $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^0\tilde{\chi}_1^0$ mass of 400 GeV. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 36.1$ fb$^{-1}$. The "Initial" number indicates the weighted number of events before any selection cut is applied. The "Generator Filter" step is applied during the MC generation of the simulated events; the BR=100% sample has a generator filter of $\geq 4e/\mu$ leptons with $p_{\mathrm{T}}>4$ GeV and $|\eta|<2.8$, and the BR=50% sample has a generator filter of $\geq 4 e/\mu/\tau_{\mathrm{had-vis}}$ leptons with $p_{\mathrm{T}}(e,\mu)>4$ GeV, $p_{\mathrm{T}}(\tau_{\mathrm{had-vis}}^{\mathrm{visible}})>15$ GeV and $|\eta|<2.8$. The $ZZ$ selection cutflow step refers to the mass window cut for the leading and subleading $Z$ boson candidate between $81.2-101.2$ GeV and $61.2-101.2$ GeV, respectively. The last entries show the efficiency of events surviving the selection requirements defined in SR0C and SR0D.

Cutflow event yields in region SR1 for RPV models with the $\lambda_{i33} \neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 36.1$ fb$^{-1}$. The "Initial" number indicates the weighted number of events before any selection cut is applied. The last entries show the normalized number of events surviving the selection requirements of SR1.

Cutflow event yields in region SR2 for RPV models with the $\lambda_{i33} \neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 36.1$ fb$^{-1}$. The "Initial" number indicates the weighted number of events before any selection cut is applied. The last entries show the normalized number of events surviving the selection requirements of SR2.

Cross sections for the slepton/snuetrino model for different NLSP masses.