Differential cross-sections for EW $Zjj$ production as a function of $\Delta\phi_{jj}$ with breakdown of associated uncertainties. The statistical uncertainty is correlated across bins according to the statistical cross correlation matrix presented in Table 21.

Differential cross-sections for inclusive $Zjj$ production in the EW $Zjj$ signal region ($N^\mathrm{gap}_\mathrm{jets}=0$, $\xi_Z < 0.5$) as a function of $m_{jj}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in the EW $Zjj$ signal region ($N^\mathrm{gap}_\mathrm{jets}=0$, $\xi_Z < 0.5$) as a function of $\Delta y_{jj}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in the EW $Zjj$ signal region ($N^\mathrm{gap}_\mathrm{jets}=0$, $\xi_Z < 0.5$) as a function of $p_{\mathrm{T},\ell\ell}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in the EW $Zjj$ signal region ($N^\mathrm{gap}_\mathrm{jets}=0$, $\xi_Z < 0.5$) as a function of $\Delta\phi_{jj}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in control region CRa ($N^\mathrm{gap}_\mathrm{jets} \geq 1$, $\xi_Z < 0.5$) as a function of $m_{jj}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in control region CRa ($N^\mathrm{gap}_\mathrm{jets} \geq 1$, $\xi_Z < 0.5$) as a function of $\Delta y_{jj}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in control region CRa ($N^\mathrm{gap}_\mathrm{jets} \geq 1$, $\xi_Z < 0.5$) as a function of $p_{\mathrm{T},\ell\ell}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in control region CRa ($N^\mathrm{gap}_\mathrm{jets} \geq 1$, $\xi_Z < 0.5$) as a function of $\Delta\phi_{jj}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in control region CRb ($N^\mathrm{gap}_\mathrm{jets} \geq 1$, $\xi_Z > 0.5$) as a function of $m_{jj}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in control region CRb ($N^\mathrm{gap}_\mathrm{jets} \geq 1$, $\xi_Z > 0.5$) as a function of $\Delta y_{jj}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in control region CRb ($N^\mathrm{gap}_\mathrm{jets} \geq 1$, $\xi_Z > 0.5$) as a function of $p_{\mathrm{T},\ell\ell}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in control region CRb ($N^\mathrm{gap}_\mathrm{jets} \geq 1$, $\xi_Z > 0.5$) as a function of $\Delta\phi_{jj}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in control region CRc ($N^\mathrm{gap}_\mathrm{jets} = 0$, $\xi_Z > 0.5$) as a function of $m_{jj}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in control region CRc ($N^\mathrm{gap}_\mathrm{jets} = 0$, $\xi_Z > 0.5$) as a function of $\Delta y_{jj}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in control region CRc ($N^\mathrm{gap}_\mathrm{jets} = 0$, $\xi_Z > 0.5$) as a function of $p_{\mathrm{T},\ell\ell}$ with breakdown of associated uncertainties.

Differential cross-sections for inclusive $Zjj$ production in control region CRc ($N^\mathrm{gap}_\mathrm{jets} = 0$, $\xi_Z > 0.5$) as a function of $\Delta\phi_{jj}$ with breakdown of associated uncertainties.

Statistical correlation between bins of the differential cross-section measurements of EW $Zjj$ production in the signal region ($N^\mathrm{gap}_\mathrm{jets} = 0$, $\xi_Z < 0.5$). The associated measured central values, statistical uncertainty magnitude and bin ranges are presented in Tables 1-4. The bins are presented in order such that for example mjj_bin_1 spans $m_{jj} \in (1000,1500)$ GeV (see Table 1), while pT_ll_bin7 spans $p_\mathrm{T}^{ll} \in (200,275)$ GeV (see Table 3).

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.

Measured differential fiducial cross sections in cos(theta*) (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in number of jets (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in transverse momentum of the leading jet (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in dijet invariant mass (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in dijet angle phi (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in m12 vs m34 (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in Higgs transverse momentum for 0 jet events (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in Higgs transverse momentum for 1-jet events (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in Higgs transverse momentum for events with 2 or more jets (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in dijet angle eta (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in invariant mass of the leading lepton pair (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in number of bjets (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured fiducial cross sections (second column). The given uncertainty is split into statistical (first) and systematic components (second). The third column gives the theoretical prediction of Higgs production in the fiducial volume using the best available inclusive Higgs production cross sections at the time of the publication. The acceptance to estimate the cross section in the fiducial volume is calculated using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty.