The normalized distributions of the BDT input variable $D_{p_{\text{T}}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized BDT discriminator distribution for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models.

The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.

The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.

The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.

The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.

The $m_{\text{T}}$ distribution for the high-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{3}(x) = \exp(p_{1}x)x^{p_{2}(1+p_{3}\ln(x))}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.

The $m_{\text{T}}$ distribution for the low-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.

The $m_{\text{T}}$ distribution for the high-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.

The $m_{\text{T}}$ distribution for the low-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.

The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.

The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.

The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.

The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.

The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.

The 95% CL upper limits on the product of the cross section and branching fraction from the inclusive search for the $\alpha_{\text{dark}}$ variations.

The 95% CL upper limits on the product of the cross section and branching fraction from the BDT-based search for the $\alpha_{\text{dark}}$ variations.

The three two-dimensional signal model parameter scans.

Metrics representing the performance of the BDT for the benchmark signal model ($m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$), compared to each of the major SM background processes.

The range of effects on the signal yield for each systematic uncertainty and the total. Values less than 0.01% are rounded to 0.0%.

The normalized distribution of the variable $m_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.

The normalized distribution of the variable $\Delta\eta(\text{J}_{1},\text{J}_{2})$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.

The normalized distribution of the variable $p_{\text{T}}^{\text{miss}}$ for the simulated SM backgrounds and several signal models. The $R_{\text{T}}$ requirement is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.

The normalized distribution of the variable $N_{\text{e}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.

The normalized distribution of the variable $N_{\mu}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.

The normalized distribution of $\Delta\eta(\text{J}_{1},\text{J}_{2})$ vs. $R_{\text{T}}$ for the simulated QCD background. The preselection requirements on both variables are omitted, but all other preselection requirements are applied.

The normalized distribution of $p_{\text{T}}^{\text{miss}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.

The normalized distribution of $R_{\text{T}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.

The normalized distributions of the BDT input variable $\tau_{21}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized distributions of the BDT input variable $\tau_{32}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized distributions of the BDT input variable $N_{2}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized distributions of the BDT input variable $N_{3}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized distributions of the BDT input variable $g_{\text{jet}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized distributions of the BDT input variable $\sigma_{\text{major}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized distributions of the BDT input variable $\sigma_{\text{minor}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized distributions of the BDT input variable $\Delta\phi(\vec{J},\vec{p}_{\text{T}}^{\text{miss}})$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized distributions of the BDT input variable $f_{\text{h}^{\pm}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized distributions of the BDT input variable $f_{\text{e}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized distributions of the BDT input variable $f_{\mu}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized distributions of the BDT input variable $f_{\text{h}^{0}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The normalized distributions of the BDT input variable $f_{\gamma}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.

The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.

The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.

The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.

The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.

The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.

The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.

The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.

The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.

The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.

The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.

The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.

The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.

Comparison of different the dijet mass $m_{\text{J}\text{J}}$, the transverse mass $m_{\text{T}}$, and the Monte Carlo (MC) mass $m_{\text{MC}}$ for a signal model with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. No selection is applied, except that there must be at least two jets. $m_{\text{MC}}$ is computed by adding the generator-level four-vectors for invisible particles to the dijet system, to represent the achievable resolution if the invisible component were fully measured. The last bin of each histogram includes the overflow events.

$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.

$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.

$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the high-$R_{\text{T}}$ inclusive signal region.

$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the low-$R_{\text{T}}$ inclusive signal region.

$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.

$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.

The proportions of each SM background process in the high-$R_{\text{T}}$ signal region.

The proportions of each SM background process in the low-$R_{\text{T}}$ signal region.

The proportions of each SM background process in the high-SVJ2 signal region.

The proportions of each SM background process in the low-SVJ2 signal region.

The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.

The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.

The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.

The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.

Relative efficiencies in % for each step of the event selection process for the major background processes. Statistical uncertainties, at most 1.8%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.

Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.5%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.

Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.

Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.

Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 2.6%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.

Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 1.2%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.

Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.9%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.

Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.

Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.

Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.

Distribution of $m_{\mathrm{jjj}}$ for preselected events with $\mathrm{N}_{j}$ = 3

Distribution of $m_{\mathrm{j}}$ for preselected events with $\mathrm{N}_{j}$ = 3

Distribution of the deep-WH value of the highest-mass jet with 60 < $m_{\mathrm{j}}$ < 100 GeV for preselected events with $\mathrm{N}_{j}$ = 3

scale factors (SFs) for W, $t^{2}$, and q/g matched jets in the low-$m_{\mathrm{j}}$ and low-$p_{\mathrm{T}}$ (LL) bin, as functions of the deep-W discriminant value.

scale factors (SFs) for W, $t^{2}$, and q/g matched jets in the low-$m_{\mathrm{j}}$ and high-$p_{\mathrm{T}}$ (LH) bin, as functions of the deep-W discriminant value.

scale factors (SFs) for $t^{2}$, $t^{3,4}$, and q/g matched jets in the high-$m_{\mathrm{j}}$ and low-$p_{\mathrm{T}}$ (HL) bin, as functions of the deep-WH discriminant value.

scale factors (SFs) for $t^{2}$, $t^{3,4}$, and q/g matched jets in the high-$m_{\mathrm{j}}$ and high-$p_{\mathrm{T}}$ (HH) bin, as functions of the deep-WH discriminant value.

The deep-W discriminant of the jet with highest mass in the single-lepton sideband for LL samples.

The deep-W discriminant of the jet with highest mass in the single-lepton sideband for LH samples.

The deep-WH discriminant of the jet with highest mass in the single-lepton sideband for HL samples.

The deep-WH discriminant of the jet with highest mass in the single-lepton sideband for HH samples.

Comparison of the distribution of data and simulated backgrounds, as a function of the deep-W discriminant value for the highest-mass jet in CR1, after the scale factors have been applied.

Comparison of the distribution of data and simulated backgrounds, as a function of the deep-WH discriminant value for the highest-mass jet in CR2, after the scale factors have been applied.

Comparison of the distribution of data and simulated backgrounds, as a function of the deep-WH discriminant value for the highest-mass jet in CR3, after the scale factors have been applied.

Comparison of the distribution of data and simulated backgrounds, as a function of the deep-W discriminant value for the highest-mass jet in CR45, after the scale factors have been applied.

Comparison of the distribution of data and simulated backgrounds, as a function of the deep-W discriminant value for the highest-mass jet in CR6, after the scale factors have been applied.

The $m_{\mathrm{j}^{\mathrm{max}}}$ distributions for different jet types for SR1–3 events of the signal with $m_{\mathrm{W}_{\mathrm{KK}}}$ = 2.5 TeV, $m_{\mathrm{R}}$ = 0.2 TeV$ without deep-W (WH) constraints.

The deep-W distribution normalized to unity for the shown components of of the signal with $m_{\mathrm{W}_{\mathrm{KK}}}$ = 2.5 TeV, $m_{\mathrm{R}}$ = 0.2 TeV. The $t^{3,4}$ jets from the preselected sample, normalized to unity, are superimposed to compare shapes with the $R^{3q}$ and $R^{4q}$ distributions.

The deep-WH distribution normalized to unity for the shown components of of the signal with $m_{\mathrm{W}_{\mathrm{KK}}}$ = 2.5 TeV, $m_{\mathrm{R}}$ = 0.2 TeV. The $t^{3,4}$ jets from the preselected sample, normalized to unity, are superimposed to compare shapes with the $R^{3q}$ and $R^{4q}$ distributions.

The $m_{\mathrm{jj}}$ distribution for CR1 for data and simulation.

The $m_{\mathrm{jj}}$ distribution for CR2 for data and simulation.

The $m_{\mathrm{jj}}$ distribution for CR3 for data and simulation.

The $m_{\mathrm{jjj}}$ distribution for CR45 for data and simulation.

The $m_{\mathrm{jjj}}$ distribution for CR6 for data and simulation.

Post-fit distributions of the reconstructed triboson system ($m_{\mathrm{jj}}$) in data and simulation for SR1.

Post-fit distributions of the reconstructed triboson system ($m_{\mathrm{jj}}$) in data and simulation for SR2.

Post-fit distributions of the reconstructed triboson system ($m_{\mathrm{jj}}$) in data and simulation for SR3.

Post-fit distributions of the reconstructed triboson system ($m_{\mathrm{jjj}}$) in data and simulation for SR4.

Post-fit distributions of the reconstructed triboson system ($m_{\mathrm{jjj}}$) in data and simulation for SR5.

Post-fit distributions of the reconstructed triboson system ($m_{\mathrm{jjj}}$) in data and simulation for SR6.

Observed upper limits at $95\%$ CL on the signal cross section $\times$ branching fraction as functions of the $m_{\mathrm{W}_{\mathrm{KK}}}$ and $m_{\mathrm{R}}$ resonance masses.

Expected median lower limit contour on the $m_{\mathrm{W}_{\mathrm{KK}}}$ and $m_{\mathrm{R}}$ plane.

Expected $+ 1$ s.d. lower limit contour on the $m_{\mathrm{W}_{\mathrm{KK}}}$ and $m_{\mathrm{R}}$ plane.

Expected - 1 s.d. lower limit contour on the $m_{\mathrm{W}_{\mathrm{KK}}}$ and $m_{\mathrm{R}}$ plane.

Observed lower limit contour on the $m_{\mathrm{W}_{\mathrm{KK}}}$ and $m_{\mathrm{R}}$ plane.

Measured inclusive fiducial $tt\gamma$ production cross section in the dilepton final state for the different dilepton-flavour channels and combined.

Absolute differential $tt\gamma$ production cross section as a function of $p_{T}(\gamma)$ . The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $|\eta |(\gamma)$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of min $\Delta R(\gamma, \ell)$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $\Delta R(\gamma, \ell_{1})$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $\Delta R(\gamma, \ell_{2})$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of min $\Delta R(\gamma, b)$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $|\Delta\eta(\ell\ell)|$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $\Delta \phi(\ell\ell)$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $p_{T}(\ell\ell) $. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $p_{T}(\ell_{1})+p_{T}(\ell_{2})$ . The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of min $\Delta R(\ell, j)$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $p_{T}(j_{1})$ .

Normalized differential $tt\gamma$ production cross section as a function of $p_{T}(\gamma)$ . The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $|\eta |(\gamma)$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of min $\Delta R(\gamma, \ell)$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $\Delta R(\gamma, \ell_{1})$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $\Delta R(\gamma, \ell_{2})$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of min $\Delta R(\gamma, b)$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $|\Delta\eta(\ell\ell)|$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $\Delta \phi(\ell\ell)$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $p_{T}(\ell\ell) $. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $p_{T}(\ell_{1})+p_{T}(\ell_{2})$ . The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of min $\Delta R(\ell, j)$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $p_{T}(j_{1})$ . The values provided in the table are not divided by the bin width.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $p_{T}(\gamma)$ .

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $p_{T}(\gamma)$ .

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $|\eta |(\gamma)$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $|\eta |(\gamma)$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of min $\Delta R(\gamma, \ell)$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of min $\Delta R(\gamma, \ell)$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $\Delta R(\gamma, \ell_{1})$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $\Delta R(\gamma, \ell_{1})$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $\Delta R(\gamma, \ell_{2})$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $\Delta R(\gamma, \ell_{2})$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of min $\Delta R(\gamma, b)$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of min $\Delta R(\gamma, b)$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $|\Delta\eta(\ell\ell)|$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $|\Delta\eta(\ell\ell)|$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $\Delta \phi(\ell\ell)$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $\Delta \phi(\ell\ell)$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $p_{T}(\ell\ell) $.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $p_{T}(\ell\ell) $.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $p_{T}(\ell_{1})+p_{T}(\ell_{2})$ .

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $p_{T}(\ell_{1})+p_{T}(\ell_{2})$ .

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of min $\Delta R(\ell, j)$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of min $\Delta R(\ell, j)$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $p_{T}(j_{1})$ .

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $p_{T}(j_{1})$ .

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c_{tZ}$, using the photon pT distribution from the dilepton analysis. The value of $c^{I}_{tZ}$ is fixed to zero in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c_{tZ}$, using the combination of photon pT distributions from the dilepton and lepton+jets analyses. The value of $c^{I}_{tZ}$ is fixed to zero in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c^{I}_{tZ}$, using the photon pT distribution from the dilepton analysis. The value of $c_{tZ}$ is fixed to zero in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c^{I}_{tZ}$, using the combination of photon pT distributions from the dilepton and lepton+jets analyses. The value of $c_{tZ}$ is fixed to zero in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c_{tZ}$, using the photon pT distribution from the dilepton analysis. The value of $c^{I}_{tZ}$ is profiled in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c_{tZ}$, using the combination of photon pT distributions from the dilepton and lepton+jets analyses. The value of $c^{I}_{tZ}$ is profiled in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c^{I}_{tZ}$, using the photon pT distribution from the dilepton analysis. The value of $c_{tZ}$ is profiled in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c^{I}_{tZ}$, using the combination of photon pT distributions from the dilepton and lepton+jets analyses. The value of $c_{tZ}$ is profiled in the fit.

Negative log-likelihood difference from the best-fit value as a function of Wilson coefficients $c_{tZ}$ and $c^{I}_{tZ}$ from the interpretation of the dilepton measurement.

Negative log-likelihood difference from the best-fit value as a function of Wilson coefficients $c_{tZ}$ and $c^{I}_{tZ}$ from the interpretation of the dilepton and lepton+jets measurements combined.

One-dimensional 68 and 95% CL intervals obtained for the Wilson coefficients $c_{tZ}$ and $c^{I}_{tZ}$, using the photon $p_{T}$ distribution from the dilepton analysis, or the combination of photon pT distributions from the dilepton and lepton+jets analyses.

Comparison of observed $95\%$ CL intervals for the Wilson coefficients $c_{tZ}$ and $c^{I}_{tZ}$. Results are shown from a CMS ttZ measurement [JHEP 03 (2020) 056], from a CMS ttZ & tZq interpretation [arXiv:2107.13896], from a CMS ttG (lepton+jets) measurement [arXiv:2107.01508], from this measurement, and from a global fit by J. Ellis et al. [JHEP 04 (2021) 279].

Expected event yields in each $m_{jj}$ bin for the different background processes in the SR of the VTR category, in the 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR. The expected signal contributions for a Higgs boson, produced in the non-VBF and VBF modes, decaying to invisible particles with a branching fraction of $\mathcal{B}(\text{H} \to \text{inv}) = 1$, and the observed event yields are also reported.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for MTR, 2017, signal region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for MTR, 2017, dimuon region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for MTR, 2018, signal region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for MTR, 2018, dimuon region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for VTR, 2017, signal region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for VTR, 2017, dimuon region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for VTR, 2018, signal region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for VTR, 2018, single electron region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for VTR, 2018, dielectron region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for VTR, 2018, dimuon region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for MTR, 2017, photon region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for MTR, 2018, photon region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for MTR, 2017, single electron region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for MTR, 2017, single muon region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for MTR, 2017, dielectron region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for MTR, 2018, single electron region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for MTR, 2018, single muon region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for MTR, 2018, dielectron region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for VTR, 2017, single electron region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for VTR, 2017, single muon region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for VTR, 2017, dielectron region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Event yields for the postfit background model from the background-only and signal-plus-background fits, as well as the observed event yields for VTR, 2018, single muon region. All signal and control regions from the 2017 and 2018 data sets are included in the fit.

Trigger efficiency measured as a function of $p_{T}^{miss}$ in data for the 2017 and 2018 samples for the MTR category. The efficiency is measured in a phase space with at least two jets in which the leading (trailing) jet has $p_{T}>80~\text{GeV}$ ($>40~\text{GeV}$). The two jets are required to form a system with $m_{jj}>200~\text{GeV}$ and $\Delta\Phi_{jj}<1.5$.

Trigger efficiency measured as a function of $p_{T}^{miss}$ in data for the 2017 and 2018 samples for the MTR category. The efficiency is measured in a phase space with at least two jets in which the leading (trailing) jet has $p_{T}>140~\text{GeV}$ ($>70~\text{GeV}$). The two jets are required to form a system with $m_{jj}>900~\text{GeV}$ and $\Delta\Phi_{jj}<1.8$.

GGsm vs -2dNLL (f_{#Lambda1} (u) observed)

GGsm vs -2dNLL (SM-like (f_{ai}=0) expected)

GGsm vs -2dNLL (f_{a2} (u) expected)

GGsm vs -2dNLL (f_{a3} (u) expected)

GGsm vs -2dNLL (f_{#Lambda1} (u) expected)

GGsm vs -2dNLL (2l2#nu off-shell + 4l on-shell observed)

GGsm vs -2dNLL (4l off-shell + 4l on-shell observed)

GGsm vs -2dNLL (2l2#nu off-shell + 4l on-shell expected)

GGsm vs -2dNLL (4l off-shell + 4l on-shell expected)

r_offshell vs -2dNLL (R_{V,F}^{off-shell}=1 observed)

r_offshell vs -2dNLL (R_{V,F}^{off-shell} (u) observed)

r_offshell vs -2dNLL (R_{V,F}^{off-shell}=1 (2l2#nu) observed)

r_offshell vs -2dNLL (R_{V,F}^{off-shell} (u, 2l2#nu) observed)

r_offshell vs -2dNLL (R_{V,F}^{off-shell}=1 expected)

r_offshell vs -2dNLL (R_{V,F}^{off-shell} (u) expected)

r_offshell vs -2dNLL (R_{V,F}^{off-shell}=1 (2l2#nu) expected)

r_offshell vs -2dNLL (R_{V,F}^{off-shell} (u, 2l2#nu) expected)

rf_offshell vs -2dNLL (2l2#nu+4l observed)

rf_offshell vs -2dNLL (Only 2l2#nu observed)

rf_offshell vs -2dNLL (2l2#nu+4l expected)

rf_offshell vs -2dNLL (Only 2l2#nu expected)

rv_offshell vs -2dNLL (2l2#nu+4l observed)

rv_offshell vs -2dNLL (Only 2l2#nu observed)

rv_offshell vs -2dNLL (2l2#nu+4l expected)

rv_offshell vs -2dNLL (Only 2l2#nu expected)

rf_offshell vs rv_offshell observed

fa2 vs -2dNLL (#Gamma_{H}=4.1 MeV observed)

fa2 vs -2dNLL (#Gamma_{H} (u) observed)

fa2 vs -2dNLL (On-shell 4l observed)

fa2 vs -2dNLL (#Gamma_{H}=4.1 MeV expected)

fa2 vs -2dNLL (#Gamma_{H} (u) expected)

fa2 vs -2dNLL (On-shell 4l expected)

fa3 vs -2dNLL (#Gamma_{H}=4.1 MeV observed)

fa3 vs -2dNLL (#Gamma_{H} (u) observed)

fa3 vs -2dNLL (On-shell 4l observed)

fa3 vs -2dNLL (#Gamma_{H}=4.1 MeV expected)

fa3 vs -2dNLL (#Gamma_{H} (u) expected)

fa3 vs -2dNLL (On-shell 4l expected)

fL1 vs -2dNLL (#Gamma_{H}=4.1 MeV observed)

fL1 vs -2dNLL (#Gamma_{H} (u) observed)

fL1 vs -2dNLL (On-shell 4l observed)

fL1 vs -2dNLL (#Gamma_{H}=4.1 MeV expected)

fL1 vs -2dNLL (#Gamma_{H} (u) expected)

fL1 vs -2dNLL (On-shell 4l expected)

The fraction of photon-induced background as compared with the total amount of DY signal plus photon-induced events ($N_{\gamma\gamma}/(N_{\gamma\gamma} + N_\mathrm{DY})$) in different dilepton mass bins. These numbers are averaged across the different years and channels.

Exclusion limits at 95% CL on the coupling K_L for a Z' in the sequential standard model as a function of the Z' mass.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 40 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 45 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 50 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 55 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 60 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 65 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 70 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 75 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 80 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 85 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 90 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 95 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of X$\to\phi\phi\to$4b, with $m_\phi$ = 100 GeV. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_XN/f$.

Data event yields and predicted signal and background yields (including subdominant $t\bar{t}$) in bins of dijet and average jet mass.

The 95% confidence level expected and observed upper limits on $\sigma$(pp->X->YH->4b) for different values of $M_X$ and $M_Y$. The areas within the red and black contours represent the regions where the cross sections predicted by NMSSM and TRSM, respectively, are larger than the experimental limits. The areas within the dashed and dotted contours on the left show the excluded masses at -1 standard deviation from the expected limits.

Measurements of the signal strengths $\mu_{\text{s}}$ in the STXS stage-1.2 bins for the ggH, qqH, and VH processes, for the combination of the CB- and VH-analyses. Central values and a split of uncertainties are also provided with each result.

Correlation matrix of the POIs of the measured STXS stage-1.2 signal strengths for the combination of the NN- an VH-analyses.

Correlation matrix of the POIs of the measured STXS stage-1.2 signal strengths for the combination of the CB- an VH-analyses.

Cross section measurements in the STXS stage-0 bins for the combination of the NN- and VH-analyses. Central values and combined statistical and systematic uncertainties are given for each measurement.

Cross section measurements in the STXS stage-1.2 bins for the combination of the NN- and VH-analyses. Central values and combined statistical and systematic uncertainties are given for each measurement.

Cross section measurements in the STXS stage-0 bins for the combination of the CB- and VH-analyses. Central values and combined statistical and systematic uncertainties are given for each measurement.

Cross section measurements in the STXS stage-1.2 bins for the combination of the CB- and VH-analyses. Central values and combined statistical and systematic uncertainties are given for each measurement.