The distribution of the $p_\mathrm{T}{}_{\mu\mathrm{-had}}^\mathrm{col}$ in the VR. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top-quark, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic sources.

The distributions of $m_{\mu\mathrm{-had}}^\mathrm{col}$ corresponding to the SR selection criteria defined in the text. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top-quark, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic sources.

The distributions of $m_{\mu\mathrm{-had}}^\mathrm{col}$ corresponding to the SR_\text{std} selection criteria defined in the text. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top-quark, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic sources.

The distributions of $m_{\mu\mathrm{-had}}^\mathrm{col}$ corresponding to the SR_\text{tight} selection criteria defined in the text. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top-quark, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic sources.

The distributions of $m_{\mu\mathrm{-had}}^\mathrm{col}$ corresponding to the SR_\text{tight}^\text{std} selection criteria defined in the text. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top-quark, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic sources.

The distribution of $\Delta\phi^\mathrm{signed}_{\mu-MET}$ with all other event selection criteria applied in the SR; the straight lines indicate the positions of the selection requirements. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of $\Delta\phi^\mathrm{signed}_{\mu-MET}$ with all other event selection criteria applied in the VR; the straight lines indicate the positions of the selection requirements. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of the $m_{\mu\mathrm{-had}}^\mathrm{col}$ in the SR. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of the $m_{\mu\mathrm{-had}}^\mathrm{col}$ in the VR. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of the $p_\mathrm{T}$ of the $\tau_\mathrm{had}^{\mu\mkern-10mu\backslash}$ in the SR. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of the $p_\mathrm{T}$ of the $\tau_\mathrm{had}^{\mu\mkern-10mu\backslash}$ in the VR. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of the $p_\mathrm{T}$ of the muon removed from the $\tau_\mathrm{had}^{\mu\mkern-10mu\backslash}$ in the SR `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of the $p_\mathrm{T}$ of the muon removed from the $\tau_\mathrm{had}^{\mu\mkern-10mu\backslash}$ in the VR `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of the $p_\mathrm{T}$ of the leading jet in the SR. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of the $p_\mathrm{T}$ of the leading jet in the VR. `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of the $\Delta{R}_{\tau\tau}^\mathrm{reco}$ between the muon and the $\tau_\mathrm{had}^{\mu\mkern-10mu\backslash}$ in the SR `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of the $\Delta{R}_{\tau\tau}^\mathrm{reco}$ between the muon and the $\tau_\mathrm{had}^{\mu\mkern-10mu\backslash}$ in the VR `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of the reconstructed $E_\mathrm{T}^\mathrm{miss}$ in the SR `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The distribution of the reconstructed $E_\mathrm{T}^\mathrm{miss}$ in the VR `$Z(\rightarrow\tau\tau)+\text{jets}$' represents the contributions from the signal process. `Diboson' indicates the contributions from $WW$, $WZ$, and $ZZ$ processes. `Top' represents the predicted contributions from the $t\bar{t}$, single-top, and $tW$ processes. `Other' includes the contributions from the $Z(\rightarrow\ell\ell)$+jets, $W$+jets, and Higgs boson processes. The uncertainties shown include both statistical and systematic errors.

The observed 95% CL exclusion limits as a function of κ_2V (obtained using the signal strength μ_VBF as the POI) from the combined ggF and VBF signal regions, as shown by the solid black line. The value of κ_λ is fixed to 1. The blue and yellow bands show respectively the 1σ and 2σ bands around the expected exclusion limits, which are shown by the dashed black line. The expected exclusion limits are obtained using a fit to the data with the background-only hypothesis. The dark red line shows in the predicted VBF HH cross-section as a function of κ_2V.

The observed 95% CL exclusion limit obtained using the signal strength μ_ggF+VBF as the POI in the two-dimensional κ_λ vs. κ_2V space, obtained from the combined ggF and VBF signal model, as shown by the solid black line. The blue and yellow bands show respectively the 1σ and 2σ bands around the expected exclusion limits, which are shown by the dashed black line. The star denotes the SM prediction (κ_λ=κ_2V=1). The displayed values are in units of $\mu_{ggF}$.

The expected and observed profile likelihood ratio scans for κ_λ coupling modifier, shown by the solid black line, using the coupling modifier as the POIs. The value of κ_2V is fixed to 1. The dashed blue line shows the expected profile likelihood ratio, as obtained using a fit to the data with the background-only hypothesis. The pink line indicates the 2σ exclusion boundary.

The expected and observed profile likelihood ratio scans for the κ_2V coupling modifier, shown by the solid black line, using the coupling modifier as the POIs. The value of κ_λ is fixed to 1. The dashed blue line shows the expected profile likelihood ratio, as obtained using a fit to the data with the background-only hypothesis. The pink line indicates the 2σ exclusion boundary.

The observed profile likelihood ratio exclusion limits for the two-dimensional κ_λ vs. κ_2V modifier space, shown by the solid dark purple line at the 1σ level and the dashed turquoise line at the 2σ level. The black cross denotes the best-fit values of (κ_λ,κ_2V). For both the expected and observed limit plots, the black star indicates the SM prediction (κ_λ=κ_2V=1).

The expected profile likelihood ratio exclusion limits for the two-dimensional κ_λ vs. κ_2V modifier space, where the solid pink line denotes the 1σ-level exclusion and the dashed orange line denotes the 2σ-level exclusion. The black cross denotes the best-fit values of (κ_λ,κ_2V). For both the expected and observed limit plots, the black star indicates the SM prediction (κ_λ=κ_2V=1).

The observed 95% CL exclusion limits on the SMEFT coefficients in the two-dimensional spaces c_{H G} vs. c_H shown by the solid black lines. The displayed values are in units of $\mu_{ggF}$. The dashed black line indicates the expected 95% CL exclusion limits. The shaded blue band indicates the ± 1σ uncertainty of the exclusion limits, while the yellow band indicates the ± 2σ uncertainty. The values of the other three coefficients for each plot are fixed to 0. The VBF HH process is ignored for this result.

The observed 95% CL exclusion limits on the SMEFT coefficients in the two-dimensional spaces c_tG vs. c_H shown by the solid black lines. The displayed values are in units of $\mu_{ggF}$. The dashed black line indicates the expected 95% CL exclusion limits. The shaded blue band indicates the ± 1σ uncertainty of the exclusion limits, while the yellow band indicates the ± 2σ uncertainty. The values of the other three coefficients for each plot are fixed to 0. The VBF HH process is ignored for this result.

The observed 95% CL exclusion limits on the SMEFT coefficients in the two-dimensional spaces c_{t H} vs. c_H shown by the solid black lines. The displayed values are in units of $\mu_{ggF}$. The dashed black line indicates the expected 95% CL exclusion limits. The shaded blue band indicates the ± 1σ uncertainty of the exclusion limits, while the yellow band indicates the ± 2σ uncertainty. The values of the other three coefficients for each plot are fixed to 0. The VBF HH process is ignored for this result.

The observed 95% CL exclusion limits on the SMEFT coefficients in the two-dimensional spaces c_H□ vs. c_H shown by the solid black lines. The displayed values are in units of $\mu_{ggF}$. The dashed black line indicates the expected 95% CL exclusion limits. The shaded blue band indicates the ± 1σ uncertainty of the exclusion limits, while the yellow band indicates the ± 2σ uncertainty. The values of the other three coefficients for each plot are fixed to 0. The VBF HH process is ignored for this result.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2016 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2016 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2016 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2016 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2016 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2016 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2017 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2017 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2017 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2017 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2017 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2017 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2018 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2018 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2018 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2018 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2018 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

Distributions of the reconstructed m_HH in data (shown by the black points) and the estimated background (shown by the yellow histograms), in each of the six |Δη_HH|/X_HH categories in the ggF signal region, for the 2018 data. The hatching shows the total uncertainty on the background estimate. The distribution of the expected background is obtained using the best-fit values of the nuisance parameters in the background-only fit to the data. Distributions of the SM and κ_λ= 6 signal models are overlaid, scaled so as to be visible on the plot, and the scaling for each signal model is the same across the six categories. The lower panels show the ratio of the observed data yield to the predicted background in each bin. Events in the underflow and overflow bins are counted in the yields of the initial and final bins respectively. In the HEPData entry, the raw value per histogram bin is provided, while in the published paper the values in the histogram are scaled by the bin width.

The observed 95% CL exclusion limits as a function of the five relevant SMEFT coefficients: (a) c_H, (b) c_{H G}, (c) c_H□, (d) c_tH, and (e) c_tG, obtained from the combined ggF signal model, as shown by the solid black line. The values of the other four coefficients are fixed to 0. The blue and yellow bands show the 1σ and 2σ bands respectively on the expected exclusion limits, which are shown by the dashed black line. The red line shows the predicted ggF HH cross-section as a function of the coefficient. The VBF HH process is ignored for this result.

The observed 95% CL exclusion limits as a function of the five relevant SMEFT coefficients: (a) c_H, (b) c_{H G}, (c) c_H□, (d) c_tH, and (e) c_tG, obtained from the combined ggF signal model, as shown by the solid black line. The values of the other four coefficients are fixed to 0. The blue and yellow bands show the 1σ and 2σ bands respectively on the expected exclusion limits, which are shown by the dashed black line. The red line shows the predicted ggF HH cross-section as a function of the coefficient. The VBF HH process is ignored for this result.

The observed 95% CL exclusion limits as a function of the five relevant SMEFT coefficients: (a) c_H, (b) c_{H G}, (c) c_H□, (d) c_tH, and (e) c_tG, obtained from the combined ggF signal model, as shown by the solid black line. The values of the other four coefficients are fixed to 0. The blue and yellow bands show the 1σ and 2σ bands respectively on the expected exclusion limits, which are shown by the dashed black line. The red line shows the predicted ggF HH cross-section as a function of the coefficient. The VBF HH process is ignored for this result.

The observed 95% CL exclusion limits as a function of the five relevant SMEFT coefficients: (a) c_H, (b) c_{H G}, (c) c_H□, (d) c_tH, and (e) c_tG, obtained from the combined ggF signal model, as shown by the solid black line. The values of the other four coefficients are fixed to 0. The blue and yellow bands show the 1σ and 2σ bands respectively on the expected exclusion limits, which are shown by the dashed black line. The red line shows the predicted ggF HH cross-section as a function of the coefficient. The VBF HH process is ignored for this result.

The observed 95% CL exclusion limits as a function of the five relevant SMEFT coefficients: (a) c_H, (b) c_{H G}, (c) c_H□, (d) c_tH, and (e) c_tG, obtained from the combined ggF signal model, as shown by the solid black line. The values of the other four coefficients are fixed to 0. The blue and yellow bands show the 1σ and 2σ bands respectively on the expected exclusion limits, which are shown by the dashed black line. The red line shows the predicted ggF HH cross-section as a function of the coefficient. The VBF HH process is ignored for this result.

The observed 95% CL exclusion limits as a function of the two relevant HH HEFT coefficients: (a) c_tt̄HH and (b) c_ggHH, obtained from the combined ggF signal model, as shown by the solid black line. The values of the other four coefficients are fixed to 0. The blue and yellow bands show the 1σ and 2σ bands respectively on the expected exclusion limits, which are shown by the dashed black line. The red line shows the predicted ggF HH cross-section as a function of the coefficient. The VBF HH process is ignored for this result.

The observed 95% CL exclusion limits as a function of the two relevant HH HEFT coefficients: (a) c_tt̄HH and (b) c_ggHH, obtained from the combined ggF signal model, as shown by the solid black line. The values of the other four coefficients are fixed to 0. The blue and yellow bands show the 1σ and 2σ bands respectively on the expected exclusion limits, which are shown by the dashed black line. The red line shows the predicted ggF HH cross-section as a function of the coefficient. The VBF HH process is ignored for this result.

Data from Figure 1, panel c, $k_{2}$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 1, panel c, $k_{2}$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 1, panel d, $k_{3}$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 1, panel d, $k_{3}$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 2, panel a, $N_{ch}k_{2}$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 2, panel a, $N_{ch}k_{2}$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 2, panel b, $N^{2}_{ch}k_{3}$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 2, panel b, $N^{2}_{ch}k_{3}$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 2, panel c, $\Gamma$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 2, panel c, $\Gamma$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel a, $\left\langle[p_{T}]\right\rangle / \left\langle[p_{T}]\right\rangle^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel a, $\left\langle[p_{T}]\right\rangle / \left\langle[p_{T}]\right\rangle^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel b, $k_{2}/k^{5\%}_{2} vs N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel b, $k_{2}/k^{5\%}_{2} vs N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel c, $k_{3}/k^{5\%}_{3} vs N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel c, $k_{3}/k^{5\%}_{3} vs N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel d, $\Gamma/\Gamma^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel d, $\Gamma/\Gamma^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-1\%}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-1\%}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-1\%}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 2 GeV/c, $|\eta|< $ 2.5

Data from Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-1\%}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 2 GeV/c, $|\eta|< $ 2.5

Data from Second Supplementary Figure, Fig 6, panel a, Correlation between FCal $\Sigma E_{T}$ and $N_{ch}$ in Pb+Pb collisions

Data from Second Supplementary Figure, Fig 6, panel b, Correlation between $[p_{T}]$ - $\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}$/$\left\langle N_{ch}\right\rangle_{0-1\%}$ in Pb+Pb collisions

Data from Third Supplementary Figure, Fig 7, Normalized Event distribution of $N_{ch}$ /$N^{5\%}_{ch}$ for Pb+Pb collisions

Data from Third Supplementary Figure, Fig 7, Normalized Event distribution of $N_{ch}$ / $N^{5\%}_{ch}$ for Xe+Xe collisions

Data from Fourth Supplementary Figure, Fig 8, panel a, $\gamma$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Fourth Supplementary Figure, Fig 8, panel a, $\gamma$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Fourth Supplementary Figure, Fig 8, panel b, $\gamma/\gamma^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Fourth Supplementary Figure, Fig 8, panel b, $\gamma/\gamma^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Auxiliary Fig 1 panel a, Correlation between FCal $\Sigma E_{T}$ and $N_{ch}$ in Xe+Xe collisions

Data from Auxiliary Fig 1 panel b, Correlation between $[p_{T}]$ - $\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}$/$\left\langle N_{ch}\right\rangle_{0-1\%}$ in Xe+Xe collisions

Data from Auxiliary Fig 2 panel b, $N_{ch}$ /$N^{5\%}_{ch}$ vs Centrality [\%] for Pb+Pb collisions

Data from Auxiliary Fig 2 panel b, $N_{ch}$ /$N^{5\%}_{ch}$ vs Centrality [\%] for Xe+Xe collisions

Data from Auxiliary Fig 3 panel b, $[p_{T}]$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Auxiliary Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-0.5\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-0.5\%}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Auxiliary Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-0.5\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-0.5\%}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Auxiliary Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-0.5\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-0.5\%}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 2 GeV/c, $|\eta|< $ 2.5

Data from Auxiliary Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-0.5\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-0.5\%}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 2 GeV/c, $|\eta|< $ 2.5

Breakdown of relative systematic uncertainties in the measured ${t\bar{t}}$ cross-section. The quoted uncertainties are obtained by repeating the fit with a group of nuisance parameters fixed to their fitted values and subtracting in quadrature the resulting total uncertainty from the uncertainty of the complete fit. However, the total uncertainty is not the quadratic sum of the grouped impacts, as this approach neglects the correlation among the different groups.

The figure shows the measurement of the top quark pair production cross-section, $\sigma_{t\bar{t}}$, in lead-lead (Pb+Pb) collisions at a center-of-mass energy of $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV, based on 1.9 nb$^{-1}$ of data.

The measured $p_\text{T}^\text{recoil}$ differential cross-sections in the $2\mu+\text{jets}$ region of the incluse jet phase space, compared with the SM predictions. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $p_\text{T}^\text{recoil}$ differential cross-sections in the $2e+\text{jets}$ region of the incluse jet phase space, compared with the SM predictions. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $p_\text{T}^\text{recoil}$ in the inclusive jet phase space for $1\mu+\text{jets}$. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $p_\text{T}^\text{recoil}$ in the inclusive jet phase space for $1e+\text{jets}$. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $p_\text{T}^\text{recoil}$ in the inclusive jet phase space for $2\mu+\text{jets}$. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $p_\text{T}^\text{recoil}$ in the inclusive jet phase space for $2e+\text{jets}$. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $p_\text{T}^\text{miss}$ differential cross-sections in the $p_\text{T}^\text{miss}+\text{jets}$ region of the VBF phase spaces, compared with the SM predictions. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $p_\text{T}^\text{recoil}$ differential cross-sections in the $1\mu+\text{jets}$ region of the VBF phase space, compared with the SM predictions. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $p_\text{T}^\text{recoil}$ differential cross-sections in the $1e+\text{jets}$ region of the VBF phase space, compared with the SM predictions. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $p_\text{T}^\text{recoil}$ differential cross-sections in the $2\mu+\text{jets}$ region of the VBF phase space, compared with the SM predictions. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $p_\text{T}^\text{recoil}$ differential cross-sections in the $2e+\text{jets}$ region of the VBF phase space, compared with the SM predictions. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $p_\text{T}^\text{recoil}$ in the VBF phase space for $1\mu+\text{jets}$. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $p_\text{T}^\text{recoil}$ in the VBF phase space for $1e+\text{jets}$. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $p_\text{T}^\text{recoil}$ in the VBF phase space for $2\mu+\text{jets}$. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $p_\text{T}^\text{recoil}$ in the VBF phase space for $2e+\text{jets}$. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $m_{jj}$ distribution in the VBF phase space compared with the SM predictions, for the $p_\text{T}^\text{miss}+\text{jets}$ region. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $m_{jj}$ distribution in the VBF phase space compared with the SM predictions, for the $1\mu+\text{jets}$ region. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $m_{jj}$ distribution in the VBF phase space compared with the SM predictions, for the $1e+\text{jets}$ region. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $m_{jj}$ distribution in the VBF phase space compared with the SM predictions, for the $2\mu+\text{jets}$ region. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $m_{jj}$ distribution in the VBF phase space compared with the SM predictions, for the $2e+\text{jets}$ region. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $m_{jj}$ in the $1\mu+\text{jets}$ region of the VBF phase space. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $m_{jj}$ in the $e+\text{jets}$ region of the VBF phase space. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $m_{jj}$ in the $2\mu+\text{jets}$ region of the VBF phase space. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $m_{jj}$ in the $2e+\text{jets}$ region of the VBF phase space. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $\Delta\phi_{jj}$ distributions in the VBF phase space compared with the SM predictions for the $p_\text{T}^\text{miss}+\text{jets}$ region. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $\Delta\phi_{jj}$ distributions in the VBF phase space compared with the SM predictions for the $1\mu+\text{jets}$ region. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $\Delta\phi_{jj}$ distributions in the VBF phase space compared with the SM predictions for the $1e+\text{jets}$ region. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $\Delta\phi_{jj}$ distributions in the VBF phase space compared with the SM predictions for the $2\mu+\text{jets}$ region. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured $\Delta\phi_{jj}$ distributions in the VBF phase space compared with the SM predictions for the $2e+\text{jets}$ region. The middle panels show the ratios of the predictions to the data, along with their uncertainties, while the lower panels show the relative contributions from different SM processes relative to the total MEPS@NLO prediction. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $\Delta\phi_{jj}$ in the $1\mu+\text{jets}$ region of the VBF phase space. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $\Delta\phi_{jj}$ in the $1e+\text{jets}$ region of the VBF phase space. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $\Delta\phi_{jj}$ in the $2\mu+\text{jets}$ region of the VBF phase space. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

Comparison with SM predictions of the $\text{R}_\text{miss}$ ratios of the measured differential cross-sections for $\Delta\phi_{jj}$ in the $2e+\text{jets}$ region of the VBF phase space. The bottom panels show the ratios of the predictions to the data, along with their uncertainties. Note that individually numbered PDF components ('dK_PDF_') in the uncertainty breakdown correspond to NNPDF Hessian eigenvectors. Uncertainty components labeled 'VV_dK' include Vjj processes.

The measured Z &rarr; &nu;&nu; cross-section, differential in p_T^Z in the (a) single jet and (b) VBF phase spaces, and differential in (c) m_jj and (d) &Delta;&phi;_jj in the VBF phase space, compared with the SM predictions. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red hatched band).

The measured Z &rarr; &nu;&nu; cross-section, differential in p_T^Z in the (a) single jet and (b) VBF phase spaces, and differential in (c) m_jj and (d) &Delta;&phi;_jj in the VBF phase space, compared with the SM predictions. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red hatched band).

The measured Z &rarr; &nu;&nu; cross-section, differential in p_T^Z in the (a) single jet and (b) VBF phase spaces, and differential in (c) m_jj and (d) &Delta;&phi;_jj in the VBF phase space, compared with the SM predictions. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red hatched band).

The measured Z &rarr; &nu;&nu; cross-section, differential in p_T^Z in the (a) single jet and (b) VBF phase spaces, and differential in (c) m_jj and (d) &Delta;&phi;_jj in the VBF phase space, compared with the SM predictions. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red hatched band).

The measured p_T^Z, p_T^W and p_T^&gamma; differential cross-sections in the inclusive jet phase spaces compared with the SM predictions: (a) p_T^miss+jets, (b) &gamma;+jets, (c) 2e+jets, (d) 2&mu;+jets,(e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured p_T^Z, p_T^W and p_T^&gamma; differential cross-sections in the VBF phase spaces compared with the SM predictions: (a) p_T^miss+jets, (b) &gamma;+jets, (c) 2e+jets, (d) 2&mu;+jets, (e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured m_jj differential cross-sections in the VBF phase spaces compared with the SM predictions: (a) p_T^miss+jets, (b) &gamma;+jets, (c) 2e+jets, (d) 2&mu;+jets, (e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured &Delta;&phi;_jj differential cross-sections in the VBF phase spaces compared with the SM predictions: (a) p_T^miss+jets (b) &gamma;+jets (c) 2e+jets (d) 2&mu;+jets (e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured p_T^Z, p_T^W and p_T^&gamma; differential cross-sections in the inclusive jet phase spaces compared with the SM predictions: (a) p_T^miss+jets, (b) &gamma;+jets, (c) 2e+jets, (d) 2&mu;+jets,(e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured p_T^Z, p_T^W and p_T^&gamma; differential cross-sections in the VBF phase spaces compared with the SM predictions: (a) p_T^miss+jets, (b) &gamma;+jets, (c) 2e+jets, (d) 2&mu;+jets, (e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured m_jj differential cross-sections in the VBF phase spaces compared with the SM predictions: (a) p_T^miss+jets, (b) &gamma;+jets, (c) 2e+jets, (d) 2&mu;+jets, (e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured &Delta;&phi;_jj differential cross-sections in the VBF phase spaces compared with the SM predictions: (a) p_T^miss+jets (b) &gamma;+jets (c) 2e+jets (d) 2&mu;+jets (e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured p_T^Z, p_T^W and p_T^&gamma; differential cross-sections in the inclusive jet phase spaces compared with the SM predictions: (a) p_T^miss+jets, (b) &gamma;+jets, (c) 2e+jets, (d) 2&mu;+jets,(e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured p_T^Z, p_T^W and p_T^&gamma; differential cross-sections in the VBF phase spaces compared with the SM predictions: (a) p_T^miss+jets, (b) &gamma;+jets, (c) 2e+jets, (d) 2&mu;+jets, (e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured m_jj differential cross-sections in the VBF phase spaces compared with the SM predictions: (a) p_T^miss+jets, (b) &gamma;+jets, (c) 2e+jets, (d) 2&mu;+jets, (e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured &Delta;&phi;_jj differential cross-sections in the VBF phase spaces compared with the SM predictions: (a) p_T^miss+jets (b) &gamma;+jets (c) 2e+jets (d) 2&mu;+jets (e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured p_T^Z, p_T^W and p_T^&gamma; differential cross-sections in the inclusive jet phase spaces compared with the SM predictions: (a) p_T^miss+jets, (b) &gamma;+jets, (c) 2e+jets, (d) 2&mu;+jets,(e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured p_T^Z, p_T^W and p_T^&gamma; differential cross-sections in the VBF phase spaces compared with the SM predictions: (a) p_T^miss+jets, (b) &gamma;+jets, (c) 2e+jets, (d) 2&mu;+jets, (e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured m_jj differential cross-sections in the VBF phase spaces compared with the SM predictions: (a) p_T^miss+jets, (b) &gamma;+jets, (c) 2e+jets, (d) 2&mu;+jets, (e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured &Delta;&phi;_jj differential cross-sections in the VBF phase spaces compared with the SM predictions: (a) p_T^miss+jets (b) &gamma;+jets (c) 2e+jets (d) 2&mu;+jets (e) e+jets and (f) &mu;+jets. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red shading).

The measured &gamma;+jets cross-section, differential in p_T^&gamma; in the (a) single jet and (b) VBF phase spaces, and differential in (c) m_jj and (d) &Delta;&phi;_jj in the VBF phase space, compared with the SM predictions. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red hatched band).

The measured &gamma;+jets cross-section, differential in p_T^&gamma; in the (a) single jet and (b) VBF phase spaces, and differential in (c) m_jj and (d) &Delta;&phi;_jj in the VBF phase space, compared with the SM predictions. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red hatched band).

The measured &gamma;+jets cross-section, differential in p_T^&gamma; in the (a) single jet and (b) VBF phase spaces, and differential in (c) m_jj and (d) &Delta;&phi;_jj in the VBF phase space, compared with the SM predictions. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red hatched band).

The measured &gamma;+jets cross-section, differential in p_T^&gamma; in the (a) single jet and (b) VBF phase spaces, and differential in (c) m_jj and (d) &Delta;&phi;_jj in the VBF phase space, compared with the SM predictions. The lower panels show the ratios of the predictions to the data, along with the data statistical uncertainties (black bars) and systematic uncertainties (red hatched band).

SM processes contributing to the fiducial SM predictions shown in Figure 7a

SM processes contributing to the fiducial SM predictions shown in Figure 7b

SM processes contributing to the fiducial SM predictions shown in Figure 8a

SM processes contributing to the fiducial SM predictions shown in Figure 8b

SM processes contributing to the fiducial SM predictions shown in Figure 8c

SM processes contributing to the fiducial SM predictions shown in Figure 8d

SM processes contributing to the fiducial SM predictions shown in Figure 9a

SM processes contributing to the fiducial SM predictions shown in Figure 9b

SM processes contributing to the fiducial SM predictions shown in Figure 9c

SM processes contributing to the fiducial SM predictions shown in Figure 9d

SM processes contributing to the fiducial SM predictions shown in Figure 3b of Auxiliary Material

SM processes contributing to the fiducial SM predictions shown in Figure 3c of Auxiliary Material

SM processes contributing to the fiducial SM predictions shown in Figure 3d of Auxiliary Material

SM processes contributing to the fiducial SM predictions shown in Figure 3e of Auxiliary Material

SM processes contributing to the fiducial SM predictions shown in Figure 5b of Auxiliary Material

SM processes contributing to the fiducial SM predictions shown in Figure 5c of Auxiliary Material

SM processes contributing to the fiducial SM predictions shown in Figure 5d of Auxiliary Material

SM processes contributing to the fiducial SM predictions shown in Figure 7b of Auxiliary Material

SM processes contributing to the fiducial SM predictions shown in Figure 7c of Auxiliary Material

SM processes contributing to the fiducial SM predictions shown in Figure 7d of Auxiliary Material

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $p_\text{T}^\text{miss}$ + jets region, $\geq 1$ jet phase space (Figure 7a) and $p_\text{T}^\text{recoil}$ observable, $p_\text{T}^\text{miss}$ + jets region, $\geq 1$ jet phase space (Figure 7a).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $p_\text{T}^\text{miss}$ + jets region, $\geq 1$ jet phase space (Figure 7a) and $p_\text{T}^\text{recoil}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 7b).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $p_\text{T}^\text{miss}$ + jets region, $\geq 1$ jet phase space (Figure 7a) and $m_{\text jj}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 9a).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $p_\text{T}^\text{miss}$ + jets region, $\geq 1$ jet phase space (Figure 7a) and $\Delta\phi_\text{jj}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 9b).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $1\mu$ + jets region, $\geq 1$ jet phase space (Figure 8c) and $p_\text{T}^\text{recoil}$ observable, $1\mu$ + jets region, $\geq 1$ jet phase space (Figure 8c).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $1\mu$ + jets region, $\geq 1$ jet phase space (Figure 8c) and $p_\text{T}^\text{recoil}$ observable, $1\mu$ + jets region, VBF phase space (Figure 3d (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $1\mu$ + jets region, $\geq 1$ jet phase space (Figure 8c) and $m_{\text jj}$ observable, $1\mu$ + jets region, VBF phase space (Figure 5d (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $1\mu$ + jets region, $\geq 1$ jet phase space (Figure 8c) and $\Delta\phi_\text{jj}$ observable, $1\mu$ + jets region, VBF phase space (Figure 7d (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 1e + jets region, $\geq 1$ jet phase space (Figure 8a) and $p_\text{T}^\text{recoil}$ observable, 1e + jets region, $\geq 1$ jet phase space (Figure 8a).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 1e + jets region, $\geq 1$ jet phase space (Figure 8a) and $p_\text{T}^\text{recoil}$ observable, 1e + jets region, VBF phase space (Figure 3b (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 1e + jets region, $\geq 1$ jet phase space (Figure 8a) and $m_{\text jj}$ observable, 1e + jets region, VBF phase space (Figure 5b (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 1e + jets region, $\geq 1$ jet phase space (Figure 8a) and $\Delta\phi_\text{jj}$ observable, 1e + jets region, VBF phase space (Figure 7b (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $2\mu$ + jets region, $\geq 1$ jet phase space (Figure 8d) and $p_\text{T}^\text{recoil}$ observable, $2\mu$ + jets region, $\geq 1$ jet phase space (Figure 8d).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $2\mu$ + jets region, $\geq 1$ jet phase space (Figure 8d) and $p_\text{T}^\text{recoil}$ observable, $2\mu$ + jets region, VBF phase space (Figure 3e (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $2\mu$ + jets region, $\geq 1$ jet phase space (Figure 8d) and $m_{\text jj}$ observable, $2\mu$ + jets region, VBF phase space (Figure 9c).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $2\mu$ + jets region, $\geq 1$ jet phase space (Figure 8d) and $\Delta\phi_\text{jj}$ observable, $2\mu$ + jets region, VBF phase space (Figure 9d).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 2e + jets region, $\geq 1$ jet phase space (Figure 8b) and $p_\text{T}^\text{recoil}$ observable, 2e + jets region, $\geq 1$ jet phase space (Figure 8b).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 2e + jets region, $\geq 1$ jet phase space (Figure 8b) and $p_\text{T}^\text{recoil}$ observable, 2e + jets region, VBF phase space (Figure 3c (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 2e + jets region, $\geq 1$ jet phase space (Figure 8b) and $m_{\text jj}$ observable, 2e + jets region, VBF phase space (Figure 5c (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 2e + jets region, $\geq 1$ jet phase space (Figure 8b) and $\Delta\phi_\text{jj}$ observable, 2e + jets region, VBF phase space (Figure 7c (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $1\mu$ + jets region, $\geq 1$ jet phase space (Figure 2c (aux)) and $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $1\mu$ + jets region, $\geq 1$ jet phase space (Figure 2c (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 1e + jets region, $\geq 1$ jet phase space (Figure 10a) and $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 1e + jets region, $\geq 1$ jet phase space (Figure 10a).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $2\mu$ + jets region, $\geq 1$ jet phase space (Figure 2d (aux)) and $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $2\mu$ + jets region, $\geq 1$ jet phase space (Figure 2d (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 2e + jets region, $\geq 1$ jet phase space (Figure 10b) and $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 2e + jets region, $\geq 1$ jet phase space (Figure 10b).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 7b) and $p_\text{T}^\text{recoil}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 7b).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 7b) and $m_{\text jj}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 9a).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 7b) and $\Delta\phi_\text{jj}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 9b).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $1\mu$ + jets region, VBF phase space (Figure 3d (aux)) and $p_\text{T}^\text{recoil}$ observable, $1\mu$ + jets region, VBF phase space (Figure 3d (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $1\mu$ + jets region, VBF phase space (Figure 3d (aux)) and $m_{\text jj}$ observable, $1\mu$ + jets region, VBF phase space (Figure 5d (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $1\mu$ + jets region, VBF phase space (Figure 3d (aux)) and $\Delta\phi_\text{jj}$ observable, $1\mu$ + jets region, VBF phase space (Figure 7d (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 1e + jets region, VBF phase space (Figure 3b (aux)) and $p_\text{T}^\text{recoil}$ observable, 1e + jets region, VBF phase space (Figure 3b (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 1e + jets region, VBF phase space (Figure 3b (aux)) and $m_{\text jj}$ observable, 1e + jets region, VBF phase space (Figure 5b (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 1e + jets region, VBF phase space (Figure 3b (aux)) and $\Delta\phi_\text{jj}$ observable, 1e + jets region, VBF phase space (Figure 7b (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $2\mu$ + jets region, VBF phase space (Figure 3e (aux)) and $p_\text{T}^\text{recoil}$ observable, $2\mu$ + jets region, VBF phase space (Figure 3e (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $2\mu$ + jets region, VBF phase space (Figure 3e (aux)) and $m_{\text jj}$ observable, $2\mu$ + jets region, VBF phase space (Figure 9c).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $2\mu$ + jets region, VBF phase space (Figure 3e (aux)) and $\Delta\phi_\text{jj}$ observable, $2\mu$ + jets region, VBF phase space (Figure 9d).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 2e + jets region, VBF phase space (Figure 3c (aux)) and $p_\text{T}^\text{recoil}$ observable, 2e + jets region, VBF phase space (Figure 3c (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 2e + jets region, VBF phase space (Figure 3c (aux)) and $m_{\text jj}$ observable, 2e + jets region, VBF phase space (Figure 5c (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, 2e + jets region, VBF phase space (Figure 3c (aux)) and $\Delta\phi_\text{jj}$ observable, 2e + jets region, VBF phase space (Figure 7c (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $1\mu$ + jets region, VBF phase space (Figure 4c (aux)) and $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $1\mu$ + jets region, VBF phase space (Figure 4c (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 1e + jets region, VBF phase space (Figure 4a (aux)) and $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 1e + jets region, VBF phase space (Figure 4a (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $2\mu$ + jets region, VBF phase space (Figure 4d (aux)) and $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $2\mu$ + jets region, VBF phase space (Figure 4d (aux)).

Statistical correlations between $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 2e + jets region, VBF phase space (Figure 4b (aux)) and $p_\text{T}^\text{recoil}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 2e + jets region, VBF phase space (Figure 4b (aux)).

Statistical correlations between $m_{\text jj}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 9a) and $m_{\text jj}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 9a).

Statistical correlations between $m_{\text jj}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 9a) and $\Delta\phi_\text{jj}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 9b).

Statistical correlations between $m_{\text jj}$ observable, $1\mu$ + jets region, VBF phase space (Figure 5d (aux)) and $m_{\text jj}$ observable, $1\mu$ + jets region, VBF phase space (Figure 5d (aux)).

Statistical correlations between $m_{\text jj}$ observable, $1\mu$ + jets region, VBF phase space (Figure 5d (aux)) and $\Delta\phi_\text{jj}$ observable, $1\mu$ + jets region, VBF phase space (Figure 7d (aux)).

Statistical correlations between $m_{\text jj}$ observable, 1e + jets region, VBF phase space (Figure 5b (aux)) and $m_{\text jj}$ observable, 1e + jets region, VBF phase space (Figure 5b (aux)).

Statistical correlations between $m_{\text jj}$ observable, 1e + jets region, VBF phase space (Figure 5b (aux)) and $\Delta\phi_\text{jj}$ observable, 1e + jets region, VBF phase space (Figure 7b (aux)).

Statistical correlations between $m_{\text jj}$ observable, $2\mu$ + jets region, VBF phase space (Figure 9c) and $m_{\text jj}$ observable, $2\mu$ + jets region, VBF phase space (Figure 9c).

Statistical correlations between $m_{\text jj}$ observable, $2\mu$ + jets region, VBF phase space (Figure 9c) and $\Delta\phi_\text{jj}$ observable, $2\mu$ + jets region, VBF phase space (Figure 9d).

Statistical correlations between $m_{\text jj}$ observable, 2e + jets region, VBF phase space (Figure 5c (aux)) and $m_{\text jj}$ observable, 2e + jets region, VBF phase space (Figure 5c (aux)).

Statistical correlations between $m_{\text jj}$ observable, 2e + jets region, VBF phase space (Figure 5c (aux)) and $\Delta\phi_\text{jj}$ observable, 2e + jets region, VBF phase space (Figure 7c (aux)).

Statistical correlations between $m_{\text jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $1\mu$ + jets region, VBF phase space (Figure 6c (aux)) and $m_{\text jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $1\mu$ + jets region, VBF phase space (Figure 6c (aux)).

Statistical correlations between $m_{\text jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 1e + jets region, VBF phase space (Figure 6a (aux)) and $m_{\text jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 1e + jets region, VBF phase space (Figure 6a (aux)).

Statistical correlations between $m_{\text jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $2\mu$ + jets region, VBF phase space (Figure 10c) and $m_{\text jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $2\mu$ + jets region, VBF phase space (Figure 10c).

Statistical correlations between $m_{\text jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 2e + jets region, VBF phase space (Figure 6b (aux)) and $m_{\text jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 2e + jets region, VBF phase space (Figure 6b (aux)).

Statistical correlations between $\Delta\phi_\text{jj}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 9b) and $\Delta\phi_\text{jj}$ observable, $p_\text{T}^\text{miss}$ + jets region, VBF phase space (Figure 9b).

Statistical correlations between $\Delta\phi_\text{jj}$ observable, $1\mu$ + jets region, VBF phase space (Figure 7d (aux)) and $\Delta\phi_\text{jj}$ observable, $1\mu$ + jets region, VBF phase space (Figure 7d (aux)).

Statistical correlations between $\Delta\phi_\text{jj}$ observable, 1e + jets region, VBF phase space (Figure 7b (aux)) and $\Delta\phi_\text{jj}$ observable, 1e + jets region, VBF phase space (Figure 7b (aux)).

Statistical correlations between $\Delta\phi_\text{jj}$ observable, $2\mu$ + jets region, VBF phase space (Figure 9d) and $\Delta\phi_\text{jj}$ observable, $2\mu$ + jets region, VBF phase space (Figure 9d).

Statistical correlations between $\Delta\phi_\text{jj}$ observable, 2e + jets region, VBF phase space (Figure 7c (aux)) and $\Delta\phi_\text{jj}$ observable, 2e + jets region, VBF phase space (Figure 7c (aux)).

Statistical correlations between $\Delta\phi_\text{jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $1\mu$ + jets region, VBF phase space (Figure 8c (aux)) and $\Delta\phi_\text{jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $1\mu$ + jets region, VBF phase space (Figure 8c (aux)).

Statistical correlations between $\Delta\phi_\text{jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 1e + jets region, VBF phase space (Figure 8a (aux)) and $\Delta\phi_\text{jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 1e + jets region, VBF phase space (Figure 8a (aux)).

Statistical correlations between $\Delta\phi_\text{jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $2\mu$ + jets region, VBF phase space (Figure 10d) and $\Delta\phi_\text{jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ $2\mu$ + jets region, VBF phase space (Figure 10d).

Statistical correlations between $\Delta\phi_\text{jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 2e + jets region, VBF phase space (Figure 8b (aux)) and $\Delta\phi_\text{jj}$ observable, $\text{R}_\text{miss}$ observable, $R_{miss}$ 2e + jets region, VBF phase space (Figure 8b (aux)).

The observed profile likelihood ratio, $-2ln \Lambda$, as a function of $\Gamma_H$. Compared with the version in the paper, the effective couplings in the ggF, $H\to\gamma\gamma$, and $H\to Z\gamma$ processes are in terms of SM coupling strengths, resulting in an improved upper limit under stronger model assumptions.

The observed profile likelihood ratio, $-2ln \Lambda$, as a function of $\Gamma_H/\Gamma_H^{SM}$. Compared with the version in the paper, the effective couplings in the ggF, $H\to\gamma\gamma$, and $H\to Z\gamma$ processes are in terms of SM coupling strengths, resulting in an improved upper limit under stronger model assumptions.

The observed profile likelihood ratio, $-2ln \Lambda$, as a function of $\Gamma_H/\Gamma_H^{SM}$ and $\kappa_t$. Compared with the version in the paper, the effective couplings in the ggF, $H\to\gamma\gamma$, and $H\to Z\gamma$ processes are in terms of SM coupling strengths, resulting in an improved upper limit under stronger model assumptions.

Observed event yields in $\textrm{SR}$ compared with post-fit expectations from Monte Carlo simulations, as a function of the scalar sum of lepton and jet transverse momenta, $H_{\mathrm{T}}$. The last bin includes overflow events. `Signal (prod.)' and `Signal (dec.)' refer to the single-top-quark production and top-quark pair decay signal contributions, respectively.

Expected and observed 95$\%$ CL upper limits on the branching ratio corresponding to the decay of a top quark to a muon and a tau lepton through a cLFV process for scalar, vector and tensor couplings. In the vector case, all vector operators are assumed to contribute simultaneously with the same effective coupling strength. The table shows the endpoint values of $\mathcal{B}(\mathrm{t}\to\mu\tau\mathrm{u})$ and $\mathcal{B}(\mathrm{t}\to\mu\tau\mathrm{c})$, which are interpolated linearly for each limit.

Expected and observed 95$\%$ CL upper limits on the Wilson coefficients for scalar, vector and tensor couplings of a top quark to a muon and a tau lepton through a cLFV process. In the vector case, all vector operators are assumed to contribute simultaneously with the same effective coupling strength. The table shows the endpoint values of the $|c^{\mu\tau\mathrm{ut}}|$ and $|c^{\mu\tau\mathrm{ct}}|$ Wilson coefficients, which are interpolated assuming a linear relationship between $\mathcal{B}(\mathrm{t}\to\mu\tau\mathrm{u})$ and $\mathcal{B}(\mathrm{t}\to\mu\tau\mathrm{c})$.

Observed event yields in $\textrm{SR}$ compared with pre-fit expectations from Monte Carlo simulations, as a function of the scalar sum of lepton and jet transverse momenta, $H_{\mathrm{T}}$. The last bin includes overflow events. The signal yields represent a leptoquark mass of $m_{S_{1}} = 1$ TeV and a coupling strength of $\lambda^{\textrm{LQ}} = 2.0$.

Observed event yields in $\textrm{SR}$ compared with post-fit expectations from Monte Carlo simulations, as a function of the scalar sum of lepton and jet transverse momenta, $H_{\mathrm{T}}$. The last bin includes overflow events. The signal yields represent a leptoquark mass of $m_{S_{1}} = 1$ TeV and a coupling strength of $\lambda^{\textrm{LQ}} = 2.0$.

Observed and expected exclusion 95$\%$ CL upper limits on the $S_{1}$ leptoquark coupling strength $\lambda^{\textrm{LQ}}$ as a function of LQ mass, $m_{S_{1}}$.

Theoretical cross-sections for single-top-quark production and top-quark decays through cLFV interactions involving vector, scalar and tensor EFT Wilson coefficients. The column titled as $c^{(ijk3)}_{\textrm{vector}}$ represents the individual cross-section contributions from each of $c_{\mathsf{lq}}^{-(ijk3)}$, $c_{\mathsf{eq}}^{(ijk3)}$, $c_{\mathsf{lu}}^{(ijk3)}$ and $c_{\mathsf{eu}}^{(ijk3)}$. The coefficient indices represent the lepton flavour generations ($i,j = 1,2,3$ where $i \neq j$) and light quark flavour generations ($k = 1,2$). The single-top-quark production cross-sections are quoted for $u$- and $c$-quark couplings separately, while they are combined for the $t\bar{t}$ decay process ($q_k = u,c$). The scale and PDF uncertainties are given. The value of each Wilson coefficient is set to 1.0 for the calculation of the cross-section.

Requirements for each analysis region. The symbol $\ell_{3}$ denotes the lowest $p_{\mathrm{T}}$ lepton. In $\mathrm{CR}t\bar{t}\mu$ an additional requirement is placed on the leading muon $p_{\mathrm{T}}$ ($p^{\mu_1}_\mathrm{T}$) and dilepton invariant masses in order to reject signal events.

Post-fit event yields for each analysis region entering the fit, with correlations on the full systematic uncertainties taken into account as determined in the fit under a signal+background hypothesis. The 'fake electron' category in the CR$t\bar{t}\mu$ control region collects small contributions primarily from $t\bar{t}\gamma$ and $Z\gamma$ which enter the event selection due to photon conversions.

Expected and observed 95$\%$ CL upper limits on Wilson coefficients corresponding to 2Q2L EFT operators which could introduce a cLFV top decay in the $\mu\tau$ channel, and existing limits from JHEP04 (2019) 014 (previous). The previous limits shown for $c^{1(ijk3)}_{\mathsf{lequ}}$ and $c^{3(ijk3)}_{\mathsf{lequ}}$ are tightened by a factor of $\sqrt{2}$, as JHEP04 (2019) 014 does not assume that these operators are Hermitian. Results are shown separately for the $\mu\tau ut$ and $\mu\tau ct$ interactions. The lepton generations are denoted by $i,j=2,3$ for $\mu$ and $\tau$ (where $i \neq j$) and the quark generations are denoted by $k=1,2$ for $u$ and $c$, respectively.

Expected and observed 95$\%$ CL upper limits on the branching ratio ($\mathcal{B}$) corresponding to the decay of a top quark to a muon and a $\tau$ lepton through a cLFV process using specific Wilson coefficients corresponding to 2Q2L EFT operators. Results are shown separately for $\mu\tau ut$ and $\mu\tau ct$ interactions. The lepton generations are denoted by $i,j=2,3$ for $\mu$ and $\tau$ (where $i \neq j$) and the quark generations are denoted by $k=1,2$ for $u$ and $c$, respectively.

Expected and observed 95% CL upper limits on the inclusive branching ratio ($\mathcal{B}$) corresponding to the decay of a top quark to a muon and a $\tau$-lepton through a cLFV process. Limits are shown for the statistical uncertainty only and for the full set of statistical and systematic uncertainties.

Expected and observed 95$\%$ CL upper limits on the Wilson coefficients corresponding to EFT operators inducing the decay of a top quark to a muon, a tau lepton and an up quark through a cLFV process ($\mu\tau ut$ interaction).

Expected and observed 95$\%$ CL upper limits on the Wilson coefficients corresponding to EFT operators inducing the decay of a top quark to a muon, a tau lepton and a charm quark through a cLFV process ($\mu\tau ct$ interaction).

Ranking of nuisance parameters by post-fit impact on cLFV signal strength $\mu$ (the parameter of interest, POI). The pre-fit (post-fit) impact of each nuisance parameter is calculated as the difference to the fitted value of cLFV signal strength between the nominal fit and a fit when fixing the corresponding nuisance parameter to $\hat{\theta}\pm\Delta\theta$ ($\hat{\theta}\pm\Delta\hat{\theta}$), where $\hat{\theta}$ is the best-fit value of the nuisance parameter and $\Delta\theta$ ($\Delta\hat{\theta}$) is its pre-fit (post-fit) uncertainty. The pulls of the nuisance parameters are calculated relative to zero. These pulls and their post-fit errors, $\Delta\hat{\theta} / \Delta\theta$, are given in the second column of the table.

Expected exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos.

Observed exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos.

Observed exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos.

Observed exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos.

Expected exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos.

Expected exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos.

Expected exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos.

Observed exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos.

Observed exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos.

Observed exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos.

Expected exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM1.

Expected exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM1.

Expected exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM1.

Observed exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM1.

Observed exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM1.

Observed exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM1.

Expected exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM2.

Expected exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM2.

Expected exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM2.

Observed exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM2.

Observed exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM2.

Observed exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM2.

Expected exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM3.

Expected exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM3.

Expected exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM3.

Observed exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM3.

Observed exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM3.

Observed exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-HM3.

Expected exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp1.

Expected exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp1.

Expected exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp1.

Observed exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp1.

Observed exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp1.

Observed exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp1.

Expected exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp2.

Expected exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp2.

Expected exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp2.

Observed exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp2.

Observed exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp2.

Observed exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp2.

Expected exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp3.

Expected exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp3.

Expected exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp3.

Observed exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp3.

Observed exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp3.

Observed exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp3.

Expected exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp-1c.

Expected exclusion limit at 95% CL for pair production of top squarks decaying to charm quarks and neutralinos when only considering SR-Comp-1c.

Expected exclusion limit at 95% CL for pair production of top squarks decaying to top or charm quarks and 1 GeV neutralinos for different branching fraction assumptions.

Expected exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to top or charm quarks and 1 GeV neutralinos for different branching fraction assumptions.

Expected exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to top or charm quarks and 1 GeV neutralinos for different branching fraction assumptions.

Observed exclusion limit at 95% CL for pair production of top squarks decaying to top or charm quarks and 1 GeV neutralinos for different branching fraction assumptions.

Observed exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to top or charm quarks and 1 GeV neutralinos for different branching fraction assumptions.

Observed exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to top or charm quarks and 1 GeV neutralinos for different branching fraction assumptions.

Expected exclusion limit at 95% CL for pair production of top squarks decaying to top or charm quarks and 200 GeV neutralinos for different branching fraction assumptions.

Expected exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to top or charm quarks and 200 GeV neutralinos for different branching fraction assumptions.

Expected exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to top or charm quarks and 200 GeV neutralinos for different branching fraction assumptions.

Observed exclusion limit at 95% CL for pair production of top squarks decaying to top or charm quarks and 200 GeV neutralinos for different branching fraction assumptions.

Observed exclusion limit $(+1\sigma)$ at 95% CL for pair production of top squarks decaying to top or charm quarks and 200 GeV neutralinos for different branching fraction assumptions.

Observed exclusion limit $(-1\sigma)$ at 95% CL for pair production of top squarks decaying to top or charm quarks and 200 GeV neutralinos for different branching fraction assumptions.

Expected exclusion limit $(-1\sigma)$ at 95% CL for pair production of up-type scalar LQs coupled to first generation leptons and second generation quarks.

Expected exclusion limit $(+1\sigma)$ at 95% CL for pair production of up-type scalar LQs coupled to first generation leptons and second generation quarks.

Expected exclusion limit at 95% CL for pair production of up-type scalar LQs coupled to first generation leptons and second generation quarks.

Observed exclusion limit $(+1\sigma)$ at 95% CL for pair production of up-type scalar LQs coupled to first generation leptons and second generation quarks.

Observed exclusion limit $(-1\sigma)$ at 95% CL for pair production of up-type scalar LQs coupled to first generation leptons and second generation quarks.

Observed exclusion limit at 95% CL for pair production of up-type scalar LQs coupled to first generation leptons and second generation quarks.

Expected exclusion limit $(-1\sigma)$ at 95% CL for pair production of up-type scalar LQs coupled to second generation leptons and quarks.

Expected exclusion limit $(+1\sigma)$ at 95% CL for pair production of up-type scalar LQs coupled to second generation leptons and quarks.

Expected exclusion limit at 95% CL for pair production of up-type scalar LQs coupled to second generation leptons and quarks.

Observed exclusion limit $(+1\sigma)$ at 95% CL for pair production of up-type scalar LQs coupled to second generation leptons and quarks.

Observed exclusion limit $(-1\sigma)$ at 95% CL for pair production of up-type scalar LQs coupled to second generation leptons and quarks.

Observed exclusion limit at 95% CL for pair production of up-type scalar LQs coupled to second generation leptons and quarks.

Observed upper limit on the cross-section at 95% CL for pair production of top squarks decaying into charm quarks and neutralinos for the fit with the best expected CL$_\mathrm{S}$.

Observed upper limit on the cross-section for pair production of up-type scalar LQs coupled to first generation leptons and second generation quarks.

Observed upper limit on the cross-section for pair production of up-type scalar LQs coupled to second generation leptons and quarks.

Expected upper limit on the cross-section $(-1\sigma)$ for $U(1)$ vector LQ models in the minimal coupling scenario with $\beta_{23}=1$, corresponding to a branching fraction $\mathcal{B}(\mathrm{vLQ}^\mathrm{u,min}_{23}\rightarrow c\nu) = 0.5$.

Expected upper limit on the cross-section $(+1\sigma)$ for $U(1)$ vector LQ models in the minimal coupling scenario with $\beta_{23}=1$, corresponding to a branching fraction $\mathcal{B}(\mathrm{vLQ}^\mathrm{u,min}_{23}\rightarrow c\nu) = 0.5$.

Expected upper limit on the cross-section for $U(1)$ vector LQ models in the minimal coupling scenario with $\beta_{23}=1$, corresponding to a branching fraction $\mathcal{B}(\mathrm{vLQ}^\mathrm{u,min}_{23}\rightarrow c\nu) = 0.5$.

Observed upper limit on the cross-section for $U(1)$ vector LQ models in the minimal coupling scenario with $\beta_{23}=1$, corresponding to a branching fraction $\mathcal{B}(\mathrm{vLQ}^\mathrm{u,min}_{23}\rightarrow c\nu) = 0.5$.

Expected upper limit on the cross-section $(-1\sigma)$ for $U(1)$ vector LQ models in the Yang-Mills coupling scenario with $\beta_{23}=1$, corresponding to a branching fraction $\mathcal{B}(\mathrm{vLQ}^\mathrm{u,YM}_{23}\rightarrow c\nu) = 0.5$.

Expected upper limit on the cross-section $(+1\sigma)$ for $U(1)$ vector LQ models in the Yang-Mills coupling scenario with $\beta_{23}=1$, corresponding to a branching fraction $\mathcal{B}(\mathrm{vLQ}^\mathrm{u,YM}_{23}\rightarrow c\nu) = 0.5$.

Expected upper limit on the cross-section for $U(1)$ vector LQ models in the Yang-Mills coupling scenario with $\beta_{23}=1$, corresponding to a branching fraction $\mathcal{B}(\mathrm{vLQ}^\mathrm{u,YM}_{23}\rightarrow c\nu) = 0.5$.

Observed upper limit on the cross-section for $U(1)$ vector LQ models in the Yang-Mills coupling scenario with $\beta_{23}=1$, corresponding to a branching fraction $\mathcal{B}(\mathrm{vLQ}^\mathrm{u,YM}_{23}\rightarrow c\nu) = 0.5$.

Distribution of $R_{\mathrm{ISR}}$ in SR-Comp-1c showing the data and the expected backgrounds, after simultaneously fitting all the control regions. The pre-fit yields for a representative $m(\tilde{t}_1,\tilde{\chi}_1^0)=(450,430)$ GeV signal is included. Processes with top quarks and multiple vector bosons are included in "Other". The right-most bin does not include the overflow entry but the $x$-axis range is chosen to include all observed data.

Distribution of $E_\mathrm{T}^\mathrm{miss}\mathrm{ Sig.}$ in SR-HM1 showing the data and the expected backgrounds, after simultaneously fitting all the control regions. The pre-fit yields for a representative $m(\tilde{t}_1,\tilde{\chi}_1^0)=(1000,1)$ GeV signal is included. Processes with top quarks and multiple vector bosons are included in "Other". The right-most bin does not include the overflow entry but the $x$-axis range is chosen to include all observed data.

Distribution of $m_{\mathrm{T}}^{\mathrm{min}}(c)$ in SR-HM2 showing the data and the expected backgrounds, after simultaneously fitting all the control regions. The pre-fit yields for a representative $m(\tilde{t}_1,\tilde{\chi}_1^0)=(750,450)$ GeV signal is included. Processes with top quarks and multiple vector bosons are included in "Other". The right-most bin does not include the overflow entry but the $x$-axis range is chosen to include all observed data.

Distribution of $R_{\mathrm{ISR}}$ in SR-Comp1 showing the data and the expected backgrounds, after simultaneously fitting all the control regions. The pre-fit yields for a representative $m(\tilde{t}_1,\tilde{\chi}_1^0)=(600,550)$ GeV signal is included. Processes with top quarks and multiple vector bosons are included in "Other". The right-most bin does not include the overflow entry but the $x$-axis range is chosen to include all observed data.

Distribution of $R_{\mathrm{ISR}}$ in SR-Comp2 showing the data and the expected backgrounds, after simultaneously fitting all the control regions. The pre-fit yields for a representative $m(\tilde{t}_1,\tilde{\chi}_1^0)=(550,470)$ GeV signal is included. Processes with top quarks and multiple vector bosons are included in "Other". The right-most bin does not include the overflow entry but the $x$-axis range is chosen to include all observed data.

Distribution of $R_{\mathrm{ISR}}$ in SR-Comp3 showing the data and the expected backgrounds, after simultaneously fitting all the control regions. The pre-fit yields for a representative $m(\tilde{t}_1,\tilde{\chi}_1^0)=(550,375)$ GeV signal is included. Processes with top quarks and multiple vector bosons are included in "Other". The right-most bin does not include the overflow entry but the $x$-axis range is chosen to include all observed data.

Acceptance across the SUSY signal grid for SR-Comp-1c.

Acceptance across the SUSY signal grid for SR-HM1.

Acceptance across the SUSY signal grid for SR-HM2.

Acceptance across the SUSY signal grid for SR-HM3.

Acceptance across the SUSY signal grid for SR-HM-Disc.

Acceptance across the SUSY signal grid for SR-Comp1.

Acceptance across the SUSY signal grid for SR-Comp2.

Acceptance across the SUSY signal grid for SR-Comp3.

Acceptance across the $\mathrm{LQ}^\mathrm{u}_{21}$ signal grid for SR-HM1.

Acceptance across the $\mathrm{LQ}^\mathrm{u}_{21}$ signal grid for SR-HM2.

Acceptance across the $\mathrm{LQ}^\mathrm{u}_{21}$ signal grid for SR-HM3.

Acceptance across the $\mathrm{LQ}^\mathrm{u}_{21}$ signal grid for SR-HM-Disc.

Acceptance across the $\mathrm{LQ}^\mathrm{u}_{22}$ signal grid for SR-HM1.

Acceptance across the $\mathrm{LQ}^\mathrm{u}_{22}$ signal grid for SR-HM2.

Acceptance across the $\mathrm{LQ}^\mathrm{u}_{22}$ signal grid for SR-HM3.

Acceptance across the $\mathrm{LQ}^\mathrm{u}_{22}$ signal grid for SR-HM-Disc.

Acceptance for the $\mathrm{vLQ}^\mathrm{u,min}_{23}$ signal model in SR-HM1.

Acceptance for the $\mathrm{vLQ}^\mathrm{u,min}_{23}$ signal model in SR-HM2.

Acceptance for the $\mathrm{vLQ}^\mathrm{u,min}_{23}$ signal model in SR-HM3.

Acceptance for the $\mathrm{vLQ}^\mathrm{u,min}_{23}$ signal model in SR-HM-Disc.

Acceptance for the $\mathrm{vLQ}^\mathrm{u,YM}_{23}$ signal model in SR-HM1.

Acceptance for the $\mathrm{vLQ}^\mathrm{u,YM}_{23}$ signal model in SR-HM2.

Acceptance for the $\mathrm{vLQ}^\mathrm{u,YM}_{23}$ signal model in SR-HM3.

Acceptance for the $\mathrm{vLQ}^\mathrm{u,YM}_{23}$ signal model in SR-HM-Disc.

Efficiency for the $\mathrm{vLQ}^\mathrm{u,min}_{23}$ signal model in SR-HM1. Due to the limited statistical power of the signal samples, efficiencies can fluctuate and can drop to zero.

Efficiency for the $\mathrm{vLQ}^\mathrm{u,min}_{23}$ signal model in SR-HM2. Due to the limited statistical power of the signal samples, efficiencies can fluctuate and can drop to zero.

Efficiency for the $\mathrm{vLQ}^\mathrm{u,min}_{23}$ signal model in SR-HM3. Due to the limited statistical power of the signal samples, efficiencies can fluctuate and can drop to zero.

Efficiency for the $\mathrm{vLQ}^\mathrm{u,min}_{23}$ signal model in SR-HM-Disc. Due to the limited statistical power of the signal samples, efficiencies can fluctuate and can drop to zero.

Efficiency for the $\mathrm{vLQ}^\mathrm{u,YM}_{23}$ signal model in SR-HM1. Due to the limited statistical power of the signal samples, efficiencies can fluctuate and can drop to zero.

Efficiency for the $\mathrm{vLQ}^\mathrm{u,YM}_{23}$ signal model in SR-HM2. Due to the limited statistical power of the signal samples, efficiencies can fluctuate and can drop to zero.

Efficiency for the $\mathrm{vLQ}^\mathrm{u,YM}_{23}$ signal model in SR-HM3. Due to the limited statistical power of the signal samples, efficiencies can fluctuate and can drop to zero.

Efficiency for the $\mathrm{vLQ}^\mathrm{u,YM}_{23}$ signal model in SR-HM-Disc. Due to the limited statistical power of the signal samples, efficiencies can fluctuate and can drop to zero.

Acceptance times efficiency across the SUSY signal grid for SR-Comp-1c.

Acceptance times efficiency across the SUSY signal grid for SR-HM1.

Acceptance times efficiency across the SUSY signal grid for SR-HM2.

Acceptance times efficiency across the SUSY signal grid for SR-HM3.

Acceptance times efficiency across the SUSY signal grid for SR-HM-Disc.

Acceptance times efficiency across the SUSY signal grid for SR-Comp1.

Acceptance times efficiency across the SUSY signal grid for SR-Comp2.

Acceptance times efficiency across the SUSY signal grid for SR-Comp3.

Acceptance times efficiency across the $\mathrm{LQ}^\mathrm{u}_{21}$ signal grid for SR-HM1.

Acceptance times efficiency across the $\mathrm{LQ}^\mathrm{u}_{21}$ signal grid for SR-HM2.

Acceptance times efficiency across the $\mathrm{LQ}^\mathrm{u}_{21}$ signal grid for SR-HM3.

Acceptance times efficiency across the $\mathrm{LQ}^\mathrm{u}_{21}$ signal grid for SR-HM-Disc.

Acceptance times efficiency across the $\mathrm{LQ}^\mathrm{u}_{22}$ signal grid for SR-HM1.

Acceptance times efficiency across the $\mathrm{LQ}^\mathrm{u}_{22}$ signal grid for SR-HM2.

Acceptance times efficiency across the $\mathrm{LQ}^\mathrm{u}_{22}$ signal grid for SR-HM3.

Acceptance times efficiency across the $\mathrm{LQ}^\mathrm{u}_{22}$ signal grid for SR-HM-Disc.

Acceptance times efficiency for the $\mathrm{vLQ}^\mathrm{u,min}_{23}$ signal model in SR-HM1.

Acceptance times efficiency for the $\mathrm{vLQ}^\mathrm{u,min}_{23}$ signal model in SR-HM2.

Acceptance times efficiency for the $\mathrm{vLQ}^\mathrm{u,min}_{23}$ signal model in SR-HM3.

Acceptance times efficiency for the $\mathrm{vLQ}^\mathrm{u,min}_{23}$ signal model in SR-HM-Disc.

Acceptance times efficiency for the $\mathrm{vLQ}^\mathrm{u,YM}_{23}$ signal model in SR-HM1.

Acceptance times efficiency for the $\mathrm{vLQ}^\mathrm{u,YM}_{23}$ signal model in SR-HM2.

Acceptance times efficiency for the $\mathrm{vLQ}^\mathrm{u,YM}_{23}$ signal model in SR-HM3.

Acceptance times efficiency for the $\mathrm{vLQ}^\mathrm{u,YM}_{23}$ signal model in SR-HM-Disc.

Cutflow table for SR-Comp-1c using the $m(\tilde{t}_{1},\tilde{\chi}_{1}^{0}) = (450,430)$ GeV signal point as the benchmark. All jet-related variables use jets with $p_\mathrm{T}>20$ GeV. The "Preselection" requirement includes: $E_\mathrm{T}^\mathrm{miss}>250$ GeV; events containing electrons or muons are vetoed; at least two jets must be present of which at least one must be identified as a $c$-tagged jet; events with jets that have been identified as $b$-tagged are discarded; the minimum azimuthal angular ($\phi$) distance between the (up to) four leading jets and the $\vec{p}_\mathrm{T}^\mathrm{miss}$ is required to be greater than 0.4.

Cutflow table for SR-Comp1 using the $m(\tilde{t}_{1},\tilde{\chi}_{1}^{0}) = (600,550)$ GeV signal point as the benchmark. All jet-related variables use jets with $p_\mathrm{T}>20$ GeV. The "Preselection" requirement includes: $E_\mathrm{T}^\mathrm{miss}>250$ GeV; events containing electrons or muons are vetoed; at least two jets must be present of which at least one must be identified as a $c$-tagged jet; events with jets that have been identified as $b$-tagged are discarded; the minimum azimuthal angular ($\phi$) distance between the (up to) four leading jets and the $\vec{p}_\mathrm{T}^\mathrm{miss}$ is required to be greater than 0.4.

Cutflow table for SR-Comp2 using the $m(\tilde{t}_{1},\tilde{\chi}_{1}^{0}) = (550,470)$ GeV signal point as the benchmark. All jet-related variables use jets with $p_\mathrm{T}>20$ GeV. The "Preselection" requirement includes: $E_\mathrm{T}^\mathrm{miss}>250$ GeV; events containing electrons or muons are vetoed; at least two jets must be present of which at least one must be identified as a $c$-tagged jet; events with jets that have been identified as $b$-tagged are discarded; the minimum azimuthal angular ($\phi$) distance between the (up to) four leading jets and the $\vec{p}_\mathrm{T}^\mathrm{miss}$ is required to be greater than 0.4.

Cutflow table for SR-Comp3 using the $m(\tilde{t}_{1},\tilde{\chi}_{1}^{0}) = (550,375)$ GeV signal point as the benchmark. All jet-related variables use jets with $p_\mathrm{T}>20$ GeV. The "Preselection" requirement includes: $E_\mathrm{T}^\mathrm{miss}>250$ GeV; events containing electrons or muons are vetoed; at least two jets must be present of which at least one must be identified as a $c$-tagged jet; events with jets that have been identified as $b$-tagged are discarded; the minimum azimuthal angular ($\phi$) distance between the (up to) four leading jets and the $\vec{p}_\mathrm{T}^\mathrm{miss}$ is required to be greater than 0.4.

Cutflow table for SR-HM1 using the $m(\tilde{t}_{1},\tilde{\chi}_{1}^{0}) = (1000,1)$ GeV signal point as the benchmark. All jet-related variables use jets with $p_\mathrm{T}>40$ GeV, however, the $E_\mathrm{T}^\mathrm{miss}$ is calculated with jets with $p_\mathrm{T}>20$ GeV. The "Preselection" requirement includes: $E_\mathrm{T}^\mathrm{miss}>250$ GeV; events containing electrons or muons are vetoed; at least two jets must be present of which at least one must be identified as a $c$-tagged jet; events with jets that have been identified as $b$-tagged are discarded; the minimum azimuthal angular ($\phi$) distance between the (up to) four leading jets and the $\vec{p}_\mathrm{T}^\mathrm{miss}$ is required to be greater than 0.4.

Cutflow table for SR-HM2 using the $m(\tilde{t}_{1},\tilde{\chi}_{1}^{0}) = (750,450)$ GeV signal point as the benchmark. All jet-related variables use jets with $p_\mathrm{T}>40$ GeV, however, the $E_\mathrm{T}^\mathrm{miss}$ is calculated with jets with $p_\mathrm{T}>20$ GeV. The "Preselection" requirement includes: $E_\mathrm{T}^\mathrm{miss}>250$ GeV; events containing electrons or muons are vetoed; at least two jets must be present of which at least one must be identified as a $c$-tagged jet; events with jets that have been identified as $b$-tagged are discarded; the minimum azimuthal angular ($\phi$) distance between the (up to) four leading jets and the $\vec{p}_\mathrm{T}^\mathrm{miss}$ is required to be greater than 0.4.

Cutflow table for SR-HM3 using the $m(\tilde{t}_{1},\tilde{\chi}_{1}^{0}) = (750,450)$ GeV signal point as the benchmark. All jet-related variables use jets with $p_\mathrm{T}>40$ GeV, however, the $E_\mathrm{T}^\mathrm{miss}$ is calculated with jets with $p_\mathrm{T}>20$ GeV. The "Preselection" requirement includes: $E_\mathrm{T}^\mathrm{miss}>250$ GeV; events containing electrons or muons are vetoed; at least two jets must be present of which at least one must be identified as a $c$-tagged jet; events with jets that have been identified as $b$-tagged are discarded; the minimum azimuthal angular ($\phi$) distance between the (up to) four leading jets and the $\vec{p}_\mathrm{T}^\mathrm{miss}$ is required to be greater than 0.4.

Cutflow table for SR-HM-Disc using the $m(\tilde{t}_{1},\tilde{\chi}_{1}^{0}) = (750,450)$ GeV signal point as the benchmark. All jet-related variables use jets with $p_\mathrm{T}>40$ GeV, however, the $E_\mathrm{T}^\mathrm{miss}$ is calculated with jets with $p_\mathrm{T}>20$ GeV. The "Preselection" requirement includes: $E_\mathrm{T}^\mathrm{miss}>250$ GeV; events containing electrons or muons are vetoed; at least two jets must be present of which at least one must be identified as a $c$-tagged jet; events with jets that have been identified as $b$-tagged are discarded; the minimum azimuthal angular ($\phi$) distance between the (up to) four leading jets and the $\vec{p}_\mathrm{T}^\mathrm{miss}$ is required to be greater than 0.4.

Cutflow table for SR-HM1 using the $m(\mathrm{LQ}_{21}^\mathrm{u}) = 600$ GeV signal point, with a 50% branching fraction to $c\nu$, as the benchmark. All jet-related variables use jets with $p_\mathrm{T}>40$ GeV, however, the $E_\mathrm{T}^\mathrm{miss}$ is calculated with jets with $p_\mathrm{T}>20$ GeV. The "Preselection" requirement includes: $E_\mathrm{T}^\mathrm{miss}>250$ GeV; events containing electrons or muons are vetoed; at least two jets must be present of which at least one must be identified as a $c$-tagged jet; events with jets that have been identified as $b$-tagged are discarded; the minimum azimuthal angular ($\phi$) distance between the (up to) four leading jets and the $\vec{p}_\mathrm{T}^\mathrm{miss}$ is required to be greater than 0.4.

Cutflow table for SR-HM2 using the $m(\mathrm{LQ}_{21}^\mathrm{u}) = 600$ GeV signal point, with a 50% branching fraction to $c\nu$, as the benchmark. All jet-related variables use jets with $p_\mathrm{T}>40$ GeV, however, the $E_\mathrm{T}^\mathrm{miss}$ is calculated with jets with $p_\mathrm{T}>20$ GeV. The "Preselection" requirement includes: $E_\mathrm{T}^\mathrm{miss}>250$ GeV; events containing electrons or muons are vetoed; at least two jets must be present of which at least one must be identified as a $c$-tagged jet; events with jets that have been identified as $b$-tagged are discarded; the minimum azimuthal angular ($\phi$) distance between the (up to) four leading jets and the $\vec{p}_\mathrm{T}^\mathrm{miss}$ is required to be greater than 0.4.

Cutflow table for SR-HM3 using the $m(\mathrm{LQ}_{21}^\mathrm{u}) = 600$ GeV signal point, with a 50% branching fraction to $c\nu$, as the benchmark. All jet-related variables use jets with $p_\mathrm{T}>40$ GeV, however, the $E_\mathrm{T}^\mathrm{miss}$ is calculated with jets with $p_\mathrm{T}>20$ GeV. The "Preselection" requirement includes: $E_\mathrm{T}^\mathrm{miss}>250$ GeV; events containing electrons or muons are vetoed; at least two jets must be present of which at least one must be identified as a $c$-tagged jet; events with jets that have been identified as $b$-tagged are discarded; the minimum azimuthal angular ($\phi$) distance between the (up to) four leading jets and the $\vec{p}_\mathrm{T}^\mathrm{miss}$ is required to be greater than 0.4.

Cutflow table for SR-HM-Disc using the $m(\mathrm{LQ}_{21}^\mathrm{u}) = 600$ GeV signal point, with a 50% branching fraction to $c\nu$, as the benchmark. All jet-related variables use jets with $p_\mathrm{T}>40$ GeV, however, the $E_\mathrm{T}^\mathrm{miss}$ is calculated with jets with $p_\mathrm{T}>20$ GeV. The "Preselection" requirement includes: $E_\mathrm{T}^\mathrm{miss}>250$ GeV; events containing electrons or muons are vetoed; at least two jets must be present of which at least one must be identified as a $c$-tagged jet; events with jets that have been identified as $b$-tagged are discarded; the minimum azimuthal angular ($\phi$) distance between the (up to) four leading jets and the $\vec{p}_\mathrm{T}^\mathrm{miss}$ is required to be greater than 0.4.