Measured differential cross section as a function of observable $ \Delta R (l,l)$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ N_{jets}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet1}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet2}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet2}/p_{T}^{Jet1}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ m_{jj}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ m_{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ H_{T}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{\gamma} / \sqrt{H_{T}}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \Delta \phi (Jet,\gamma)$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \phi_{CS}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \cos \theta_{CS}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{\gamma} / \sqrt{H_{T}}$ (Fig. 8 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ H_{T}$ (Fig. 8 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \Delta \phi (Jet,\gamma)$ (Fig. 8 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \Delta R (l,l)$ (Fig. 5 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma}$ (Fig. 5 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } p_{T}^{ll} + p_{T}^{\gamma} < 200 GeV$ (Fig. 11 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } 200 GeV < p_{T}^{ll} + p_{T}^{\gamma} < 300 GeV$ (Fig. 11 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } p_{T}^{ll} + p_{T}^{\gamma} > 300 GeV$ (Fig. 11 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ m_{jj}$ (Fig. 7 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ m_{ll\gamma j}$ (Fig. 7 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ N_{jets}$ (Fig. 6 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet1}$ (Fig. 6 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet2}$ (Fig. 6 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet2}/p_{T}^{Jet1}$ (Fig. 6 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll}$ (Fig. 5 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j}$ (Fig. 8 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } p_{T}^{ll\gamma} < 50 GeV$ (Fig. 12 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } 50 GeV < p_{T}^{ll\gamma} < 75 GeV$ (Fig. 12 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } p_{T}^{ll\gamma} > 75 GeV$ (Fig. 12 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } 125 GeV < m_{ll\gamma} < 200 GeV$ (Fig. 10 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } 200 GeV < m_{ll\gamma} < 300 GeV$ (Fig. 10 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } m_{ll\gamma} > 300 GeV$ (Fig. 10 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} + p_{T}^{\gamma}$ (Fig. 5 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \cos \theta_{CS}$ (Fig. 9 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \phi_{CS}$ (Fig. 9 (a))

Correlation matrix of all the parameters including nuisance parameters used in the profile likelihood unfolding fit on $A_{C}$.

The observed 95&#37; CL exclusion limits as a function of &kappa;_2V (obtained using the signal strength &mu;_VBF as the POI) from the combined ggF and VBF signal regions, as shown by the solid black line. The value of &kappa;_&lambda; is fixed to 1. The blue and yellow bands show respectively the 1&sigma; and 2&sigma; 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 &kappa;_2V.

The observed 95&#37; CL exclusion limit obtained using the signal strength &mu;_ggF+VBF as the POI in the two-dimensional &kappa;_&lambda; vs. &kappa;_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 1&sigma; and 2&sigma; bands around the expected exclusion limits, which are shown by the dashed black line. The star denotes the SM prediction (&kappa;_&lambda;=κ_2V=1). The displayed values are in units of $\mu_{ggF}$.

The expected and observed profile likelihood ratio scans for &kappa;_&lambda; coupling modifier, shown by the solid black line, using the coupling modifier as the POIs. The value of &kappa;_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 2&sigma; exclusion boundary.

The expected and observed profile likelihood ratio scans for the &kappa;_2V coupling modifier, shown by the solid black line, using the coupling modifier as the POIs. The value of &kappa;_&lambda; 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 2&sigma; exclusion boundary.

The observed profile likelihood ratio exclusion limits for the two-dimensional &kappa;_&lambda; vs. &kappa;_2V modifier space, shown by the solid dark purple line at the 1&sigma; level and the dashed turquoise line at the 2&sigma; level. The black cross denotes the best-fit values of (&kappa;_&lambda;,&kappa;_2V). For both the expected and observed limit plots, the black star indicates the SM prediction (&kappa;_&lambda;=κ_2V=1).

The expected profile likelihood ratio exclusion limits for the two-dimensional &kappa;_&lambda; vs. &kappa;_2V modifier space, where the solid pink line denotes the 1&sigma;-level exclusion and the dashed orange line denotes the 2&sigma;-level exclusion. The black cross denotes the best-fit values of (&kappa;_&lambda;,&kappa;_2V). For both the expected and observed limit plots, the black star indicates the SM prediction (&kappa;_&lambda;=κ_2V=1).

The observed 95&#37; 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&#37; CL exclusion limits. The shaded blue band indicates the &plusmn; 1&sigma; uncertainty of the exclusion limits, while the yellow band indicates the &plusmn; 2&sigma; 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&#37; 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&#37; CL exclusion limits. The shaded blue band indicates the &plusmn; 1&sigma; uncertainty of the exclusion limits, while the yellow band indicates the &plusmn; 2&sigma; 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&#37; 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&#37; CL exclusion limits. The shaded blue band indicates the &plusmn; 1&sigma; uncertainty of the exclusion limits, while the yellow band indicates the &plusmn; 2&sigma; 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&#37; CL exclusion limits on the SMEFT coefficients in the two-dimensional spaces c_H&#9633; 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&#37; CL exclusion limits. The shaded blue band indicates the &plusmn; 1&sigma; uncertainty of the exclusion limits, while the yellow band indicates the &plusmn; 2&sigma; 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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 |&Delta;&eta;_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 &kappa;_&lambda;= 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&#37; CL exclusion limits as a function of the five relevant SMEFT coefficients: (a) c_H, (b) c_{H G}, (c) c_H&#9633;, (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 1&sigma; and 2&sigma; 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&#37; CL exclusion limits as a function of the five relevant SMEFT coefficients: (a) c_H, (b) c_{H G}, (c) c_H&#9633;, (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 1&sigma; and 2&sigma; 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&#37; CL exclusion limits as a function of the five relevant SMEFT coefficients: (a) c_H, (b) c_{H G}, (c) c_H&#9633;, (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 1&sigma; and 2&sigma; 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&#37; CL exclusion limits as a function of the five relevant SMEFT coefficients: (a) c_H, (b) c_{H G}, (c) c_H&#9633;, (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 1&sigma; and 2&sigma; 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&#37; CL exclusion limits as a function of the five relevant SMEFT coefficients: (a) c_H, (b) c_{H G}, (c) c_H&#9633;, (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 1&sigma; and 2&sigma; 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&#37; CL exclusion limits as a function of the two relevant HH HEFT coefficients: (a) c_tt&#772;HH 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 1&sigma; and 2&sigma; 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&#37; CL exclusion limits as a function of the two relevant HH HEFT coefficients: (a) c_tt&#772;HH 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 1&sigma; and 2&sigma; 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.

Event yields of the signal and SM background processes in the six analysis regions after the fit to the data under the $t \rightarrow uX$ hypothesis assuming $m_X = 30$ GeV. Total includes signal and background.The quoted uncertainties take into account correlations and constraints of the nuisance parameters and include both the statistical and systematic uncertainties. Negative correlations between the $t\bar{t} +$ light, $t\bar{t} + \geq1b$ and $t\bar{t} + \geq1c$ modelling uncertainties can make the uncertainty in the total yields smaller than in the individual components.

Event yields of the signal and SM background processes in the six analysis regions after the fit to the data under the $t \rightarrow cX$ hypothesis assuming $m_X = 30$ GeV. Total includes signal and background.The quoted uncertainties take into account correlations and constraints of the nuisance parameters and include both the statistical and systematic uncertainties. Negative correlations between the $t\bar{t} +$ light, $t\bar{t} + \geq1b$ and $t\bar{t} + \geq1c$ modelling uncertainties can make the uncertainty in the total yields smaller than in the individual components.

Event acceptance times efficiency in percent for every $t\rightarrow uX$ and $t\rightarrow cX$ mass signal sample.

Cut flow for the scalar signal in the $t\rightarrow uX$ decay combining both quark and anti-quark samples. Shown for each signal are the corresponding mass, the number of generated events, the number of reconstructed ("Reco") events, the events that pass the lepton triggers, the events that have only one electron ("el") or only one muon ("mu") with p$_{\text{T}}$ larger than 27 GeV, the number of events with at least four jets with p$_{\text{T}}$ larger than 25 GeV, the number of events with at least three $b$-tagged jets at the 70% efficiency working point, and the number of events with at least two $b$-tagged jets at the 60% efficiency working point and at least another one at the 70%. The quoted yields do not include reweighting.

Cut flow for the scalar signal in the $t\rightarrow cX$ decay combining both quark and anti-quark samples. Shown for each signal are the corresponding mass, the number of generated events, the number of reconstructed ("Reco") events, the events that pass the lepton triggers, the events that have only one electron ("el") or only one muon ("mu") with p$_{\text{T}}$ larger than 27 GeV, the number of events with at least four jets with p$_{\text{T}}$ larger than 25 GeV, the number of events with at least three $b$-tagged jets at the 70% efficiency working point, and the number of events with at least two $b$-tagged jets at the 60% efficiency working point and at least another one at the 70%. The quoted yields do not include reweighting.

Normalisation factors for the major background processes and ttW ($\Delta \eta < 0$) from the fit using only statistical uncertainties (fixing Nuisance Parameters (NP) to their fitted values) to data in all analysis regions.

Normalisation factors for the major background processes and ttW ($\Delta \eta < 0$) from the fit using using both statistical and systematic uncertainties to data in all analysis regions.

Correlation matrix between the Normalisation Factors in the fit using only statistical uncertainties (fixing Nuisance Parameters (NP) to their fitted values) to data in all analysis regions.

The most relevant systematic uncertainties ranked by their impact on the leptonic charge asymmetry ($A_c^{\ell}$) parameter at reconstructed level. The impact of the uncertainties is shown before and after the combined profile-likelihood fit to data in the signal and control regions. Pulls introduced by the fitting procedure are also shown. The entries shown in bold are the uncertainties of the freely floating background normalisations. ME stands for "matrix element", PS for "parton shower" and JER for "jet energy resolution". The gamma-uncertainties refer to the MC statistical uncertainties in a specific region and bin.

The most relevant systematic uncertainties ranked by their impact on the ttW Normalisation Factor ($\Delta \eta < 0$) parameter at reconstructed level. The impact of the uncertainties is shown before and after the combined profile-likelihood fit to data in the signal and control regions. Pulls introduced by the fitting procedure are also shown. ME stands for "matrix element", PS for "parton shower" and JER for "jet energy resolution". The gamma-uncertainties refer to the MC statistical uncertainties in a specific region and bin.

The predicted and observed numbers of events in the control and signal regions. The predictions are shown before the fit to data. The indicated uncertainties consider statistical as well as all experimental and theoretical systematic uncertainties. Background categories with event yields with a value of 1.0e-6 have a negligible contribution to the region and are manually set to that value.

The predicted and observed numbers of events in the control and signal regions. The predictions are shown after the fit to data. The indicated uncertainties consider statistical as well as all experimental and theoretical systematic uncertainties. Background categories with event yields with a value of 1.0e-6 have a negligible contribution to the region and are manually set to that value.

Measured differential fiducial cross section for $p_{T}^{\ell\ell}$ in the 0+1-jet fiducial region using the regularized in-likelihood unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $\Delta\phi_{\ell\ell}$ in the 0+1-jet fiducial region using the regularized in-likelihood unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $p_{T}^{\ell 0}$ in the 0+1-jet fiducial region using the regularized in-likelihood unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $\cos\theta^{*}$ in the 0+1-jet fiducial region using the regularized in-likelihood unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $|Y_{j0}|$ in the 0+1-jet fiducial region using the regularized in-likelihood unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $m_{\ell\ell}$ versus $N_{jet}$ in the 0-jet and 1-jet fiducial region using the regularized in-likelihood unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $\Delta\phi_{\ell\ell}$ versus $N_{jet}$ in the 0-jet and 1-jet fiducial region using the regularized in-likelihood unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $Y_{\ell\ell}$ versus $N_{jet}$ in the 0-jet and 1-jet fiducial region using the regularized in-likelihood unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $p_{T}^{\ell\ell}$ versus $N_{jet}$ in the 0-jet and 1-jet fiducial region using the regularized in-likelihood unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $p_{T}^{\ell 0}$ versus $N_{jet}$ in the 0-jet and 1-jet fiducial region using the regularized in-likelihood unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $\cos\theta^{*}$ versus $N_{jet}$ in the 0-jet and 1-jet fiducial region using the regularized in-likelihood unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $p_{T}^{H}$ in the 0+1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $m_{\ell\ell}$ in the 0+1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $Y_{\ell\ell}$ in the 0+1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $p_{T}^{\ell\ell}$ in the 0+1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $\Delta\phi_{\ell\ell}$ in the 0+1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $p_{T}^{\ell 0}$ in the 0+1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $\cos\theta^{*}$ in the 0+1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $|Y_{j0}|$ in the 0+1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $m_{\ell\ell}$ versus $N_{jet}$ in the 0-jet and 1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $\Delta\phi_{\ell\ell}$ versus $N_{jet}$ in the 0-jet and 1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $Y_{\ell\ell}$ versus $N_{jet}$ in the 0-jet and 1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $p_{T}^{\ell\ell}$ versus $N_{jet}$ in the 0-jet and 1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $p_{T}^{\ell 0}$ versus $N_{jet}$ in the 0-jet and 1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Measured differential fiducial cross section for $\cos\theta^{*}$ versus $N_{jet}$ in the 0-jet and 1-jet fiducial region using the iterative Bayesian unfolding method. The quoted uncertainties include statistical and systematic uncertainties from experimental and theory sources as well as background normalization effects and shape effects from background and signal.

Migration Matrices for $m_{\ell\ell}$

Migration Matrices for $p_{T}^{H}$

Migration Matrices for $Y_{\ell\ell}$

Migration Matrices for $p_{T}^{\ell\ell}$

Migration Matrices for $p_{T}^{\ell 0}$

Migration Matrices for $\cos\theta^{*} $

Migration Matrices for $\Delta\phi_{\ell\ell}$

Migration Matrices for $|Y_{j0}|$

Migration Matrices for $M_{\ell\ell} $ versus $ N_{jet}$

Migration Matrices for $Y_{\ell\ell} $ versus $ N_{jet}$

Migration Matrices for $p_{T}^{\ell\ell} $ versus $ N_{jet}$

Migration Matrices for $p_{T}^{\ell 0} $ versus $ N_{jet}$

Migration Matrices for $\cos\theta^{*} $ versus $ N_{jet}$

Migration Matrices for $\Delta\phi_{\ell\ell} $ versus $ N_{jet}$

Correlation Matrices for observed cross-sections for $m_{\ell\ell}$

Correlation Matrices for observed cross-sections for $p_{T}^{H}$

Correlation Matrices for observed cross-sections for $Y_{\ell\ell}$

Correlation Matrices for observed cross-sections for $p_{T}^{\ell\ell}$

Correlation Matrices for observed cross-sections for $p_{T}^{\ell 0}$

Correlation Matrices for observed cross-sections for $\cos\theta^{*} $

Correlation Matrices for observed cross-sections for $\Delta\phi_{\ell\ell}$

Correlation Matrices for observed cross-sections for $|Y_{j0}|$

Correlation Matrices for observed cross-sections for $M_{\ell\ell} $ versus $ N_{jet}$

Correlation Matrices for observed cross-sections for $Y_{\ell\ell} $ versus $ N_{jet}$

Correlation Matrices for observed cross-sections for $p_{T}^{\ell\ell} $ versus $ N_{jet}$

Correlation Matrices for observed cross-sections for $p_{T}^{\ell 0} $ versus $ N_{jet}$

Correlation Matrices for observed cross-sections for $\cos\theta^{*} $ versus $ N_{jet}$

Correlation Matrices for observed cross-sections for $\Delta\phi_{\ell\ell} $ versus $ N_{jet}$

Distributions of $p_{T}^{Z_1}$. Small background contributions are denoted as "other backgrounds", including 4$\mu$ events containing non-prompt muons estimated from data and from $ttV$, $VVV$, and Higgs boson production processes.

Distributions of $p_{T}^{Z_2}$. Small background contributions are denoted as "other backgrounds", including 4$\mu$ events containing non-prompt muons estimated from data and from $ttV$, $VVV$, and Higgs boson production processes.

Distributions of the mass difference of the $Z_1$ and $Z_2$ candidates. Small background contributions are denoted as "other backgrounds", including 4$\mu$ events containing non-prompt muons estimated from data and from $ttV$, $VVV$, and Higgs boson production processes.

The pDNN output discriminant variable distributions for low mass with a signal sample at 35 GeV and 51 GeV, respectively.

The pDNN output discriminant variable distributions for high mass with a signal sample at 35 GeV and 51 GeV, respectively.

Mass spectra of $m_{Z2}$ for the pDNN-selected events with a signal sample at 15 GeV.

Mass spectra of $m_{Z1}$ for the pDNN-selected events with a signal sample at 51 GeV.

The $p_0$-value scan across the Z' mass signal regions.

95% CL upper limits (expected and observed) on the cross-sections times branching fraction. The discontinuity at 42 GeV represents the border of the low/high mass classifiers.

95% CL upper limits (expected and observed) on the coupling parameter. The discontinuity at 42 GeV represents the border of the low/high mass classifiers.

The parameterized mass resolution $\sigma_{m_{\mu\mu}}$ as a function of $m_{Z'}$ using fully simulated $Z' \rightarrow \mu^+\mu^-$ events.

The transverse momentum $p_{T}$ distributions for each muon (ordered with $p_{T}$ from (a) to (d)). In addition to the major background from the SM $Z(Z^*)\rightarrow 4\mu$ production, other backgrounds, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

The transverse momentum $p_{T}$ distributions for each muon (ordered with $p_{T}$ from (a) to (d)). In addition to the major background from the SM $Z(Z^*)\rightarrow 4\mu$ production, other backgrounds, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

The transverse momentum $p_{T}$ distributions for each muon (ordered with $p_{T}$ from (a) to (d)). In addition to the major background from the SM $Z(Z^*)\rightarrow 4\mu$ production, other backgrounds, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

The transverse momentum $p_{T}$ distributions for each muon (ordered with $p_{T}$ from (a) to (d)). In addition to the major background from the SM $Z(Z^*)\rightarrow 4\mu$ production, other backgrounds, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

Kinematic distributions of the pre-selected $4\mu$ events. The plots (a) to (d) are the $\eta$ distributions of the 4 muons ($p_{T}$ ordered). In addition to the major background from the SM $Z(Z^*)\rightarrow 4\mu$ production, other backgrounds, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

Kinematic distributions of the pre-selected $4\mu$ events. The plots (a) to (d) are the $\eta$ distributions of the 4 muons ($p_{T}$ ordered). In addition to the major background from the SM $Z(Z^*)\rightarrow 4\mu$ production, other backgrounds, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

Kinematic distributions of the pre-selected $4\mu$ events. The plots (a) to (d) are the $\eta$ distributions of the 4 muons ($p_{T}$ ordered). In addition to the major background from the SM $Z(Z^*)\rightarrow 4\mu$ production, other backgrounds, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

Kinematic distributions of the pre-selected $4\mu$ events. The plots (a) to (d) are the $\eta$ distributions of the 4 muons ($p_{T}$ ordered). In addition to the major background from the SM $Z(Z^*)\rightarrow 4\mu$ production, other backgrounds, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

Kinematic distributions of the pre-selected $4\mu$ events. Plots (a) to (d) are the angular separations, $\Delta R$ of the two muons that formed $Z_1$ and $Z_2$, and the mass distributions of $Z_1$ and $Z_2$. In addition to the major backgrounds from the SM $Z(Z^*)\rightarrow 4\mu$ production, other background, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

Kinematic distributions of the pre-selected $4\mu$ events. Plots (a) to (d) are the angular separations, $\Delta R$ of the two muons that formed $Z_1$ and $Z_2$, and the mass distributions of $Z_1$ and $Z_2$. In addition to the major backgrounds from the SM $Z(Z^*)\rightarrow 4\mu$ production, other background, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

Kinematic distributions of the pre-selected $4\mu$ events. Plots (a) to (d) are the angular separations, $\Delta R$ of the two muons that formed $Z_1$ and $Z_2$, and the mass distributions of $Z_1$ and $Z_2$. In addition to the major backgrounds from the SM $Z(Z^*)\rightarrow 4\mu$ production, other background, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

Kinematic distributions of the pre-selected $4\mu$ events. Plots (a) to (d) are the angular separations, $\Delta R$ of the two muons that formed $Z_1$ and $Z_2$, and the mass distributions of $Z_1$ and $Z_2$. In addition to the major backgrounds from the SM $Z(Z^*)\rightarrow 4\mu$ production, other background, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

Data and MC comparison of the $Z \to 4\mu$ invariant mass using pre-selected 4$\mu$ events. Figure (b) shows the distribution between 80 GeV~and 110 GeV~in Figure (a). Figure (c) shows the distribution of transverse momentum of $4\mu$ system. In addition to the major background from the SM $Z(Z^*)\rightarrow 4\mu$ production, other backgrounds, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

Data and MC comparison of the $Z \to 4\mu$ invariant mass using pre-selected 4$\mu$ events. Figure (b) shows the distribution between 80 GeV~and 110 GeV~in Figure (a). Figure (c) shows the distribution of transverse momentum of $4\mu$ system. In addition to the major background from the SM $Z(Z^*)\rightarrow 4\mu$ production, other backgrounds, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

Data and MC comparison of the $Z \to 4\mu$ invariant mass using pre-selected 4$\mu$ events. Figure (b) shows the distribution between 80 GeV~and 110 GeV~in Figure (a). Figure (c) shows the distribution of transverse momentum of $4\mu$ system. In addition to the major background from the SM $Z(Z^*)\rightarrow 4\mu$ production, other backgrounds, including 4$\mu$ events containing non-prompt muons estimated from data, and from $ttV$, $VVV$, and Higgs boson production processes, are included in the plots. Examples of the Z' signal from $pp\rightarrow Z'\mu^+\mu^- \rightarrow 4\mu$ process with masses of 15 and 51 GeV are also shown in the plots.

Particle-level TEEC results for the third HT2 bin

Particle-level TEEC results for the fourth HT2 bin

Particle-level TEEC results for the fifth HT2 bin

Particle-level TEEC results for the sixth HT2 bin

Particle-level TEEC results for the seventh HT2 bin

Particle-level TEEC results for the eighth HT2 bin

Particle-level TEEC results for the ninth HT2 bin

Particle-level TEEC results for the tenth HT2 bin

Particle-level ATEEC results

Particle-level ATEEC results for the first HT2 bin

Particle-level ATEEC results for the second HT2 bin

Particle-level ATEEC results for the third HT2 bin

Particle-level ATEEC results for the fourth HT2 bin

Particle-level ATEEC results for the fifth HT2 bin

Particle-level ATEEC results for the sixth HT2 bin

Particle-level ATEEC results for the seventh HT2 bin

Particle-level ATEEC results for the eighth HT2 bin

Particle-level ATEEC results for the ninth HT2 bin

Particle-level ATEEC results for the tenth HT2 bin

Particle-level TEEC predictions

Particle-level TEEC predictions for the first HT2 bin

Particle-level TEEC predictions for the second HT2 bin

Particle-level TEEC predictions for the third HT2 bin

Particle-level TEEC predictions for the fourth HT2 bin

Particle-level TEEC predictions for the fifth HT2 bin

Particle-level TEEC predictions for the sixth HT2 bin

Particle-level TEEC predictions for the seventh HT2 bin

Particle-level TEEC predictions for the eighth HT2 bin

Particle-level TEEC predictions for the ninth HT2 bin

Particle-level TEEC predictions for the tenth HT2 bin

Particle-level ATEEC predictions

Particle-level ATEEC predictions for the first HT2 bin

Particle-level ATEEC predictions for the second HT2 bin

Particle-level ATEEC predictions for the third HT2 bin

Particle-level ATEEC predictions for the fourth HT2 bin

Particle-level ATEEC predictions for the fifth HT2 bin

Particle-level ATEEC predictions for the sixth HT2 bin

Particle-level ATEEC predictions for the seventh HT2 bin

Particle-level ATEEC predictions for the eighth HT2 bin

Particle-level ATEEC predictions for the ninth HT2 bin

Particle-level ATEEC predictions for the tenth HT2 bin

Fitted values for the strong coupling constant extracted from TEEC with MMHT 2014 PDF

Fitted values for the strong coupling constant extracted from TEEC with NNPDF 3.0

Fitted values for the strong coupling constant extracted from TEEC with CT14 PDF

Fitted values for the strong coupling constant extracted from ATEEC with MMHT 2014 PDF

Fitted values for the strong coupling constant extracted from ATEEC with NNPDF 3.0

Fitted values for the strong coupling constant extracted from ATEEC with CT14 PDF

Comparison between data and background prediction before the fit (Pre-Fit) for the mass of the FCNC top-quark candidate in SR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The four FCNC LH signals are also shown separately, normalized to five times the cross-section corresponding to the most stringent observed branching ratio limits. The first (last) bin in all distributions includes the underflow (overflow). The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction before the fit (Pre-Fit) for the mass of the SM top-quark candidate in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The four FCNC LH signals are also shown separately, normalized to five times the cross-section corresponding to the most stringent observed branching ratio limits. The first (last) bin in all distributions includes the underflow (overflow). The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction before the fit (Pre-Fit) for the transverse momentum of the Z boson candidate in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The four FCNC LH signals are also shown separately, normalized to five times the cross-section corresponding to the most stringent observed branching ratio limits. The first (last) bin in all distributions includes the underflow (overflow). The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{1}$ discriminant in the mass sideband CR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{2}^{u}$ discriminant in the mass sideband CR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{1}$ discriminant in SR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{2}^{u}$ discriminant in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{1}$ discriminant in the mass sideband CR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{2}^{c}$ discriminant in the mass sideband CR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{1}$ discriminant in SR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{2}^{c}$ discriminant in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the leading lepton $p_{T}$ in the $t\bar{t}$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The last bin includes the overflow. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the third lepton $p_{T}$ in the $t\bar{t}$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The last bin includes the overflow. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the leading lepton $p_{T}$ in the $t\bar{t}Z$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The last bin includes the overflow. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{1}$ discriminant in the $t\bar{t}Z$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).