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.