CMS-B2G-20-009

CMS-B2G-20-009 ; CERN-EP-2022-152
Search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state in proton-proton collisions at $ \sqrt{s}= $ 13 TeV
CMS Collaboration
30 September 2022
Phys. Lett. B 844 (2023) 137813
Abstract: A search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state is presented. The analysis is based on proton-proton collision data recorded by the CMS detector in 2016-2018 at a centre-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 138 fb$^{-1}$. The search is sensitive to resonances with masses above 1.3 TeV, decaying to bosons that are highly Lorentz-boosted such that each of the bosons forms a single large-radius jet. Machine learning techniques are employed to identify such jets. No significant excess over the estimated standard model background is observed. A maximum local significance of 3.6 standard deviations, corresponding to a global significance of 2.3 standard deviations, is observed at masses of 2.1 and 2.9 TeV. In a heavy vector triplet model, spin-1 Z' and W' resonances with masses below 4.8 TeV are excluded at the 95% confidence level (CL). These limits are the most stringent to date. In a bulk graviton model, spin-2 gravitons and spin-0 radions with masses below 1.4 and 2.7 TeV, respectively, are excluded at 95% CL. Production of heavy resonances through vector boson fusion is constrained with upper cross section limits at 95% CL as low as 0.1 fb.
Links: e-print arXiv:2210.00043 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; HepData record ; Physics Briefing ; CADI line (restricted) ;

Figures & Tables	Summary	Additional Figures	References	CMS Publications

Figures
png pdf	Figure 1: Feynman diagrams of the signal processes ggF or DY produced (upper) and VBF produced (lower): (left) graviton or radion decaying to WW or ZZ; (center) Z' and W' decaying to ZH and WH, respectively; (right) Z' and W' decaying to WW and WZ, respectively.
png pdf	Figure 1-a: Example Feynman diagram of signal process: DY produced graviton or radion decaying to WW or ZZ.
png pdf	Figure 1-b: Example Feynman diagram of signal process: DY produced Z' and W' decaying to ZH and WH, respectively.
png pdf	Figure 1-c: Example Feynman diagram of signal process: DY produced Z' and W' decaying to WW and WZ, respectively.
png pdf	Figure 1-d: Example Feynman diagram of signal process: VBF produced graviton or radion decaying to WW or ZZ.
png pdf	Figure 1-e: Example Feynman diagram of signal process: VBF produced Z' and W' decaying to ZH and WH, respectively.
png pdf	Figure 1-f: Example Feynman diagram of signal process: VBF produced Z' and W' decaying to WW and WZ, respectively.
png pdf	Figure 2: Distributions of $ m_\mathrm{jj}^{ \mathrm{AK8} } $ (left) and $ m_\text{jet1}^{ \mathrm{AK8} } $ (right) in the nominal QCD multijet simulation using PYTHIA 8 (black markers) and three-dimensional templates (black solid line) in the DY/ggF VH HPHP category. Superimposed are the normalized up and down variations of five alternative shapes corresponding to shape nuisance parameters in the fit model. Each of the variations has a characteristic dependence on $ m_\text{jet}^{ \mathrm{AK8} } $ to allow the necessary flexibility in the fit for the template to adapt to the data. We also allow an overall variation of the rate in the fit.
png pdf	Figure 2-a: Distribution of $ m_\mathrm{jj}^{ \mathrm{AK8} } $ in the nominal QCD multijet simulation using PYTHIA 8 (black markers) and three-dimensional templates (black solid line) in the DY/ggF VH HPHP category. Superimposed are the normalized up and down variations of five alternative shapes corresponding to shape nuisance parameters in the fit model. Each of the variations has a characteristic dependence on $ m_\text{jet}^{ \mathrm{AK8} } $ to allow the necessary flexibility in the fit for the template to adapt to the data. We also allow an overall variation of the rate in the fit.
png pdf	Figure 2-b: Distribution of $ m_\text{jet1}^{ \mathrm{AK8} } $ in the nominal QCD multijet simulation using PYTHIA 8 (black markers) and three-dimensional templates (black solid line) in the DY/ggF VH HPHP category. Superimposed are the normalized up and down variations of five alternative shapes corresponding to shape nuisance parameters in the fit model. Each of the variations has a characteristic dependence on $ m_\text{jet}^{ \mathrm{AK8} } $ to allow the necessary flexibility in the fit for the template to adapt to the data. We also allow an overall variation of the rate in the fit.
png pdf	Figure 3: Comparison between the background post-fit and the data distributions of $ m_\mathrm{jj}^{ \mathrm{AK8} } $ (left) and $ m_\text{jet1}^{ \mathrm{AK8} } $ (right) in the DY/ggF VH HPHP category. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are represented as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor of 20. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Figure 3-a: Comparison between the background post-fit and the data distributions of $ m_\mathrm{jj}^{ \mathrm{AK8} } $ in the DY/ggF VH HPHP category. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are represented as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor of 20. Shown below the plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Figure 3-b: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{ \mathrm{AK8} } $ in the DY/ggF VH HPHP category. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are represented as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor of 20. Shown below the plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Figure 4: Projections of the data and background post-fit distributions onto the $ m_\mathrm{jj}^{ \mathrm{AK8} } $ dimension in regions enriched in background ($ m_\text{jet1}^{\mathrm{AK8}} < $ 65 or $ > $140 GeV, and $ m_\text{jet2}^{\mathrm{AK8}} < $ 65 or $ > $140 GeV), for the HPHP VH (left) and VV (right) DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Figure 4-a: Projection of the data and background post-fit distributions onto the $ m_\mathrm{jj}^{ \mathrm{AK8} } $ dimension in regions enriched in background ($ m_\text{jet1}^{\mathrm{AK8}} < $ 65 or $ > $140 GeV, and $ m_\text{jet2}^{\mathrm{AK8}} < $ 65 or $ > $140 GeV), for the HPHP VH DY/ggF category. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below the plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Figure 4-b: Projection of the data and background post-fit distributions onto the $ m_\mathrm{jj}^{ \mathrm{AK8} } $ dimension in regions enriched in background ($ m_\text{jet1}^{\mathrm{AK8}} < $ 65 or $ > $140 GeV, and $ m_\text{jet2}^{\mathrm{AK8}} < $ 65 or $ > $140 GeV), for the HPHP VV DY/ggF category. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below the plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Figure 5: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{ \mathrm{AK8} } $ dimension in regions enriched in signal from DY/ggF VV ( 65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 105 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 105 GeV) for the HPHP VH (left) and VV (right) DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Figure 5-a: Projection of data and background post-fit distributions onto the $ m_\mathrm{jj}^{ \mathrm{AK8} } $ dimension in regions enriched in signal from DY/ggF VV ( 65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 105 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 105 GeV) for the HPHP VH DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid. Shown below the plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Figure 5-b: Projection of data and background post-fit distributions onto the $ m_\mathrm{jj}^{ \mathrm{AK8} } $ dimension in regions enriched in signal from DY/ggF VV ( 65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 105 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 105 GeV) for the HPHP VV DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid. Shown below the plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Figure 6: Distributions of the difference between the data and the background-only fit divided by the statistical uncertainty in the data. The total uncertainty in the background estimate fitted to data divided by the statistical uncertainty in the data is shown as a band. It should be noted that these two uncertainties are partially correlated. Three projections of the 3D phase space are shown in regions enriched in signal from DY/ggF VV (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 105 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 105 GeV) (upper left), DY/ggF VH (65 $ < m_\text{jet1/2}^{\mathrm{AK8}} < $ 105 GeV, 110 $ < m_\text{jet2/1}^{\mathrm{AK8}} < $ 140 GeV) (upper right) and VBF VV/VH (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 140 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 140 GeV) (lower). Examples of expected signal shapes added to the fit are overlaid, where the number of expected events is scaled by an arbitrary normalization factor stated in the legend.
png pdf	Figure 6-a: Distribution of the difference between the data and the background-only fit divided by the statistical uncertainty in the data. The total uncertainty in the background estimate fitted to data divided by the statistical uncertainty in the data is shown as a band. It should be noted that these two uncertainties are partially correlated. The projection of the 3D phase space is shown in the 65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 105 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 105 GeV region. Examples of expected signal shapes added to the fit are overlaid, where the number of expected events is scaled by an arbitrary normalization factor stated in the legend.
png pdf	Figure 6-b: Distribution of the difference between the data and the background-only fit divided by the statistical uncertainty in the data. The total uncertainty in the background estimate fitted to data divided by the statistical uncertainty in the data is shown as a band. It should be noted that these two uncertainties are partially correlated. The projection of the 3D phase space is shown in the DY/ggF VH (65 $ < m_\text{jet1/2}^{\mathrm{AK8}} < $ 105 GeV, 110 $ < m_\text{jet2/1}^{\mathrm{AK8}} < $ 140 GeV region. Examples of expected signal shapes added to the fit are overlaid, where the number of expected events is scaled by an arbitrary normalization factor stated in the legend.
png pdf	Figure 6-c: Distribution of the difference between the data and the background-only fit divided by the statistical uncertainty in the data. The total uncertainty in the background estimate fitted to data divided by the statistical uncertainty in the data is shown as a band. It should be noted that these two uncertainties are partially correlated. The projection of the 3D phase space is shown in the VBF VV/VH (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 140 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 140 GeV region. Examples of expected signal shapes added to the fit are overlaid, where the number of expected events is scaled by an arbitrary normalization factor stated in the legend.
png pdf	Figure 7: Observed and expected 95% CL upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ of data at $ \sqrt{s}= $ 13 TeV, for $ \text{Rad}\to\mathrm{V}\mathrm{V} $ (upper left), $ \mathrm{G}_{\text{bulk}}\to\mathrm{V}\mathrm{V} $ (upper right), HVT model B $ \mathrm{V}^\prime\to\mathrm{V}\mathrm{V} $+ VH (lower left), HVT model C $ \mathrm{V}^\prime\to\mathrm{V}\mathrm{V} $+ VH (lower right) signals. For each signal scenario the theoretical prediction and its uncertainty associated with the choice of PDF set is shown.
png pdf	Figure 7-a: Observed and expected 95% CL upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ of data at $ \sqrt{s}= $ 13 TeV, for $ \text{Rad}\to\mathrm{V}\mathrm{V} $ signals. The theoretical prediction and its uncertainty associated with the choice of PDF set is shown.
png pdf	Figure 7-b: Observed and expected 95% CL upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{G}_{\text{bulk}}\to\mathrm{V}\mathrm{V} $ signals. The theoretical prediction and its uncertainty associated with the choice of PDF set is shown.
png pdf	Figure 7-c: Observed and expected 95% CL upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ of data at $ \sqrt{s}= $ 13 TeV, for HVT model B $ \mathrm{V}^\prime\to\mathrm{V}\mathrm{V} $+ VH signals. The theoretical prediction and its uncertainty associated with the choice of PDF set is shown.
png pdf	Figure 7-d: Observed and expected 95% CL upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ of data at $ \sqrt{s}= $ 13 TeV, for HVT model C $ \mathrm{V}^\prime\to\mathrm{V}\mathrm{V} $+ VH signals. The theoretical prediction and its uncertainty associated with the choice of PDF set is shown.

Tables
png pdf	Table 1: Summary of the event category definitions. The categories are listed from the highest to the lowest sensitivity in each production mode. The percentages correspond to the maximum misidentification rate associated with the high (HP) and low (LP) purity working points.
png pdf	Table 2: Summary of the exclusion limits on the resonance masses for the considered models. The numbers show the lower limit at 95% CL, with the exception of the ones given in parentheses quoting the ranges of exclusion.

Summary

A search has been presented for resonances with masses above 1.3 TeV that decay to WW, WZ, ZZ, WH, or ZH boson pairs. Each of the two boson decays is clustered into one large-radius jet, yielding a dijet final state from Drell--Yan and gluon fusion production, complemented by two additional jets for vector boson fusion production. The hadronic decays of H, W, and Z bosons are identified using machine learning-based jet taggers that reduce the background from quantum chromodynamics multijet production. No evidence of a departure from the expected background is found. A maximum local significance of 3.6 standard deviations from the standard model prediction, corresponding to a global significance of 2.3 standard deviations, is observed at masses of 2.1 and 2.9 TeV. Upper limits at 95% confidence level on the resonance production cross section are set as a function of the resonance mass. In a heavy vector triplet model, spin-1 Z' and W' resonances with masses below 4.8 TeV are excluded. These limits are the most stringent to date. In a bulk graviton model, spin-2 gravitons and spin-0 radions with masses below 1.4 and 2.7 TeV, respectively, are excluded. Furthermore, the exclusive production of new heavy resonances through the vector boson fusion mode is constrained with upper cross section limits as low as 0.1 fb.

Additional Figures
png pdf	Additional Figure 1: Example Feynman diagrams of signal processes: (top left) $ \mathrm{g} \mathrm{g} $ produced graviton or radion decaying to WW or ZZ; (top center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively; (top right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom left) VBF produced graviton or radion decaying to WW or ZZ; (bottom center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively. The diagrams on the top are shown in the paper as well, and are included here for convenience.
png pdf	Additional Figure 1-a: Example Feynman diagrams of signal processes: (top left) $ \mathrm{g} \mathrm{g} $ produced graviton or radion decaying to WW or ZZ; (top center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively; (top right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom left) VBF produced graviton or radion decaying to WW or ZZ; (bottom center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively. The diagrams on the top are shown in the paper as well, and are included here for convenience.
png pdf	Additional Figure 1-b: Example Feynman diagrams of signal processes: (top left) $ \mathrm{g} \mathrm{g} $ produced graviton or radion decaying to WW or ZZ; (top center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively; (top right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom left) VBF produced graviton or radion decaying to WW or ZZ; (bottom center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively. The diagrams on the top are shown in the paper as well, and are included here for convenience.
png pdf	Additional Figure 1-c: Example Feynman diagrams of signal processes: (top left) $ \mathrm{g} \mathrm{g} $ produced graviton or radion decaying to WW or ZZ; (top center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively; (top right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom left) VBF produced graviton or radion decaying to WW or ZZ; (bottom center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively. The diagrams on the top are shown in the paper as well, and are included here for convenience.
png pdf	Additional Figure 1-d: Example Feynman diagrams of signal processes: (top left) $ \mathrm{g} \mathrm{g} $ produced graviton or radion decaying to WW or ZZ; (top center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively; (top right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom left) VBF produced graviton or radion decaying to WW or ZZ; (bottom center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively. The diagrams on the top are shown in the paper as well, and are included here for convenience.
png pdf	Additional Figure 1-e: Example Feynman diagrams of signal processes: (top left) $ \mathrm{g} \mathrm{g} $ produced graviton or radion decaying to WW or ZZ; (top center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively; (top right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom left) VBF produced graviton or radion decaying to WW or ZZ; (bottom center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively. The diagrams on the top are shown in the paper as well, and are included here for convenience.
png pdf	Additional Figure 1-f: Example Feynman diagrams of signal processes: (top left) $ \mathrm{g} \mathrm{g} $ produced graviton or radion decaying to WW or ZZ; (top center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively; (top right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom left) VBF produced graviton or radion decaying to WW or ZZ; (bottom center) DY produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to WW and WZ, respectively; (bottom right) VBF produced $ \mathrm{Z}^{'} $ and $ \mathrm{W^{'}} $ decaying to ZH and WH, respectively. The diagrams on the top are shown in the paper as well, and are included here for convenience.
png pdf	Additional Figure 2: Total signal efficiency including all event categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF (left) and VBF (right) signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 2-a: Total signal efficiency including all event categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF (left) and VBF (right) signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 2-b: Total signal efficiency including all event categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF (left) and VBF (right) signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 3: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 3-a: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 3-b: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 3-c: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 3-d: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 3-e: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 3-f: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 3-g: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 3-h: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 3-i: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 3-j: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 4: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 4-a: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 4-b: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 4-c: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 4-d: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 4-e: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 4-f: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 4-g: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 4-h: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 4-i: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 4-j: Signal efficiency in each of the categories as a function of the resonance mass $M_{\mathrm{X}}$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
png pdf	Additional Figure 5: Left: Selection requirement on the $ \mathrm{q}\overline{\mathrm{q}} $ discriminator to obtain a 5% misidentification rate in QCD multijet simulation as a function of jet $ p_{\mathrm{T}} $ and $ \rho=2\ln(m_\text{jet}^{\mathrm{AK8}}/p_{\mathrm{T}}) $. Right: Difference in the requirement to be applied on the $ \mathrm{q}\overline{\mathrm{q}} $ tagger to obtain a 5% background misidentification rate between the nominal and a smoothed version of this histogram.
png pdf	Additional Figure 5-a: Left: Selection requirement on the $ \mathrm{q}\overline{\mathrm{q}} $ discriminator to obtain a 5% misidentification rate in QCD multijet simulation as a function of jet $ p_{\mathrm{T}} $ and $ \rho=2\ln(m_\text{jet}^{\mathrm{AK8}}/p_{\mathrm{T}}) $. Right: Difference in the requirement to be applied on the $ \mathrm{q}\overline{\mathrm{q}} $ tagger to obtain a 5% background misidentification rate between the nominal and a smoothed version of this histogram.
png pdf	Additional Figure 5-b: Left: Selection requirement on the $ \mathrm{q}\overline{\mathrm{q}} $ discriminator to obtain a 5% misidentification rate in QCD multijet simulation as a function of jet $ p_{\mathrm{T}} $ and $ \rho=2\ln(m_\text{jet}^{\mathrm{AK8}}/p_{\mathrm{T}}) $. Right: Difference in the requirement to be applied on the $ \mathrm{q}\overline{\mathrm{q}} $ tagger to obtain a 5% background misidentification rate between the nominal and a smoothed version of this histogram.
png pdf	Additional Figure 6: Displays of an event with a reconstructed dijet invariant mass $ m_\mathrm{jj}^{\mathrm{AK8}}= $ 2.94 TeV in the DY/ggF VV HPHP category, with $ m_\text{jet1}^{\mathrm{AK8}}= $ 82 GeV and $ m_\text{jet2}^{\mathrm{AK8}}= $ 86 GeV, consistent with a WW, WZ or ZZ signal hypothesis. Reconstructed tracks are indicated as lines. Energy deposits in the electromagnetic and hadronic calorimeter are indicated as green and blue bars, respectively. The two leading AK8 jets have $ p_{\mathrm{T}}= $ 1.47 TeV, $ \eta= $ 0.27 and $ p_{\mathrm{T}}= $ 1.45 TeV, $ \eta= $ 0.17.
png	Additional Figure 6-a: Displays of an event with a reconstructed dijet invariant mass $ m_\mathrm{jj}^{\mathrm{AK8}}= $ 2.94 TeV in the DY/ggF VV HPHP category, with $ m_\text{jet1}^{\mathrm{AK8}}= $ 82 GeV and $ m_\text{jet2}^{\mathrm{AK8}}= $ 86 GeV, consistent with a WW, WZ or ZZ signal hypothesis. Reconstructed tracks are indicated as lines. Energy deposits in the electromagnetic and hadronic calorimeter are indicated as green and blue bars, respectively. The two leading AK8 jets have $ p_{\mathrm{T}}= $ 1.47 TeV, $ \eta= $ 0.27 and $ p_{\mathrm{T}}= $ 1.45 TeV, $ \eta= $ 0.17.
png	Additional Figure 6-b: Displays of an event with a reconstructed dijet invariant mass $ m_\mathrm{jj}^{\mathrm{AK8}}= $ 2.94 TeV in the DY/ggF VV HPHP category, with $ m_\text{jet1}^{\mathrm{AK8}}= $ 82 GeV and $ m_\text{jet2}^{\mathrm{AK8}}= $ 86 GeV, consistent with a WW, WZ or ZZ signal hypothesis. Reconstructed tracks are indicated as lines. Energy deposits in the electromagnetic and hadronic calorimeter are indicated as green and blue bars, respectively. The two leading AK8 jets have $ p_{\mathrm{T}}= $ 1.47 TeV, $ \eta= $ 0.27 and $ p_{\mathrm{T}}= $ 1.45 TeV, $ \eta= $ 0.17.
png pdf	Additional Figure 7: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH HPHP (upper) and VV HPHP (lower) categories.
png pdf	Additional Figure 7-a: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH HPHP (upper) and VV HPHP (lower) categories.
png pdf	Additional Figure 7-b: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH HPHP (upper) and VV HPHP (lower) categories.
png pdf	Additional Figure 7-c: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH HPHP (upper) and VV HPHP (lower) categories.
png pdf	Additional Figure 7-d: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH HPHP (upper) and VV HPHP (lower) categories.
png pdf	Additional Figure 8: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH LPHP (upper), VH HPLP (middle), and VV HPLP (lower) categories.
png pdf	Additional Figure 8-a: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH LPHP (upper), VH HPLP (middle), and VV HPLP (lower) categories.
png pdf	Additional Figure 8-b: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH LPHP (upper), VH HPLP (middle), and VV HPLP (lower) categories.
png pdf	Additional Figure 8-c: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH LPHP (upper), VH HPLP (middle), and VV HPLP (lower) categories.
png pdf	Additional Figure 8-d: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH LPHP (upper), VH HPLP (middle), and VV HPLP (lower) categories.
png pdf	Additional Figure 8-e: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH LPHP (upper), VH HPLP (middle), and VV HPLP (lower) categories.
png pdf	Additional Figure 8-f: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH LPHP (upper), VH HPLP (middle), and VV HPLP (lower) categories.
png pdf	Additional Figure 8-g: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH LPHP (upper), VH HPLP (middle), and VV HPLP (lower) categories.
png pdf	Additional Figure 8-h: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH LPHP (upper), VH HPLP (middle), and VV HPLP (lower) categories.
png pdf	Additional Figure 8-i: Projections of PYTHIA8 MC simulation of the QCD multijet background distribution onto the $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle), and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) dimensions are compared to the nominal QCD background template and the five alternate shapes added to the fit as shape nuisance parameters for the VH LPHP (upper), VH HPLP (middle), and VV HPLP (lower) categories.
png pdf	Additional Figure 9: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH HPHP (upper) and VV HPHP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty of the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty on the background estimate fitted to the data divided by the statistical uncertainty of the data is shown as a band.
png pdf	Additional Figure 9-a: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH HPHP (upper) and VV HPHP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty of the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty on the background estimate fitted to the data divided by the statistical uncertainty of the data is shown as a band.
png pdf	Additional Figure 9-b: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH HPHP (upper) and VV HPHP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty of the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty on the background estimate fitted to the data divided by the statistical uncertainty of the data is shown as a band.
png pdf	Additional Figure 9-c: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH HPHP (upper) and VV HPHP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty of the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty on the background estimate fitted to the data divided by the statistical uncertainty of the data is shown as a band.
png pdf	Additional Figure 9-d: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH HPHP (upper) and VV HPHP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty of the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty on the background estimate fitted to the data divided by the statistical uncertainty of the data is shown as a band.
png pdf	Additional Figure 10: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH LPHP (upper), DY/ggF VH HPLP (middle), and DY/ggF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 10-a: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH LPHP (upper), DY/ggF VH HPLP (middle), and DY/ggF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 10-b: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH LPHP (upper), DY/ggF VH HPLP (middle), and DY/ggF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 10-c: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH LPHP (upper), DY/ggF VH HPLP (middle), and DY/ggF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 10-d: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH LPHP (upper), DY/ggF VH HPLP (middle), and DY/ggF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 10-e: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH LPHP (upper), DY/ggF VH HPLP (middle), and DY/ggF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 10-f: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH LPHP (upper), DY/ggF VH HPLP (middle), and DY/ggF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 10-g: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH LPHP (upper), DY/ggF VH HPLP (middle), and DY/ggF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 10-h: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH LPHP (upper), DY/ggF VH HPLP (middle), and DY/ggF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 10-i: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the DY/ggF VH LPHP (upper), DY/ggF VH HPLP (middle), and DY/ggF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 11: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH HPHP (upper) and VBF VV HPHP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 11-a: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH HPHP (upper) and VBF VV HPHP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 11-b: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH HPHP (upper) and VBF VV HPHP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 11-c: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH HPHP (upper) and VBF VV HPHP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 11-d: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH HPHP (upper) and VBF VV HPHP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 11-e: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH HPHP (upper) and VBF VV HPHP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 11-f: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH HPHP (upper) and VBF VV HPHP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 12: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH LPHP (upper), VBF VH HPLP (middle), and VBF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 12-a: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH LPHP (upper), VBF VH HPLP (middle), and VBF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 12-b: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH LPHP (upper), VBF VH HPLP (middle), and VBF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 12-c: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH LPHP (upper), VBF VH HPLP (middle), and VBF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 12-d: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH LPHP (upper), VBF VH HPLP (middle), and VBF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 12-e: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH LPHP (upper), VBF VH HPLP (middle), and VBF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 12-f: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH LPHP (upper), VBF VH HPLP (middle), and VBF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 12-g: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH LPHP (upper), VBF VH HPLP (middle), and VBF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 12-h: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH LPHP (upper), VBF VH HPLP (middle), and VBF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 12-i: Comparison between the background post-fit and the data distributions of $ m_\text{jet1}^{\mathrm{AK8}} $ (left), $ m_\text{jet2}^{\mathrm{AK8}} $ (middle) and $ m_\mathrm{jj}^{\mathrm{AK8}} $ (right) in the VBF VH LPHP (upper), VBF VH HPLP (middle), and VBF VV HPLP (lower) categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. An example of a signal distribution is overlaid, where the number of expected events is scaled by an arbitrary normalization factor. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 13: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from DY/ggF VV (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 105 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 105 GeV) for the VH LPHP (left), VH HPLP (middle), and VV HPLP DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 13-a: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from DY/ggF VV (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 105 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 105 GeV) for the VH LPHP (left), VH HPLP (middle), and VV HPLP DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 13-b: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from DY/ggF VV (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 105 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 105 GeV) for the VH LPHP (left), VH HPLP (middle), and VV HPLP DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 13-c: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from DY/ggF VV (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 105 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 105 GeV) for the VH LPHP (left), VH HPLP (middle), and VV HPLP DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 14: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from DY/ggF VH (65 $ < m_\text{jet1/2}^{\mathrm{AK8}} < $ 105 GeV, 110 $ < m_\text{jet2/1}^{\mathrm{AK8}} < $ 140 GeV) for the HPHP (upper) and HPLP/LPHP (lower) DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 14-a: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from DY/ggF VH (65 $ < m_\text{jet1/2}^{\mathrm{AK8}} < $ 105 GeV, 110 $ < m_\text{jet2/1}^{\mathrm{AK8}} < $ 140 GeV) for the HPHP (upper) and HPLP/LPHP (lower) DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 14-b: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from DY/ggF VH (65 $ < m_\text{jet1/2}^{\mathrm{AK8}} < $ 105 GeV, 110 $ < m_\text{jet2/1}^{\mathrm{AK8}} < $ 140 GeV) for the HPHP (upper) and HPLP/LPHP (lower) DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 14-c: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from DY/ggF VH (65 $ < m_\text{jet1/2}^{\mathrm{AK8}} < $ 105 GeV, 110 $ < m_\text{jet2/1}^{\mathrm{AK8}} < $ 140 GeV) for the HPHP (upper) and HPLP/LPHP (lower) DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 14-d: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from DY/ggF VH (65 $ < m_\text{jet1/2}^{\mathrm{AK8}} < $ 105 GeV, 110 $ < m_\text{jet2/1}^{\mathrm{AK8}} < $ 140 GeV) for the HPHP (upper) and HPLP/LPHP (lower) DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 14-e: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from DY/ggF VH (65 $ < m_\text{jet1/2}^{\mathrm{AK8}} < $ 105 GeV, 110 $ < m_\text{jet2/1}^{\mathrm{AK8}} < $ 140 GeV) for the HPHP (upper) and HPLP/LPHP (lower) DY/ggF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 15: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from VBF VV/VH (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 140 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 140 GeV) for the HPHP (upper) and HPLP/LPHP (lower) VBF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 15-a: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from VBF VV/VH (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 140 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 140 GeV) for the HPHP (upper) and HPLP/LPHP (lower) VBF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 15-b: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from VBF VV/VH (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 140 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 140 GeV) for the HPHP (upper) and HPLP/LPHP (lower) VBF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 15-c: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from VBF VV/VH (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 140 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 140 GeV) for the HPHP (upper) and HPLP/LPHP (lower) VBF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 15-d: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from VBF VV/VH (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 140 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 140 GeV) for the HPHP (upper) and HPLP/LPHP (lower) VBF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 15-e: Projections of data and background post-fit distributions onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $ dimension in regions enriched in signal from VBF VV/VH (65 $ < m_\text{jet1}^{\mathrm{AK8}} < $ 140 GeV, 65 $ < m_\text{jet2}^{\mathrm{AK8}} < $ 140 GeV) for the HPHP (upper) and HPLP/LPHP (lower) VBF categories. The background shape uncertainty is shown as a gray shaded band around the result of the maximum likelihood fit to the data under the background-only assumption (gray solid line), and the statistical uncertainties in the data are shown as vertical bars. The various background components contributing to the total background fit are also shown with different line colors. Shown below each mass plot is the difference between the data and the fit divided by the statistical uncertainty in the data; the uncertainty bar represents the statistical uncertainty only. The total uncertainty in the background estimate fitted to the data divided by the statistical uncertainty in the data is shown as a band.
png pdf	Additional Figure 16: Projection of the 3D phase space of the data onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $--$ m_\text{jet1}^{\mathrm{AK8}} $ plane for a selected region in $ m_\text{jet2}^{\mathrm{AK8}} $ enriched in signal from DY/ggF VV. Contours of the signal and background distributions after the background post-fit are overlaid. The projections are shown for the HPHP VH (VV) DY/ggF category on the left (right).
png pdf	Additional Figure 16-a: Projection of the 3D phase space of the data onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $--$ m_\text{jet1}^{\mathrm{AK8}} $ plane for a selected region in $ m_\text{jet2}^{\mathrm{AK8}} $ enriched in signal from DY/ggF VV. Contours of the signal and background distributions after the background post-fit are overlaid. The projections are shown for the HPHP VH (VV) DY/ggF category on the left (right).
png pdf	Additional Figure 16-b: Projection of the 3D phase space of the data onto the $ m_\mathrm{jj}^{\mathrm{AK8}} $--$ m_\text{jet1}^{\mathrm{AK8}} $ plane for a selected region in $ m_\text{jet2}^{\mathrm{AK8}} $ enriched in signal from DY/ggF VV. Contours of the signal and background distributions after the background post-fit are overlaid. The projections are shown for the HPHP VH (VV) DY/ggF category on the left (right).
png pdf	Additional Figure 17: Expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction for a $ \mathrm{G}_{\text{bulk}}\to\mathrm{W}\mathrm{W} $ (left) and a $ \mathrm{G}_{\text{bulk}}\to\mathrm{Z}\mathrm{Z} $ (right) signal using 77.3 fb$ ^{-1} $ of data collected in 2016+2017 obtained using the methods presented here (red solid line), compared to the result obtained with previous methods (black dash-dotted line), published in EPJC 80 (2020) 237. The limit obtained combining data collected in 2016--2018 in this paper is also shown (blue dashed line).
png pdf	Additional Figure 17-a: Expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction for a $ \mathrm{G}_{\text{bulk}}\to\mathrm{W}\mathrm{W} $ (left) and a $ \mathrm{G}_{\text{bulk}}\to\mathrm{Z}\mathrm{Z} $ (right) signal using 77.3 fb$ ^{-1} $ of data collected in 2016+2017 obtained using the methods presented here (red solid line), compared to the result obtained with previous methods (black dash-dotted line), published in EPJC 80 (2020) 237. The limit obtained combining data collected in 2016--2018 in this paper is also shown (blue dashed line).
png pdf	Additional Figure 17-b: Expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction for a $ \mathrm{G}_{\text{bulk}}\to\mathrm{W}\mathrm{W} $ (left) and a $ \mathrm{G}_{\text{bulk}}\to\mathrm{Z}\mathrm{Z} $ (right) signal using 77.3 fb$ ^{-1} $ of data collected in 2016+2017 obtained using the methods presented here (red solid line), compared to the result obtained with previous methods (black dash-dotted line), published in EPJC 80 (2020) 237. The limit obtained combining data collected in 2016--2018 in this paper is also shown (blue dashed line).
png pdf	Additional Figure 18: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{G}_{\text{bulk}}\to\mathrm{W}\mathrm{W} $ (left) and $ \mathrm{G}_{\text{bulk}}\to\mathrm{Z}\mathrm{Z} $ (right) signals. In the upper panel the ggF production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 18-a: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{G}_{\text{bulk}}\to\mathrm{W}\mathrm{W} $ (left) and $ \mathrm{G}_{\text{bulk}}\to\mathrm{Z}\mathrm{Z} $ (right) signals. In the upper panel the ggF production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 18-b: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{G}_{\text{bulk}}\to\mathrm{W}\mathrm{W} $ (left) and $ \mathrm{G}_{\text{bulk}}\to\mathrm{Z}\mathrm{Z} $ (right) signals. In the upper panel the ggF production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 18-c: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{G}_{\text{bulk}}\to\mathrm{W}\mathrm{W} $ (left) and $ \mathrm{G}_{\text{bulk}}\to\mathrm{Z}\mathrm{Z} $ (right) signals. In the upper panel the ggF production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 18-d: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{G}_{\text{bulk}}\to\mathrm{W}\mathrm{W} $ (left) and $ \mathrm{G}_{\text{bulk}}\to\mathrm{Z}\mathrm{Z} $ (right) signals. In the upper panel the ggF production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 19: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \text{Rad} \to\mathrm{W}\mathrm{W} $ (left) and $ \text{Rad} \to\mathrm{Z}\mathrm{Z} $ (right) signals. In the upper panel the ggF production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 19-a: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \text{Rad} \to\mathrm{W}\mathrm{W} $ (left) and $ \text{Rad} \to\mathrm{Z}\mathrm{Z} $ (right) signals. In the upper panel the ggF production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 19-b: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \text{Rad} \to\mathrm{W}\mathrm{W} $ (left) and $ \text{Rad} \to\mathrm{Z}\mathrm{Z} $ (right) signals. In the upper panel the ggF production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 19-c: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \text{Rad} \to\mathrm{W}\mathrm{W} $ (left) and $ \text{Rad} \to\mathrm{Z}\mathrm{Z} $ (right) signals. In the upper panel the ggF production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 19-d: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \text{Rad} \to\mathrm{W}\mathrm{W} $ (left) and $ \text{Rad} \to\mathrm{Z}\mathrm{Z} $ (right) signals. In the upper panel the ggF production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 20: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{Z}^{'}\to\mathrm{W}\mathrm{W} $ (left) and $ \mathrm{W^{'}}\to\mathrm{W}\mathrm{Z} $ (right) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 20-a: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{Z}^{'}\to\mathrm{W}\mathrm{W} $ (left) and $ \mathrm{W^{'}}\to\mathrm{W}\mathrm{Z} $ (right) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 20-b: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{Z}^{'}\to\mathrm{W}\mathrm{W} $ (left) and $ \mathrm{W^{'}}\to\mathrm{W}\mathrm{Z} $ (right) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 20-c: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{Z}^{'}\to\mathrm{W}\mathrm{W} $ (left) and $ \mathrm{W^{'}}\to\mathrm{W}\mathrm{Z} $ (right) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 20-d: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{Z}^{'}\to\mathrm{W}\mathrm{W} $ (left) and $ \mathrm{W^{'}}\to\mathrm{W}\mathrm{Z} $ (right) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 21: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{Z}^{'}\to\mathrm{Z}\mathrm{H} $ (left) and $ \mathrm{W^{'}}\to\mathrm{W}\mathrm{H} $ (right) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 21-a: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{Z}^{'}\to\mathrm{Z}\mathrm{H} $ (left) and $ \mathrm{W^{'}}\to\mathrm{W}\mathrm{H} $ (right) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 21-b: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{Z}^{'}\to\mathrm{Z}\mathrm{H} $ (left) and $ \mathrm{W^{'}}\to\mathrm{W}\mathrm{H} $ (right) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 21-c: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{Z}^{'}\to\mathrm{Z}\mathrm{H} $ (left) and $ \mathrm{W^{'}}\to\mathrm{W}\mathrm{H} $ (right) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 21-d: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{Z}^{'}\to\mathrm{Z}\mathrm{H} $ (left) and $ \mathrm{W^{'}}\to\mathrm{W}\mathrm{H} $ (right) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 22: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for VBF produced $ \text{Rad} \to\mathrm{V}\mathrm{V} $ (left) and $ \mathrm{G}_{\text{bulk}}\to\mathrm{V}\mathrm{V} $ (right) signals. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 22-a: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for VBF produced $ \text{Rad} \to\mathrm{V}\mathrm{V} $ (left) and $ \mathrm{G}_{\text{bulk}}\to\mathrm{V}\mathrm{V} $ (right) signals. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 22-b: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for VBF produced $ \text{Rad} \to\mathrm{V}\mathrm{V} $ (left) and $ \mathrm{G}_{\text{bulk}}\to\mathrm{V}\mathrm{V} $ (right) signals. For each signal scenario the theoretical prediction (red line) and its uncertainty associated with the choice of PDF set (red hashed band) is shown.
png pdf	Additional Figure 23: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{V}^\prime\to\mathrm{W}\mathrm{V} $ (upper) and $ \mathrm{V}^\prime\to\mathrm{V}\mathrm{H} $ (lower) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 23-a: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{V}^\prime\to\mathrm{W}\mathrm{V} $ (upper) and $ \mathrm{V}^\prime\to\mathrm{V}\mathrm{H} $ (lower) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 23-b: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{V}^\prime\to\mathrm{W}\mathrm{V} $ (upper) and $ \mathrm{V}^\prime\to\mathrm{V}\mathrm{H} $ (lower) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 23-c: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{V}^\prime\to\mathrm{W}\mathrm{V} $ (upper) and $ \mathrm{V}^\prime\to\mathrm{V}\mathrm{H} $ (lower) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.
png pdf	Additional Figure 23-d: Observed and expected 95% CL\ upper limits on the product of the production cross section ($ \sigma $) and the branching fraction, obtained after combining all categories with 138 fb$^{-1}$ fb$ ^{-1} $ of data at $ \sqrt{s}= $ 13 TeV, for $ \mathrm{V}^\prime\to\mathrm{W}\mathrm{V} $ (upper) and $ \mathrm{V}^\prime\to\mathrm{V}\mathrm{H} $ (lower) signals. In the upper panel the DY production mode is shown while in the lower panel the VBF mode is presented. For each signal scenario the theoretical prediction (red line for $ c_{\mathrm{H}} = $ 1, blue line for $ c_{\mathrm{H}} = $ 3) and its uncertainty associated with the choice of PDF set (red and blue hashed bands) is shown.

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48	ATLAS Collaboration	Search for new resonances decaying to a W or Z boson and a Higgs boson in the $ {\ell^+\ell^-\mathrm{b}\overline{\mathrm{b}}} $, $ {\ell\nu\mathrm{b}\overline{\mathrm{b}}} $, and $ {\nu\overline{\nu}\mathrm{b}\overline{\mathrm{b}}} $ channels with pp collisions at $ \sqrt{s}= $ 13 TeV with the ATLAS detector	PLB 765 (2017) 32	1607.05621
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52	CMS Collaboration	Particle-flow reconstruction and global event description with the CMS detector	JINST 12 (2017) P10003	CMS-PRF-14-001 1706.04965
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