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| CMS-B2G-23-007 ; CERN-EP-2026-001 | ||
| Search for heavy scalar resonances decaying to Lorentz-boosted Higgs and Higgs-like bosons in the $ \mathrm{b}\overline{\mathrm{b}}4\mathrm{q} $ final state at $ \sqrt{s} = $ 13 TeV | ||
| CMS Collaboration | ||
| 30 January 2026 | ||
| Submitted to the Journal of High Energy Physics | ||
| Abstract: A search is performed for a heavy scalar resonance ($\mathrm{X}$) decaying to a Higgs boson ($\mathrm{H}$) and a Higgs-like scalar boson ($\mathrm{Y}$) in the two bottom quark ($ \mathrm{H}\to\mathrm{b}\overline{\mathrm{b}} $) and four quark ($ \mathrm{Y} \to\mathrm{V}\mathrm{V}\to4\mathrm{q} $) final state, where $\mathrm{V}$ denotes a $\mathrm{W}$ or $\mathrm{Z}$ boson. Masses of the $\mathrm{X}$ between 900 and 4000 GeV and the $\mathrm{Y}$ between 60 and 2800 GeV are considered. The search is performed in data collected by the CMS experiment at the CERN LHC from proton-proton collisions at 13 TeV center-of-mass energy, with a data set corresponding to a total integrated luminosity of 138 fb$ ^{-1} $. It targets the Lorentz-boosted regime, in which the products of the $ \mathrm{H}\to\mathrm{b}\overline{\mathrm{b}} $ decay can be reconstructed as a single large-area jet, and those from the $ \mathrm{Y} \to\mathrm{V}\mathrm{V}\to4\mathrm{q} $ decay as either one $ \mathrm{Y} \to4\mathrm{q} $ or two $ \mathrm{V}\to\mathrm{q}\overline{\mathrm{q}} $ jets. Jet identification and mass reconstruction exploit machine-learning tools, including a novel attention-based ``particle transformer'' for $ \mathrm{Y} \to4\mathrm{q} $ identification. No significant excess is observed in the data above the standard model background expectation. Upper limits on the product of production cross section and branching fraction as low as 0.2fb$^{-1}$ are derived at 95% confidence level for various mass hypotheses. This is the first search at the LHC for scalar resonances in the all-hadronic $ \mathrm{b}\overline{\mathrm{b}}\mathrm{V}\mathrm{V} $ decay channel. | ||
| Links: e-print arXiv:2602.00273 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; CADI line (restricted) ; | ||
| Figures | |
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Figure 1:
Schematic diagrams of the $ \mathrm{X} \to \mathrm{HY} $ decay in the $ \mathrm{H}\to\mathrm{b}\overline{\mathrm{b}} $ and $ {{Y}} \to\mathrm{V}\mathrm{V}\to4\mathrm{q} $ all-hadronic final state, with $ \mathrm{V}=\mathrm{W} $ or $\mathrm{Z} $. Left: The fully merged regime ($ {m_{{Y}} } \lesssim 0.1 {m_{{X}} } $) in which {Y} is highly boosted, with its decay products merged and reconstructed as a single large-area jet. Right: The semimerged regime (0.1 $ {m_{{X}} } \lesssim {m_{{Y}} } < {m_{{X}} } - {m_\mathrm{H}} $) in which {Y} is not as boosted, and each daughter V boson is instead reconstructed individually as a large-area jet. |
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Figure 2:
Schematic of the event categorization into the signal pass (SP), signal fail (SF), validation pass (VP), and validation fail (VF) regions for the fully merged (left) and semimerged (right) categories. The pass and fail tagging regions of the fully merged and semimerged categories are determined by application of the high purity (HP) working point (WP) of the $ T_\text{YWW} $ and $ T_\text{Xbb} $ taggers, respectively. |
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Figure 2-a:
Schematic of the event categorization into the signal pass (SP), signal fail (SF), validation pass (VP), and validation fail (VF) regions for the fully merged (left) and semimerged (right) categories. The pass and fail tagging regions of the fully merged and semimerged categories are determined by application of the high purity (HP) working point (WP) of the $ T_\text{YWW} $ and $ T_\text{Xbb} $ taggers, respectively. |
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Figure 2-b:
Schematic of the event categorization into the signal pass (SP), signal fail (SF), validation pass (VP), and validation fail (VF) regions for the fully merged (left) and semimerged (right) categories. The pass and fail tagging regions of the fully merged and semimerged categories are determined by application of the high purity (HP) working point (WP) of the $ T_\text{YWW} $ and $ T_\text{Xbb} $ taggers, respectively. |
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Figure 3:
Measured transfer functions $ R^\text{sim}({{m_{{X}} },{m_{{Y}} }}) $ (left) and $ R({{m_{{X}} },{m_{{Y}} }}) $ (right) between the signal pass (SP) and signal fail (SF) regions of the fully merged category used to estimate the QCD multijet background contribution. |
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Figure 3-a:
Measured transfer functions $ R^\text{sim}({{m_{{X}} },{m_{{Y}} }}) $ (left) and $ R({{m_{{X}} },{m_{{Y}} }}) $ (right) between the signal pass (SP) and signal fail (SF) regions of the fully merged category used to estimate the QCD multijet background contribution. |
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Figure 3-b:
Measured transfer functions $ R^\text{sim}({{m_{{X}} },{m_{{Y}} }}) $ (left) and $ R({{m_{{X}} },{m_{{Y}} }}) $ (right) between the signal pass (SP) and signal fail (SF) regions of the fully merged category used to estimate the QCD multijet background contribution. |
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Figure 4:
Projected distributions of the $ {m_{{X}} ^\text{rec}} $ (left) and $ {m_{{Y}} ^\text{rec}} $ (right) observables in the validation pass (VP) region of the fully merged (FM) category, after a background-only maximum likelihood fit to the data. The upper panels show the data and fitted background estimates, as well as the $ \pm $1 standard deviation uncertainty in the total background estimate ($ {\sigma_\text{syst}} $) per bin, divided by the respective bin widths, in gray. The vertical error bars for the data represent the statistical uncertainty, while the horizontal bars represent the bin widths. The lower panels show the pull per bin, defined as $\frac{ (\mathrm{data} - \mathrm{Bkg.})}{{\sigma_\text{stat}}} $, as well as a gray band indicating the systematic uncertainty in the pulls, estimated by dividing the corresponding systematic uncertainty in the main panel by $ {\sigma_\text{stat}} $. |
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Figure 4-a:
Projected distributions of the $ {m_{{X}} ^\text{rec}} $ (left) and $ {m_{{Y}} ^\text{rec}} $ (right) observables in the validation pass (VP) region of the fully merged (FM) category, after a background-only maximum likelihood fit to the data. The upper panels show the data and fitted background estimates, as well as the $ \pm $1 standard deviation uncertainty in the total background estimate ($ {\sigma_\text{syst}} $) per bin, divided by the respective bin widths, in gray. The vertical error bars for the data represent the statistical uncertainty, while the horizontal bars represent the bin widths. The lower panels show the pull per bin, defined as $\frac{ (\mathrm{data} - \mathrm{Bkg.})}{{\sigma_\text{stat}}} $, as well as a gray band indicating the systematic uncertainty in the pulls, estimated by dividing the corresponding systematic uncertainty in the main panel by $ {\sigma_\text{stat}} $. |
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Figure 4-b:
Projected distributions of the $ {m_{{X}} ^\text{rec}} $ (left) and $ {m_{{Y}} ^\text{rec}} $ (right) observables in the validation pass (VP) region of the fully merged (FM) category, after a background-only maximum likelihood fit to the data. The upper panels show the data and fitted background estimates, as well as the $ \pm $1 standard deviation uncertainty in the total background estimate ($ {\sigma_\text{syst}} $) per bin, divided by the respective bin widths, in gray. The vertical error bars for the data represent the statistical uncertainty, while the horizontal bars represent the bin widths. The lower panels show the pull per bin, defined as $\frac{ (\mathrm{data} - \mathrm{Bkg.})}{{\sigma_\text{stat}}} $, as well as a gray band indicating the systematic uncertainty in the pulls, estimated by dividing the corresponding systematic uncertainty in the main panel by $ {\sigma_\text{stat}} $. |
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Figure 5:
Projected distributions of the $ {m_{{X}} ^\text{rec}} $ (left) and $ {m_{{Y}} ^\text{rec}} $ (right) observables in the validation pass (VP) region of the semimerged (SM) category, after a background-only maximum likelihood fit to the data. The upper panels show the data and fitted background estimates, as well as the $ \pm $1 standard deviation uncertainty in the total background estimate ($ {\sigma_\text{syst}} $) per bin, divided by the respective bin widths, in gray. The vertical error bars for the data represent the statistical uncertainty, while the horizontal bars represent the bin widths. The lower panels show the pull per bin, defined as $\frac{ (\mathrm{data} - \mathrm{Bkg.})}{{\sigma_\text{stat}}} $ as well as a gray band indicating the systematic uncertainty in the pulls, estimated by dividing the corresponding systematic uncertainty in the main panel by $ {\sigma_\text{stat}} $. |
png pdf |
Figure 5-a:
Projected distributions of the $ {m_{{X}} ^\text{rec}} $ (left) and $ {m_{{Y}} ^\text{rec}} $ (right) observables in the validation pass (VP) region of the semimerged (SM) category, after a background-only maximum likelihood fit to the data. The upper panels show the data and fitted background estimates, as well as the $ \pm $1 standard deviation uncertainty in the total background estimate ($ {\sigma_\text{syst}} $) per bin, divided by the respective bin widths, in gray. The vertical error bars for the data represent the statistical uncertainty, while the horizontal bars represent the bin widths. The lower panels show the pull per bin, defined as $\frac{ (\mathrm{data} - \mathrm{Bkg.})}{{\sigma_\text{stat}}} $ as well as a gray band indicating the systematic uncertainty in the pulls, estimated by dividing the corresponding systematic uncertainty in the main panel by $ {\sigma_\text{stat}} $. |
png pdf |
Figure 5-b:
Projected distributions of the $ {m_{{X}} ^\text{rec}} $ (left) and $ {m_{{Y}} ^\text{rec}} $ (right) observables in the validation pass (VP) region of the semimerged (SM) category, after a background-only maximum likelihood fit to the data. The upper panels show the data and fitted background estimates, as well as the $ \pm $1 standard deviation uncertainty in the total background estimate ($ {\sigma_\text{syst}} $) per bin, divided by the respective bin widths, in gray. The vertical error bars for the data represent the statistical uncertainty, while the horizontal bars represent the bin widths. The lower panels show the pull per bin, defined as $\frac{ (\mathrm{data} - \mathrm{Bkg.})}{{\sigma_\text{stat}}} $ as well as a gray band indicating the systematic uncertainty in the pulls, estimated by dividing the corresponding systematic uncertainty in the main panel by $ {\sigma_\text{stat}} $. |
png pdf |
Figure 6:
Projected distributions of the $ {m_{{X}} ^\text{rec}} $ (left) and $ {m_{{Y}} ^\text{rec}} $ (right) observables in the signal pass (SP) region of the fully merged (FM) category, after a maximum likelihood fit to the data with an $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_{{X}} } = $ 900 GeV and $ {m_{{Y}} } = $ 80 GeV and product of best-fit production cross section and branching fraction of 15fb$^{-1}$. The signal distribution has been scaled by a factor of two in the upper panels to help distinguish it from the background distributions. The lower panels show the pull per bin, defined as $\frac{ (\mathrm{data} - \mathrm{Bkg.})}{{\sigma_\text{stat}}} $, as well as a gray band indicating the systematic uncertainty in the pulls, estimated by dividing the corresponding systematic uncertainty in the main panel by $ {\sigma_\text{stat}} $. |
png pdf |
Figure 6-a:
Projected distributions of the $ {m_{{X}} ^\text{rec}} $ (left) and $ {m_{{Y}} ^\text{rec}} $ (right) observables in the signal pass (SP) region of the fully merged (FM) category, after a maximum likelihood fit to the data with an $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_{{X}} } = $ 900 GeV and $ {m_{{Y}} } = $ 80 GeV and product of best-fit production cross section and branching fraction of 15fb$^{-1}$. The signal distribution has been scaled by a factor of two in the upper panels to help distinguish it from the background distributions. The lower panels show the pull per bin, defined as $\frac{ (\mathrm{data} - \mathrm{Bkg.})}{{\sigma_\text{stat}}} $, as well as a gray band indicating the systematic uncertainty in the pulls, estimated by dividing the corresponding systematic uncertainty in the main panel by $ {\sigma_\text{stat}} $. |
png pdf |
Figure 6-b:
Projected distributions of the $ {m_{{X}} ^\text{rec}} $ (left) and $ {m_{{Y}} ^\text{rec}} $ (right) observables in the signal pass (SP) region of the fully merged (FM) category, after a maximum likelihood fit to the data with an $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_{{X}} } = $ 900 GeV and $ {m_{{Y}} } = $ 80 GeV and product of best-fit production cross section and branching fraction of 15fb$^{-1}$. The signal distribution has been scaled by a factor of two in the upper panels to help distinguish it from the background distributions. The lower panels show the pull per bin, defined as $\frac{ (\mathrm{data} - \mathrm{Bkg.})}{{\sigma_\text{stat}}} $, as well as a gray band indicating the systematic uncertainty in the pulls, estimated by dividing the corresponding systematic uncertainty in the main panel by $ {\sigma_\text{stat}} $. |
png pdf |
Figure 7:
Projected distributions of the $ {m_{{X}} ^\text{rec}} $ (left) and $ {m_{{Y}} ^\text{rec}} $ (right) observables in the signal pass (SP) region of the semimerged (SM) category, after a maximum likelihood fit to the data with an $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_{{X}} } = $ 1200 GeV and $ {m_{{Y}} } = $ 900 GeV and product of best-fit production cross section and branching fraction of 250fb$^{-1}$. The lower panels show the pull per bin, defined as $\frac{ (\mathrm{data} - \mathrm{Bkg.})}{{\sigma_\text{stat}}} $, as well as a gray band indicating the systematic uncertainty in the pulls, estimated by dividing the corresponding systematic uncertainty in the main panel by $ {\sigma_\text{stat}} $. |
png pdf |
Figure 7-a:
Projected distributions of the $ {m_{{X}} ^\text{rec}} $ (left) and $ {m_{{Y}} ^\text{rec}} $ (right) observables in the signal pass (SP) region of the semimerged (SM) category, after a maximum likelihood fit to the data with an $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_{{X}} } = $ 1200 GeV and $ {m_{{Y}} } = $ 900 GeV and product of best-fit production cross section and branching fraction of 250fb$^{-1}$. The lower panels show the pull per bin, defined as $\frac{ (\mathrm{data} - \mathrm{Bkg.})}{{\sigma_\text{stat}}} $, as well as a gray band indicating the systematic uncertainty in the pulls, estimated by dividing the corresponding systematic uncertainty in the main panel by $ {\sigma_\text{stat}} $. |
png pdf |
Figure 7-b:
Projected distributions of the $ {m_{{X}} ^\text{rec}} $ (left) and $ {m_{{Y}} ^\text{rec}} $ (right) observables in the signal pass (SP) region of the semimerged (SM) category, after a maximum likelihood fit to the data with an $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_{{X}} } = $ 1200 GeV and $ {m_{{Y}} } = $ 900 GeV and product of best-fit production cross section and branching fraction of 250fb$^{-1}$. The lower panels show the pull per bin, defined as $\frac{ (\mathrm{data} - \mathrm{Bkg.})}{{\sigma_\text{stat}}} $, as well as a gray band indicating the systematic uncertainty in the pulls, estimated by dividing the corresponding systematic uncertainty in the main panel by $ {\sigma_\text{stat}} $. |
png pdf |
Figure 8:
The 2D pulls in the $ {m_{{X}} ^\text{rec}} $ and $ {m_{{Y}} ^\text{rec}} $ observables in the signal pass (SP) regions of the fully merged (FM, left) and semimerged (SM, right) categories, after a maximum likelihood fit to the data with an $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_{{X}} } = $ 900 GeV and $ {m_{{Y}} } = $ 80 GeV, and $ {m_{{X}} } = $ 1200 GeV and $ {m_{{Y}} } = $ 900 GeV, respectively. Pulls are defined as $\frac{(\mathrm{data} - \mathrm{Bkg.})}{\sigma_\text{stat}} $ where $\sigma$ is the sum in quadrature of the background and data uncertainties. |
png pdf |
Figure 8-a:
The 2D pulls in the $ {m_{{X}} ^\text{rec}} $ and $ {m_{{Y}} ^\text{rec}} $ observables in the signal pass (SP) regions of the fully merged (FM, left) and semimerged (SM, right) categories, after a maximum likelihood fit to the data with an $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_{{X}} } = $ 900 GeV and $ {m_{{Y}} } = $ 80 GeV, and $ {m_{{X}} } = $ 1200 GeV and $ {m_{{Y}} } = $ 900 GeV, respectively. Pulls are defined as $\frac{(\mathrm{data} - \mathrm{Bkg.})}{\sigma_\text{stat}} $ where $\sigma$ is the sum in quadrature of the background and data uncertainties. |
png pdf |
Figure 8-b:
The 2D pulls in the $ {m_{{X}} ^\text{rec}} $ and $ {m_{{Y}} ^\text{rec}} $ observables in the signal pass (SP) regions of the fully merged (FM, left) and semimerged (SM, right) categories, after a maximum likelihood fit to the data with an $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_{{X}} } = $ 900 GeV and $ {m_{{Y}} } = $ 80 GeV, and $ {m_{{X}} } = $ 1200 GeV and $ {m_{{Y}} } = $ 900 GeV, respectively. Pulls are defined as $\frac{(\mathrm{data} - \mathrm{Bkg.})}{\sigma_\text{stat}} $ where $\sigma$ is the sum in quadrature of the background and data uncertainties. |
png pdf |
Figure 9:
Median expected (left) and observed (right) upper limits at 95% CL on the product of production cross section and branching fraction for $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ on the 2D $ {m_{{X}} } $ and $ {m_{{Y}} } $ plane. The dashed line separates the mass points considered in the fully merged (FM) and semimerged (SM) categories. |
png pdf |
Figure 9-a:
Median expected (left) and observed (right) upper limits at 95% CL on the product of production cross section and branching fraction for $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ on the 2D $ {m_{{X}} } $ and $ {m_{{Y}} } $ plane. The dashed line separates the mass points considered in the fully merged (FM) and semimerged (SM) categories. |
png pdf |
Figure 9-b:
Median expected (left) and observed (right) upper limits at 95% CL on the product of production cross section and branching fraction for $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ on the 2D $ {m_{{X}} } $ and $ {m_{{Y}} } $ plane. The dashed line separates the mass points considered in the fully merged (FM) and semimerged (SM) categories. |
png pdf |
Figure 10:
Expected and observed upper limits at 95% CL on the product of production cross section and branching fraction for $ {{{X}} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signals. The dashed and solid black lines represent median expected and observed limits, respectively. The inner (green) and outer (yellow) bands represent the $ \pm $ 1 and $ \pm $ 2 standard deviations for the expected limits, respectively. The left and right set of points in each panel correspond to those considered in the fully merged (FM) and semimerged (SM) categories, respectively. |
| Tables | |
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Table 1:
Sources of systematic uncertainties and their effects on different processes in the fully merged (FM) and semimerged (SM) categories. |
| Summary |
| A search has been performed for a heavy scalar resonance $\mathrm{X}$ decaying to a Higgs boson (H) and Higgs-like scalar boson ($\mathrm{Y}$) in the two bottom quark ($ \mathrm{H}\to\mathrm{b}\overline{\mathrm{b}} $) and four quark ($ {{Y}} \to\mathrm{V}\mathrm{V}\to4\mathrm{q} $) final state, where V denotes a W or Z boson. The search targets Lorentz-boosted $ {{{X}} \to\mathrm{H}{{Y}} } $ production where the daughter quarks from the H and {Y} bosons are merged within large-area jets. A mass-decorrelated graph neural network tagger, known as PARTICLENET, was used to select $ \mathrm{H}\to\mathrm{b}\overline{\mathrm{b}} $ and $ \mathrm{V}\to\mathrm{q}\overline{\mathrm{q}} $ jets while the new ``particle transformer'' is used for fully merged $ \mathrm{Y} \to\mathrm{V}\mathrm{V} $ jets. The signal is extracted from a two-dimensional maximum likelihood fit to data binned in the reconstructed {Y} and {X} masses. The dominant quantum chromodynamics multijet background is estimated using control regions in data with the tagger score selections inverted. Other minor backgrounds including top quark and V plus jets are estimated using Monte Carlo simulations. No significant excess is observed in the data above the standard model background expectation. Upper limits at 95% confidence level as low as 0.2fb$^{-1}$ are set for the product of resonant $ \mathrm{X} \to\mathrm{H}{{Y}} \to\mathrm{b}\overline{\mathrm{b}}\mathrm{V}\mathrm{V}} $ production cross section and branching fraction for various {X} and {Y} masses. This is the first search for scalar resonances in the all-hadronic $ \mathrm{b}\overline{\mathrm{b}}\mathrm{V}\mathrm{V} $ final state at the LHC. |
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