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| CMS-PAS-B2G-23-007 | ||
| Search for heavy scalar resonances decaying to a Higgs and a Higgs-like boson in the Lorentz-boosted $ \mathrm{b\overline{b}}4\mathrm{q} $ final state | ||
| CMS Collaboration | ||
| 2025-07-11 | ||
| Abstract: A search is performed for a heavy scalar resonance X decaying to a Higgs boson (H) and Higgs-like scalar boson (Y) in the $ \mathrm{H}\to\mathrm{b\overline{b}} $ and $ \mathrm{Y}\to\mathrm{VV}\to4\mathrm{q} $ final state, where q denotes a quark. Masses of the X boson between 900 and 4000 GeV and the Y between 60 and 2800 GeV are considered. The search is performed in data collected by the CMS experiment at the LHC from proton-proton collisions at 13 TeV center-of-mass energy, with a dataset corresponding to a total luminosity of 138 fb$ ^{-1} $. It targets the Lorentz-boosted regime, in which the products of the $ \mathrm{H}\to\mathrm{b\overline{b}} $ decay can be reconstructed as a single large-area jet, and those from the $ \mathrm{Y}\to\mathrm{q\overline{q}} $ decay as either one $ \mathrm{Y}\to4\mathrm{q} $ or two $ \mathrm{Y}\to\mathrm{q\overline{q}} $ jets. It exploits machine-learning-based jet identification and mass reconstruction algorithms, including a novel attention-based "particle transformer" for $ \mathrm{Y}\to4\mathrm{q} $ discrimination. No significant excess is observed in the data above the standard model background expectation and upper limits as low as 0.2 fb are derived at 95% confidence level for various mass points. This is the first search at the LHC for scalar resonances in the all-hadronic $ \mathrm{b\overline{b}}\mathrm{VV} $ final state. | ||
| Links: CDS record (PDF) ; CADI line (restricted) ; | ||
| Figures | |
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Figure 1:
Schematic diagrams of the $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}} $ decay in the $ \mathrm{H}\to\mathrm{b}\overline{\mathrm{b}} $ and $ \mathrm{Y}\to\mathrm{V}\mathrm{V}\to4\mathrm{q} $ all-hadronic final state. Left: The fully-merged regime ($ {m_{\mathrm{Y}}} \lesssim 0.1 {m_\mathrm{X}} $) in which $ \mathrm{Y} $ is highly boosted, with its decay products merged and reconstructed as a single large-area jet. Right: The semi-merged regime (0.1 $ {m_\mathrm{X}} \lesssim {m_{\mathrm{Y}}} < {m_\mathrm{X}} - {m_\mathrm{H}} $) in which $ \mathrm{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 SP, SF, VP, and VF regions for the fully-merged (FM) (left) and semi-merged (SM) (right) categories. |
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Figure 2-a:
Schematic of the event categorization into the SP, SF, VP, and VF regions for the fully-merged (FM) (left) and semi-merged (SM) (right) categories. |
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Figure 2-b:
Schematic of the event categorization into the SP, SF, VP, and VF regions for the fully-merged (FM) (left) and semi-merged (SM) (right) categories. |
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Figure 3:
Measured transfer functions $ R^\mathrm{Sim}({{m_\mathrm{X}},{m_{\mathrm{Y}}}}) $ (left) and $ R({{m_\mathrm{X}},{m_{\mathrm{Y}}}}) $ (right) between the SP and 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^\mathrm{Sim}({{m_\mathrm{X}},{m_{\mathrm{Y}}}}) $ (left) and $ R({{m_\mathrm{X}},{m_{\mathrm{Y}}}}) $ (right) between the SP and 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^\mathrm{Sim}({{m_\mathrm{X}},{m_{\mathrm{Y}}}}) $ (left) and $ R({{m_\mathrm{X}},{m_{\mathrm{Y}}}}) $ (right) between the SP and 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_\mathrm{X}^\mathrm{rec}} $ (left) and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ (right) observables in the 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_\mathrm{Syst}} $) per bin, divided by the respective bin widths, in gray. The vertical error bars for data represent the statistical uncertainty, while the horizontal bars represent the bin widths. The lower panels show the pull per bin, defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{{\sigma_\mathrm{Stat}}} $, where $ {\sigma_\mathrm{Stat}} $ is the statistical uncertainty in the data, as well as the ratio of systematic and statistical uncertainties. |
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Figure 4-a:
Projected distributions of the $ {m_\mathrm{X}^\mathrm{rec}} $ (left) and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ (right) observables in the 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_\mathrm{Syst}} $) per bin, divided by the respective bin widths, in gray. The vertical error bars for data represent the statistical uncertainty, while the horizontal bars represent the bin widths. The lower panels show the pull per bin, defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{{\sigma_\mathrm{Stat}}} $, where $ {\sigma_\mathrm{Stat}} $ is the statistical uncertainty in the data, as well as the ratio of systematic and statistical uncertainties. |
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Figure 4-b:
Projected distributions of the $ {m_\mathrm{X}^\mathrm{rec}} $ (left) and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ (right) observables in the 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_\mathrm{Syst}} $) per bin, divided by the respective bin widths, in gray. The vertical error bars for data represent the statistical uncertainty, while the horizontal bars represent the bin widths. The lower panels show the pull per bin, defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{{\sigma_\mathrm{Stat}}} $, where $ {\sigma_\mathrm{Stat}} $ is the statistical uncertainty in the data, as well as the ratio of systematic and statistical uncertainties. |
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Figure 5:
Projected distributions of the $ {m_\mathrm{X}^\mathrm{rec}} $ (left) and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ (right) observables in the VP region of the semi-merged (SM) category, after a background-only maximum likelihood fit to the data. The lower panels show the pull per bin, defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{{\sigma_\mathrm{Stat}}} $, where $ {\sigma_\mathrm{Stat}} $ is the statistical uncertainty in the data, as well as the ratio of systematic and statistical uncertainties. |
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Figure 5-a:
Projected distributions of the $ {m_\mathrm{X}^\mathrm{rec}} $ (left) and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ (right) observables in the VP region of the semi-merged (SM) category, after a background-only maximum likelihood fit to the data. The lower panels show the pull per bin, defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{{\sigma_\mathrm{Stat}}} $, where $ {\sigma_\mathrm{Stat}} $ is the statistical uncertainty in the data, as well as the ratio of systematic and statistical uncertainties. |
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Figure 5-b:
Projected distributions of the $ {m_\mathrm{X}^\mathrm{rec}} $ (left) and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ (right) observables in the VP region of the semi-merged (SM) category, after a background-only maximum likelihood fit to the data. The lower panels show the pull per bin, defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{{\sigma_\mathrm{Stat}}} $, where $ {\sigma_\mathrm{Stat}} $ is the statistical uncertainty in the data, as well as the ratio of systematic and statistical uncertainties. |
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Figure 6:
Projected distributions of the $ {m_\mathrm{X}^\mathrm{rec}} $ (left) and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ (right) observables in the SP region of the fully-merged (FM) category, after a maximum likelihood fit to the data with an $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_\mathrm{X}} = $ 900 GeV and $ {m_{\mathrm{Y}}} = $ 80 GeV. The lower panels show the pull per bin, defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{{\sigma_\mathrm{Stat}}} $, where $ {\sigma_\mathrm{Stat}} $ is the statistical uncertainty in the data, as well as the ratio of systematic and statistical uncertainties. |
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Figure 6-a:
Projected distributions of the $ {m_\mathrm{X}^\mathrm{rec}} $ (left) and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ (right) observables in the SP region of the fully-merged (FM) category, after a maximum likelihood fit to the data with an $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_\mathrm{X}} = $ 900 GeV and $ {m_{\mathrm{Y}}} = $ 80 GeV. The lower panels show the pull per bin, defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{{\sigma_\mathrm{Stat}}} $, where $ {\sigma_\mathrm{Stat}} $ is the statistical uncertainty in the data, as well as the ratio of systematic and statistical uncertainties. |
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Figure 6-b:
Projected distributions of the $ {m_\mathrm{X}^\mathrm{rec}} $ (left) and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ (right) observables in the SP region of the fully-merged (FM) category, after a maximum likelihood fit to the data with an $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_\mathrm{X}} = $ 900 GeV and $ {m_{\mathrm{Y}}} = $ 80 GeV. The lower panels show the pull per bin, defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{{\sigma_\mathrm{Stat}}} $, where $ {\sigma_\mathrm{Stat}} $ is the statistical uncertainty in the data, as well as the ratio of systematic and statistical uncertainties. |
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Figure 7:
Projected distributions of the $ {m_\mathrm{X}^\mathrm{rec}} $ (left) and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ (right) observables in the SP region of the semi-merged (SM) category, after a maximum likelihood fit to the data with an $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_\mathrm{X}} = $ 1200 GeV and $ {m_{\mathrm{Y}}} = $ 900 GeV. The lower panels show the pull per bin, defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{{\sigma_\mathrm{Stat}}} $, where $ {\sigma_\mathrm{Stat}} $ is the statistical uncertainty in the data, as well as the ratio of systematic and statistical uncertainties. |
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Figure 7-a:
Projected distributions of the $ {m_\mathrm{X}^\mathrm{rec}} $ (left) and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ (right) observables in the SP region of the semi-merged (SM) category, after a maximum likelihood fit to the data with an $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_\mathrm{X}} = $ 1200 GeV and $ {m_{\mathrm{Y}}} = $ 900 GeV. The lower panels show the pull per bin, defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{{\sigma_\mathrm{Stat}}} $, where $ {\sigma_\mathrm{Stat}} $ is the statistical uncertainty in the data, as well as the ratio of systematic and statistical uncertainties. |
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Figure 7-b:
Projected distributions of the $ {m_\mathrm{X}^\mathrm{rec}} $ (left) and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ (right) observables in the SP region of the semi-merged (SM) category, after a maximum likelihood fit to the data with an $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_\mathrm{X}} = $ 1200 GeV and $ {m_{\mathrm{Y}}} = $ 900 GeV. The lower panels show the pull per bin, defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{{\sigma_\mathrm{Stat}}} $, where $ {\sigma_\mathrm{Stat}} $ is the statistical uncertainty in the data, as well as the ratio of systematic and statistical uncertainties. |
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Figure 8:
2D pulls in the $ {m_\mathrm{X}^\mathrm{rec}} $ and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ observables in the SP regions of the fully-merged (FM) (left) and semi-merged (SM) (right) categories, after a maximum likelihood fit to the data with an $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_\mathrm{X}} = $ 900 GeV and $ {m_{\mathrm{Y}}} = $ 80 GeV, and $ {m_\mathrm{X}} = $ 1200 GeV and $ {m_{\mathrm{Y}}} = $ 900 GeV, respectively. Pulls are defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{\sigma} $, where $ \sigma $ is the sum in quadrature of the background and data uncertainties. Signal contours are overlaid in white. |
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Figure 8-a:
2D pulls in the $ {m_\mathrm{X}^\mathrm{rec}} $ and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ observables in the SP regions of the fully-merged (FM) (left) and semi-merged (SM) (right) categories, after a maximum likelihood fit to the data with an $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_\mathrm{X}} = $ 900 GeV and $ {m_{\mathrm{Y}}} = $ 80 GeV, and $ {m_\mathrm{X}} = $ 1200 GeV and $ {m_{\mathrm{Y}}} = $ 900 GeV, respectively. Pulls are defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{\sigma} $, where $ \sigma $ is the sum in quadrature of the background and data uncertainties. Signal contours are overlaid in white. |
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Figure 8-b:
2D pulls in the $ {m_\mathrm{X}^\mathrm{rec}} $ and $ {m_{\mathrm{Y}}^\mathrm{rec}} $ observables in the SP regions of the fully-merged (FM) (left) and semi-merged (SM) (right) categories, after a maximum likelihood fit to the data with an $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ signal with $ {m_\mathrm{X}} = $ 900 GeV and $ {m_{\mathrm{Y}}} = $ 80 GeV, and $ {m_\mathrm{X}} = $ 1200 GeV and $ {m_{\mathrm{Y}}} = $ 900 GeV, respectively. Pulls are defined as $ \ifrac{(\mathrm{data} - \mathrm{bkg.})}{\sigma} $, where $ \sigma $ is the sum in quadrature of the background and data uncertainties. Signal contours are overlaid in white. |
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Figure 9:
Median expected (left) and observed (right) upper limits at 95% CL on production cross section times branching fraction for $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ in the 2D $ {m_\mathrm{X}} $ and $ {m_{\mathrm{Y}}} $ plane. The dashed line separates the mass points considered in the fully-merged (FM) and semi-merged (SM) categories. |
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Figure 9-a:
Median expected (left) and observed (right) upper limits at 95% CL on production cross section times branching fraction for $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ in the 2D $ {m_\mathrm{X}} $ and $ {m_{\mathrm{Y}}} $ plane. The dashed line separates the mass points considered in the fully-merged (FM) and semi-merged (SM) categories. |
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Figure 9-b:
Median expected (left) and observed (right) upper limits at 95% CL on production cross section times branching fraction for $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{W}\mathrm{W}} $ in the 2D $ {m_\mathrm{X}} $ and $ {m_{\mathrm{Y}}} $ plane. The dashed line separates the mass points considered in the fully-merged (FM) and semi-merged (SM) categories. |
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Figure 10:
Expected and observed upper limits at 95% CL on production cross section times branching fraction for $ {\mathrm{X}\to\mathrm{H}\mathrm{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 green and yellow bands represent the $ \pm $ 1 and $ \pm $ 2 standard deviations for the expected limits. The left and right set of points in each panel correspond to those considered in the fully-merged (FM) and semi-merged (SM) categories, respectively. |
| Tables | |
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Table 1:
Offline selection criteria for analysis regions in the fully-merged category. |
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Table 2:
Offline selection criteria for analysis regions in the semi-merged category. |
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Table 3:
Sources of systematic uncertainties considered in this analysis and their effects on different processes in the fully-merged (FM) and semi-merged (SM) categories. |
| Summary |
| A search was performed for a heavy scalar resonance X decaying to a Higgs boson (H) and Higgs-like scalar boson (Y) in the $ \mathrm{H}\to\mathrm{b}\overline{\mathrm{b}} $ and $ \mathrm{Y}\to\mathrm{V}\mathrm{V}\to4\mathrm{q} $ final state, where V denotes a W or Z boson. The search targeted Lorentz-boosted $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}} $ production where H and Y daughter quarks are merged within large-area AK8 jets. The established 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'' was used for fully-merged $ \mathrm{Y}\to\mathrm{V}\mathrm{V} $ jets. The signal was extracted from a two dimensional maximum likelihood fit to data binned in the reconstructed Y and X masses. The dominant quantum chromodynamics multijet background was estimated through a data-driven approach using control regions with the tagger score selections inverted. Other minor backgrounds including top quark and V plus jets were estimated using Monte Carlo simulations. No significant excess was observed in the data above the standard model background expectation and 95% confidence level upper limits as low as 0.2\unitfb for resonant $ {\mathrm{X}\to\mathrm{H}\mathrm{Y}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{V}\mathrm{V}} $ production cross section times branching fraction for various X and $ \mathrm{Y} $ masses were set. |
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