Compact Muon Solenoid
LHC, CERN
Visit us: CMS Public Website, CMS Physics ;
Contact us: CMS Publications Committee
| CMS-PAS-NPS-25-005 | ||
| Search for Lorentz-boosted Higgs boson decays to a pair of new spin-0 particles in the $ \mathrm{b \overline{b} b \overline{b}} $ final state at $ \sqrt{s} = $ 13 TeV | ||
| CMS Collaboration | ||
| 2026-07-31 | ||
| Abstract: A search is presented for exotic decays of the 125 GeV Higgs boson (H) to a pair of identical neutral scalar or pseudoscalar particles ($ a_{1} a_{1} $), where each decays promptly to a $ \mathrm{b \overline{b}} $ pair, resulting in a $ \mathrm{b \overline{b} b \overline{b}} $ final state. The search uses proton-proton collision data collected by the CMS detector at $ \sqrt{s} = $ 13 TeV, corresponding to an integrated luminosity of 138 $ \mathrm{fb^{-1}} $. Events with Lorentz-boosted Higgs bosons from five different production modes are targeted to measure the branching fraction $ \mathcal{B}(\mathrm{H \to} a_{1}a_{1} \mathrm{\to b \overline{b} b \overline{b}}) $ for $ a_{1} $ masses from 11-62.5 GeV. The largest deviation from the background expectation occurs near an $ a_{1} $ mass of 45 GeV, with a local (global) significance of 3.0 (1.7) standard deviations. Upper limits at the 95% confidence level are set on $ \mathcal{B}(\mathrm{H \to} a_{1}a_{1} \mathrm{\to b \overline{b} b \overline{b}}) $ ranging from 0.13% to 9.4% (0.22% to 3.1% expected), depending on the $ a_{1} $ mass. The results improve on previous constraints by up to an order of magnitude, and provide the most stringent limits to date on extended Higgs sector scenarios, including two-Higgs-doublet plus singlet models, for new light bosons in the probed mass range. | ||
| Links: CDS record (PDF) ; CADI line (restricted) ; | ||
| Figures | |
png pdf |
Figure 1:
Simulated QCD multijet (left) and $ \mathrm{t} \overline{\mathrm{t}} $ (right) background efficiency vs.\ $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ signal efficiency of the PARTICLENET} \MATHRM{X4B classifier, for three signal $ m(a_1) $ values. Two tight selection thresholds used in the analysis (WP40 and WP60) are indicated by stars. |
png pdf |
Figure 1-a:
Simulated QCD multijet (left) and $ \mathrm{t} \overline{\mathrm{t}} $ (right) background efficiency vs.\ $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ signal efficiency of the PARTICLENET} \MATHRM{X4B classifier, for three signal $ m(a_1) $ values. Two tight selection thresholds used in the analysis (WP40 and WP60) are indicated by stars. |
png pdf |
Figure 1-b:
Simulated QCD multijet (left) and $ \mathrm{t} \overline{\mathrm{t}} $ (right) background efficiency vs.\ $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ signal efficiency of the PARTICLENET} \MATHRM{X4B classifier, for three signal $ m(a_1) $ values. Two tight selection thresholds used in the analysis (WP40 and WP60) are indicated by stars. |
png pdf |
Figure 2:
Distributions of the PARTICLENET regressed masses of the full AK8 jet ($ m(\mathrm{X}) $, left) and the $ a_1 $ boson ($ m(a_1) $, right) for simulated $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ events with all four b hadrons clustered into the AK8 jet. The four-prong $ {ParticleNet} m(\mathrm{X}) $ regressor shows improved resolution compared to PF mass and soft-drop mass, and the two-prong PARTICLENET regressor. |
png pdf |
Figure 2-a:
Distributions of the PARTICLENET regressed masses of the full AK8 jet ($ m(\mathrm{X}) $, left) and the $ a_1 $ boson ($ m(a_1) $, right) for simulated $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ events with all four b hadrons clustered into the AK8 jet. The four-prong $ {ParticleNet} m(\mathrm{X}) $ regressor shows improved resolution compared to PF mass and soft-drop mass, and the two-prong PARTICLENET regressor. |
png pdf |
Figure 2-b:
Distributions of the PARTICLENET regressed masses of the full AK8 jet ($ m(\mathrm{X}) $, left) and the $ a_1 $ boson ($ m(a_1) $, right) for simulated $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ events with all four b hadrons clustered into the AK8 jet. The four-prong $ {ParticleNet} m(\mathrm{X}) $ regressor shows improved resolution compared to PF mass and soft-drop mass, and the two-prong PARTICLENET regressor. |
png pdf |
Figure 3:
Distributions of the PARTICLENET regressed masses of the full AK8 jet (left) and the $ a_1 $ boson (right) for jets passing a loose selection requirement on the PARTICLENET} \MATHRM{X4B tagger (sideband plus signal region), in data and simulated $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ signal and background events containing no reconstructed leptons, collected with jet triggers during Run 2. Corrections are applied to the background models to better match the data yields and AK8 jet $ p_{\mathrm{T}} $ spectra. Only statistical uncertainties on the background model are shown, and the signal distributions assume a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 3-a:
Distributions of the PARTICLENET regressed masses of the full AK8 jet (left) and the $ a_1 $ boson (right) for jets passing a loose selection requirement on the PARTICLENET} \MATHRM{X4B tagger (sideband plus signal region), in data and simulated $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ signal and background events containing no reconstructed leptons, collected with jet triggers during Run 2. Corrections are applied to the background models to better match the data yields and AK8 jet $ p_{\mathrm{T}} $ spectra. Only statistical uncertainties on the background model are shown, and the signal distributions assume a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 3-b:
Distributions of the PARTICLENET regressed masses of the full AK8 jet (left) and the $ a_1 $ boson (right) for jets passing a loose selection requirement on the PARTICLENET} \MATHRM{X4B tagger (sideband plus signal region), in data and simulated $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ signal and background events containing no reconstructed leptons, collected with jet triggers during Run 2. Corrections are applied to the background models to better match the data yields and AK8 jet $ p_{\mathrm{T}} $ spectra. Only statistical uncertainties on the background model are shown, and the signal distributions assume a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 4:
Distributions used to calibrate the AK8 jet PARTICLENET taggers and $ \mathrm{X}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ mass regressor: the $ \mathrm{X4b} $ score in AK8 jets overlapping four b-tagged AK4 jets in the QCD CR (top left), the $ \mathrm{Xbb} $ (top right) and $ \mathrm{bbqq} $ (bottom left) scores in semileptonic $ \mathrm{t} \overline{\mathrm{t}} $ CR events with AK8 jets containing hadrons from both the top quark and antiquark decays, and the regressed $ m(\mathrm{X}) $ in AK8 jets from single hadronic top quark decays selected with a mass-decorrelated top quark tagger (bottom right). The last bins in the tagger distributions correspond to the 60% signal efficiency WP for $ \mathrm{X4b} $, the signal candidate selection for $ \mathrm{Xbb} $, and the 40% signal efficiency WP for $ \mathrm{bbqq} $. The MC model is fit to the data with separate rate and shape uncertainties in each MC sample. |
png pdf |
Figure 4-a:
Distributions used to calibrate the AK8 jet PARTICLENET taggers and $ \mathrm{X}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ mass regressor: the $ \mathrm{X4b} $ score in AK8 jets overlapping four b-tagged AK4 jets in the QCD CR (top left), the $ \mathrm{Xbb} $ (top right) and $ \mathrm{bbqq} $ (bottom left) scores in semileptonic $ \mathrm{t} \overline{\mathrm{t}} $ CR events with AK8 jets containing hadrons from both the top quark and antiquark decays, and the regressed $ m(\mathrm{X}) $ in AK8 jets from single hadronic top quark decays selected with a mass-decorrelated top quark tagger (bottom right). The last bins in the tagger distributions correspond to the 60% signal efficiency WP for $ \mathrm{X4b} $, the signal candidate selection for $ \mathrm{Xbb} $, and the 40% signal efficiency WP for $ \mathrm{bbqq} $. The MC model is fit to the data with separate rate and shape uncertainties in each MC sample. |
png pdf |
Figure 4-b:
Distributions used to calibrate the AK8 jet PARTICLENET taggers and $ \mathrm{X}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ mass regressor: the $ \mathrm{X4b} $ score in AK8 jets overlapping four b-tagged AK4 jets in the QCD CR (top left), the $ \mathrm{Xbb} $ (top right) and $ \mathrm{bbqq} $ (bottom left) scores in semileptonic $ \mathrm{t} \overline{\mathrm{t}} $ CR events with AK8 jets containing hadrons from both the top quark and antiquark decays, and the regressed $ m(\mathrm{X}) $ in AK8 jets from single hadronic top quark decays selected with a mass-decorrelated top quark tagger (bottom right). The last bins in the tagger distributions correspond to the 60% signal efficiency WP for $ \mathrm{X4b} $, the signal candidate selection for $ \mathrm{Xbb} $, and the 40% signal efficiency WP for $ \mathrm{bbqq} $. The MC model is fit to the data with separate rate and shape uncertainties in each MC sample. |
png pdf |
Figure 4-c:
Distributions used to calibrate the AK8 jet PARTICLENET taggers and $ \mathrm{X}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ mass regressor: the $ \mathrm{X4b} $ score in AK8 jets overlapping four b-tagged AK4 jets in the QCD CR (top left), the $ \mathrm{Xbb} $ (top right) and $ \mathrm{bbqq} $ (bottom left) scores in semileptonic $ \mathrm{t} \overline{\mathrm{t}} $ CR events with AK8 jets containing hadrons from both the top quark and antiquark decays, and the regressed $ m(\mathrm{X}) $ in AK8 jets from single hadronic top quark decays selected with a mass-decorrelated top quark tagger (bottom right). The last bins in the tagger distributions correspond to the 60% signal efficiency WP for $ \mathrm{X4b} $, the signal candidate selection for $ \mathrm{Xbb} $, and the 40% signal efficiency WP for $ \mathrm{bbqq} $. The MC model is fit to the data with separate rate and shape uncertainties in each MC sample. |
png pdf |
Figure 4-d:
Distributions used to calibrate the AK8 jet PARTICLENET taggers and $ \mathrm{X}\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ mass regressor: the $ \mathrm{X4b} $ score in AK8 jets overlapping four b-tagged AK4 jets in the QCD CR (top left), the $ \mathrm{Xbb} $ (top right) and $ \mathrm{bbqq} $ (bottom left) scores in semileptonic $ \mathrm{t} \overline{\mathrm{t}} $ CR events with AK8 jets containing hadrons from both the top quark and antiquark decays, and the regressed $ m(\mathrm{X}) $ in AK8 jets from single hadronic top quark decays selected with a mass-decorrelated top quark tagger (bottom right). The last bins in the tagger distributions correspond to the 60% signal efficiency WP for $ \mathrm{X4b} $, the signal candidate selection for $ \mathrm{Xbb} $, and the 40% signal efficiency WP for $ \mathrm{bbqq} $. The MC model is fit to the data with separate rate and shape uncertainties in each MC sample. |
png pdf |
Figure 5:
Distributions of the $ \mathrm{e}\mathrm{e} $ or $ \mu\mu $ invariant mass in the $ \mathrm{Z}\ell\ell $ category (top left), the $ p_{\mathrm{T}} $ of the vector sum of the lepton and $ E_{\mathrm{T}}^{\text{miss}} $ in the $ \mathrm{W}\ell\nu $ category (top right), the number of b-tagged AK4 jets outside the Higgs boson candidate AK8 jet in the $ {\mathrm{t}\overline{\mathrm{t}}} \ell\nu $ category (bottom left), and the $ p_{\mathrm{T}} $ of the W/Z boson candidate AK8 jet in the $ \mathrm{V}jj $ category (bottom right). Corrections are applied to the background models to better match the data yields. Only statistical uncertainties on the background model are shown, and the signal distributions assume a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 5-a:
Distributions of the $ \mathrm{e}\mathrm{e} $ or $ \mu\mu $ invariant mass in the $ \mathrm{Z}\ell\ell $ category (top left), the $ p_{\mathrm{T}} $ of the vector sum of the lepton and $ E_{\mathrm{T}}^{\text{miss}} $ in the $ \mathrm{W}\ell\nu $ category (top right), the number of b-tagged AK4 jets outside the Higgs boson candidate AK8 jet in the $ {\mathrm{t}\overline{\mathrm{t}}} \ell\nu $ category (bottom left), and the $ p_{\mathrm{T}} $ of the W/Z boson candidate AK8 jet in the $ \mathrm{V}jj $ category (bottom right). Corrections are applied to the background models to better match the data yields. Only statistical uncertainties on the background model are shown, and the signal distributions assume a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 5-b:
Distributions of the $ \mathrm{e}\mathrm{e} $ or $ \mu\mu $ invariant mass in the $ \mathrm{Z}\ell\ell $ category (top left), the $ p_{\mathrm{T}} $ of the vector sum of the lepton and $ E_{\mathrm{T}}^{\text{miss}} $ in the $ \mathrm{W}\ell\nu $ category (top right), the number of b-tagged AK4 jets outside the Higgs boson candidate AK8 jet in the $ {\mathrm{t}\overline{\mathrm{t}}} \ell\nu $ category (bottom left), and the $ p_{\mathrm{T}} $ of the W/Z boson candidate AK8 jet in the $ \mathrm{V}jj $ category (bottom right). Corrections are applied to the background models to better match the data yields. Only statistical uncertainties on the background model are shown, and the signal distributions assume a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 5-c:
Distributions of the $ \mathrm{e}\mathrm{e} $ or $ \mu\mu $ invariant mass in the $ \mathrm{Z}\ell\ell $ category (top left), the $ p_{\mathrm{T}} $ of the vector sum of the lepton and $ E_{\mathrm{T}}^{\text{miss}} $ in the $ \mathrm{W}\ell\nu $ category (top right), the number of b-tagged AK4 jets outside the Higgs boson candidate AK8 jet in the $ {\mathrm{t}\overline{\mathrm{t}}} \ell\nu $ category (bottom left), and the $ p_{\mathrm{T}} $ of the W/Z boson candidate AK8 jet in the $ \mathrm{V}jj $ category (bottom right). Corrections are applied to the background models to better match the data yields. Only statistical uncertainties on the background model are shown, and the signal distributions assume a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 5-d:
Distributions of the $ \mathrm{e}\mathrm{e} $ or $ \mu\mu $ invariant mass in the $ \mathrm{Z}\ell\ell $ category (top left), the $ p_{\mathrm{T}} $ of the vector sum of the lepton and $ E_{\mathrm{T}}^{\text{miss}} $ in the $ \mathrm{W}\ell\nu $ category (top right), the number of b-tagged AK4 jets outside the Higgs boson candidate AK8 jet in the $ {\mathrm{t}\overline{\mathrm{t}}} \ell\nu $ category (bottom left), and the $ p_{\mathrm{T}} $ of the W/Z boson candidate AK8 jet in the $ \mathrm{V}jj $ category (bottom right). Corrections are applied to the background models to better match the data yields. Only statistical uncertainties on the background model are shown, and the signal distributions assume a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 6:
Distributions of the invariant mass of the two highest-$ p_{\mathrm{T}} $ AK4 jets outside the Higgs boson candidate AK8 jet in the $ \mathrm{VBF}jj $ category (left), and the Higgs boson candidate AK8 jet $ p_{\mathrm{T}} $ in the $ \mathrm{gg0}\ell $ category (right). Corrections are applied to the background models to better match the data yields and AK8 jet $ p_{\mathrm{T}} $ spectra. Only statistical uncertainties on the background model are shown, and the signal distributions assume a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 6-a:
Distributions of the invariant mass of the two highest-$ p_{\mathrm{T}} $ AK4 jets outside the Higgs boson candidate AK8 jet in the $ \mathrm{VBF}jj $ category (left), and the Higgs boson candidate AK8 jet $ p_{\mathrm{T}} $ in the $ \mathrm{gg0}\ell $ category (right). Corrections are applied to the background models to better match the data yields and AK8 jet $ p_{\mathrm{T}} $ spectra. Only statistical uncertainties on the background model are shown, and the signal distributions assume a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 6-b:
Distributions of the invariant mass of the two highest-$ p_{\mathrm{T}} $ AK4 jets outside the Higgs boson candidate AK8 jet in the $ \mathrm{VBF}jj $ category (left), and the Higgs boson candidate AK8 jet $ p_{\mathrm{T}} $ in the $ \mathrm{gg0}\ell $ category (right). Corrections are applied to the background models to better match the data yields and AK8 jet $ p_{\mathrm{T}} $ spectra. Only statistical uncertainties on the background model are shown, and the signal distributions assume a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 7:
Regressed $ m(\mathrm{X}) $ distributions for SR data, simulated signal, and the background model from the 2DAlphabet background-only fit, in the $ \mathrm{gg0}\ell $ and $ \mathrm{VBF}jj $ categories (top), and the $ \mathrm{V}jj $ and leptonic categories (bottom). Signal distributions are shown assuming a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 7-a:
Regressed $ m(\mathrm{X}) $ distributions for SR data, simulated signal, and the background model from the 2DAlphabet background-only fit, in the $ \mathrm{gg0}\ell $ and $ \mathrm{VBF}jj $ categories (top), and the $ \mathrm{V}jj $ and leptonic categories (bottom). Signal distributions are shown assuming a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 7-b:
Regressed $ m(\mathrm{X}) $ distributions for SR data, simulated signal, and the background model from the 2DAlphabet background-only fit, in the $ \mathrm{gg0}\ell $ and $ \mathrm{VBF}jj $ categories (top), and the $ \mathrm{V}jj $ and leptonic categories (bottom). Signal distributions are shown assuming a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 8:
Regressed $ m(a_1) $ distributions for SR data, simulated signal, and the background model from the 2DAlphabet background-only fit in events with 110 $ < m(\mathrm{X}) < 140 \text{Ge\hspace{-.08em}V} $, in the $ \mathrm{gg0}\ell $ and $ \mathrm{VBF}jj $ categories (top), and the $ \mathrm{V}jj $ and leptonic categories (bottom). Signal distributions are shown assuming a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 8-a:
Regressed $ m(a_1) $ distributions for SR data, simulated signal, and the background model from the 2DAlphabet background-only fit in events with 110 $ < m(\mathrm{X}) < 140 \text{Ge\hspace{-.08em}V} $, in the $ \mathrm{gg0}\ell $ and $ \mathrm{VBF}jj $ categories (top), and the $ \mathrm{V}jj $ and leptonic categories (bottom). Signal distributions are shown assuming a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 8-b:
Regressed $ m(a_1) $ distributions for SR data, simulated signal, and the background model from the 2DAlphabet background-only fit in events with 110 $ < m(\mathrm{X}) < 140 \text{Ge\hspace{-.08em}V} $, in the $ \mathrm{gg0}\ell $ and $ \mathrm{VBF}jj $ categories (top), and the $ \mathrm{V}jj $ and leptonic categories (bottom). Signal distributions are shown assuming a 100% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction. |
png pdf |
Figure 9:
Expected and observed 95% CL upper limits on the $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction for $ m(a_1) $ hypotheses from 11 to 62.5 GeV, assuming SM cross sections for 125 GeV Higgs boson production, from the full combined measurement (left), and in fit categories targeting specific Higgs boson production modes (right). |
png pdf |
Figure 9-a:
Expected and observed 95% CL upper limits on the $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction for $ m(a_1) $ hypotheses from 11 to 62.5 GeV, assuming SM cross sections for 125 GeV Higgs boson production, from the full combined measurement (left), and in fit categories targeting specific Higgs boson production modes (right). |
png pdf |
Figure 9-b:
Expected and observed 95% CL upper limits on the $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching fraction for $ m(a_1) $ hypotheses from 11 to 62.5 GeV, assuming SM cross sections for 125 GeV Higgs boson production, from the full combined measurement (left), and in fit categories targeting specific Higgs boson production modes (right). |
png pdf |
Figure 10:
95% CL upper limits on the Higgs boson branching fraction to a pair of new scalar or pseudoscalar particles $ \mathcal{B}(\mathrm{H}\to a_1a_1) $ as a function of $ m(a_1) $ in 2HDM+S scenarios, derived from the measured limits on $ \mathcal{B}(\mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}}) $. The top left panel shows expected and observed limits for Type I, with a comparison to previous CMS searches in other $ a_1 $ decay modes. The top right, bottom left, and bottom right panels correspond to Types II, III, and IV, respectively. For Types II--IV, the observed limits are shown in the $ \tan\beta $ vs.\ $ m(a_1) $ plane, where $ \tan\beta = v_2/v_1 $. The results are presented in terms of $ \mathcal{B}(\mathrm{H}\to a_1a_1) $, accounting for the $ \mathcal{B}(a_1 \to \mathrm{b}\overline{\mathrm{b}}) $ value predicted by the given 2HDM+S model parameters. |
png pdf |
Figure 10-a:
95% CL upper limits on the Higgs boson branching fraction to a pair of new scalar or pseudoscalar particles $ \mathcal{B}(\mathrm{H}\to a_1a_1) $ as a function of $ m(a_1) $ in 2HDM+S scenarios, derived from the measured limits on $ \mathcal{B}(\mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}}) $. The top left panel shows expected and observed limits for Type I, with a comparison to previous CMS searches in other $ a_1 $ decay modes. The top right, bottom left, and bottom right panels correspond to Types II, III, and IV, respectively. For Types II--IV, the observed limits are shown in the $ \tan\beta $ vs.\ $ m(a_1) $ plane, where $ \tan\beta = v_2/v_1 $. The results are presented in terms of $ \mathcal{B}(\mathrm{H}\to a_1a_1) $, accounting for the $ \mathcal{B}(a_1 \to \mathrm{b}\overline{\mathrm{b}}) $ value predicted by the given 2HDM+S model parameters. |
png pdf |
Figure 10-b:
95% CL upper limits on the Higgs boson branching fraction to a pair of new scalar or pseudoscalar particles $ \mathcal{B}(\mathrm{H}\to a_1a_1) $ as a function of $ m(a_1) $ in 2HDM+S scenarios, derived from the measured limits on $ \mathcal{B}(\mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}}) $. The top left panel shows expected and observed limits for Type I, with a comparison to previous CMS searches in other $ a_1 $ decay modes. The top right, bottom left, and bottom right panels correspond to Types II, III, and IV, respectively. For Types II--IV, the observed limits are shown in the $ \tan\beta $ vs.\ $ m(a_1) $ plane, where $ \tan\beta = v_2/v_1 $. The results are presented in terms of $ \mathcal{B}(\mathrm{H}\to a_1a_1) $, accounting for the $ \mathcal{B}(a_1 \to \mathrm{b}\overline{\mathrm{b}}) $ value predicted by the given 2HDM+S model parameters. |
png pdf |
Figure 10-c:
95% CL upper limits on the Higgs boson branching fraction to a pair of new scalar or pseudoscalar particles $ \mathcal{B}(\mathrm{H}\to a_1a_1) $ as a function of $ m(a_1) $ in 2HDM+S scenarios, derived from the measured limits on $ \mathcal{B}(\mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}}) $. The top left panel shows expected and observed limits for Type I, with a comparison to previous CMS searches in other $ a_1 $ decay modes. The top right, bottom left, and bottom right panels correspond to Types II, III, and IV, respectively. For Types II--IV, the observed limits are shown in the $ \tan\beta $ vs.\ $ m(a_1) $ plane, where $ \tan\beta = v_2/v_1 $. The results are presented in terms of $ \mathcal{B}(\mathrm{H}\to a_1a_1) $, accounting for the $ \mathcal{B}(a_1 \to \mathrm{b}\overline{\mathrm{b}}) $ value predicted by the given 2HDM+S model parameters. |
png pdf |
Figure 10-d:
95% CL upper limits on the Higgs boson branching fraction to a pair of new scalar or pseudoscalar particles $ \mathcal{B}(\mathrm{H}\to a_1a_1) $ as a function of $ m(a_1) $ in 2HDM+S scenarios, derived from the measured limits on $ \mathcal{B}(\mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}}) $. The top left panel shows expected and observed limits for Type I, with a comparison to previous CMS searches in other $ a_1 $ decay modes. The top right, bottom left, and bottom right panels correspond to Types II, III, and IV, respectively. For Types II--IV, the observed limits are shown in the $ \tan\beta $ vs.\ $ m(a_1) $ plane, where $ \tan\beta = v_2/v_1 $. The results are presented in terms of $ \mathcal{B}(\mathrm{H}\to a_1a_1) $, accounting for the $ \mathcal{B}(a_1 \to \mathrm{b}\overline{\mathrm{b}}) $ value predicted by the given 2HDM+S model parameters. |
| Tables | |
png pdf |
Table 1:
Summary of event categories used to enhance sensitivity to different Higgs boson production modes. Each category excludes all events from categories above it in the list. Here $ \ell $ denotes an electron or muon, AK8(H) denotes the $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ candidate AK8 jet, AK4(b) denotes a b-tagged AK4 jet, and $ j_1 $ and $ j_2 $ denote the two highest-$ p_{\mathrm{T}} $ AK4 jets. |
png pdf |
Table 2:
Estimated signal and background yields for the full Run 2 dataset in all event selection categories. The ``Fit category'' column shows how event selection categories are merged for the 2DAlphabet signal extraction fit. The ``Signal'' column gives the expected signal yields (averaged over all $ m(a_1) $, with 10% $ \mathrm{H}\to a_1a_1\to\mathrm{b}\overline{\mathrm{b}}\mathrm{b}\overline{\mathrm{b}} $ branching) passing the tight PARTICLENET} \MATHRM{X4B WP with regressed $ m(\mathrm{X}) $ from 110--140 GeV. ``Bkg. (data)'' and ``Bkg. (MC)'' give the corresponding expected background, estimated from events passing a lower $ \mathrm{X4b} $ WP, which are shown in brackets for data. ``S/B'' is the expected signal-to-background ratio. |
| Summary |
| References | ||||
| 1 | ATLAS Collaboration | Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC | PLB 716 (2012) 1 | 1207.7214 |
| 2 | CMS Collaboration | Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC | PLB 716 (2012) 30 | CMS-HIG-12-028 1207.7235 |
| 3 | CMS Collaboration | Observation of a new boson with mass near 125 GeV in pp collisions at $ \sqrt{s} = $ 7 and 8 TeV | JHEP 06 (2013) 081 | CMS-HIG-12-036 1303.4571 |
| 4 | ATLAS and CMS Collaborations | Combination of ATLAS and CMS searches for Higgs boson pair production at $ \sqrt{s}= $ 13 TeV | Submitted to Phys. Rev. Lett, 2026 link |
|
| 5 | ATLAS Collaboration | Combination of Searches for Higgs Boson Pair Production in $ pp $ Collisions at $ \sqrt{s}= $ 13 TeV with the ATLAS Detector | PRL 133 (2024) | 2406.09971 |
| 6 | CMS Collaboration | Combination of searches for nonresonant Higgs boson pair production in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | Submitted to Reports on Progress in Physics, 2025 link |
|
| 7 | ATLAS Collaboration | Combined measurements of Higgs boson production and decay at $ \sqrt{s}= $ 13 TeV using up to 140 $ \mathrm{fb}^{-1} $ of data collected by the ATLAS Experiment | ATLAS-CONF-2025-006, 2025 link |
|
| 8 | CMS Collaboration | Combined measurements and interpretations of Higgs boson production and decay in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | Submitted to Reports on Progress in Physics, 2026 link |
|
| 9 | ATLAS Collaboration | Characterising the Higgs boson with ATLAS data from the LHC Run-2 | Physics Reports 1116 (2025) | 2404.05498 |
| 10 | ATLAS Collaboration | Summary plots for beyond Standard Model Higgs boson benchmarks for direct and indirect searches | technical report, CERN, Geneva, 2025 | |
| 11 | J. Li, H. Song, S. Su, and W. Su | Charged Higgs search in 2HDM | JHEP 05 (2025) | 2412.04572 |
| 12 | D. Curtin et al. | Exotic decays of the 125 GeV Higgs boson | PRD 90 (2014) | 1312.4992 |
| 13 | A. Giorgio et al. | Two-Higgs-doublet-plus-pseudoscalar model: Collider, dark matter, and gravitational wave signals | PRD 108 (2023) | 2212.14788 |
| 14 | N. Turok and J. Zadrozny | Phase transitions in the two-doublet model | Nuclear Physics B 369 (1992) | |
| 15 | I. P. Ivanov | Building and testing models with extended Higgs sectors | Progress in Particle and Nuclear Physics 95 (2017) | 1702.03776 |
| 16 | S. Baum and N. R. Shah | Two Higgs doublets and a complex singlet: disentangling the decay topologies and associated phenomenology | JHEP 12 (2018) 044 | 1808.02667 |
| 17 | ATLAS Collaboration | ATLAS searches for additional scalars and exotic Higgs boson decays with the LHC Run 2 dataset | Physics Reports 1116 (2025) | 2405.04914 |
| 18 | CMS Collaboration | Search for Higgs boson decays into two neutral scalars with unequal masses in final states with b quarks and tau leptons in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | Submitted to JHEP, 2026 link |
|
| 19 | CMS Collaboration | Search for exotic decays of the Higgs boson to a pair of pseudoscalars in the $ \mu\mu $bb and $ \tau\tau $bb final states | EPJC 84 (2024) 493 | CMS-HIG-22-007 2402.13358 |
| 20 | CMS Collaboration | Search for light pseudoscalar boson pairs produced from Higgs boson decays using the 4$ \tau $ and 2$ \mu $2$ \tau $ final states in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | JHEP 04 (2026) 132 | CMS-SUS-24-002 2508.06947 |
| 21 | CMS Collaboration | Search for a light pseudoscalar Higgs boson in final states with boosted $ \mu\mu $ and $ \tau\tau $ pairs in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | CMS Physics Analysis Summary, 2026 CMS-PAS-SUS-23-005 |
CMS-PAS-SUS-23-005 |
| 22 | CMS Collaboration | Search for light scalar particles produced in Higgs boson decays in exclusive final states with two muons and two hadrons in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | Submitted to JHEP, 2026 link |
|
| 23 | CMS Collaboration | Search for low-mass dilepton resonances in Higgs boson decays to four-lepton final states in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | EPJC 82 (2022) 290 | CMS-HIG-19-007 2111.01299 |
| 24 | CMS Collaboration | Search for light pseudoscalar bosons, pair-produced in Higgs boson decays in the four-electron final state in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | PRL 136 (2026) 181807 | CMS-EXO-24-031 2511.19563 |
| 25 | CMS Collaboration | Search for the exotic decay of the Higgs boson into two light pseudoscalars with four photons in the final state in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | JHEP 07 (2023) 148 | CMS-HIG-21-003 2208.01469 |
| 26 | CMS Collaboration | Search for exotic Higgs boson decays $ \mathrm{H}\rightarrow\mathcal{A}\mathcal{A} $ with $ \mathcal{A}\rightarrow\gamma\gamma $ in events with a semi-merged topology in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | Submitted to JHEP, 2026 link |
|
| 27 | CMS Collaboration | Search for exotic Higgs boson decays $ \mathrm{H}\rightarrow\mathcal{A}\mathcal{A}\rightarrow4\gamma $ with events containing two merged diphotons in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | PRL 131 (2023) 101801 | CMS-HIG-21-016 2209.06197 |
| 28 | CMS Collaboration | Search for the decay of the Higgs boson to a pair of light pseudoscalar bosons in the final state with four bottom quarks in proton-proton collisions at $ \sqrt{\textrm{s}} = $ 13 TeV | JHEP 06 (2024) 097 | CMS-HIG-18-026 2403.10341 |
| 29 | ATLAS Collaboration | Search for decays of the Higgs boson into scalar particles decaying into four or six $ b $-quarks using $ pp $ collisions at $ \sqrt{s}= $ 13 TeV with the ATLAS detector | PRD 112 (2025) 072005 | 2507.01165 |
| 30 | Qu, Huilin and Gouskos, Loukas | Jet tagging via particle clouds | PRD 101 (2020) | 1902.08570 |
| 31 | CMS Collaboration | The CMS experiment at the CERN LHC | JINST 3 (2008) | |
| 32 | CMS Collaboration | Development of the CMS detector for the CERN LHC Run 3 | JINST 19 (2024) | CMS-PRF-21-001 2309.05466 |
| 33 | CMS Collaboration | Performance of the CMS Level-1 trigger in proton-proton collisions at $ \sqrt{s} = $ 13 TeV | JINST 15 (2020) | CMS-TRG-17-001 2006.10165 |
| 34 | CMS Collaboration | Performance of the CMS high-level trigger during LHC Run 2 | JINST 19 (2024) | CMS-TRG-19-001 2410.17038 |
| 35 | CMS Collaboration | Electron and photon reconstruction and identification with the CMS experiment at the CERN LHC | JINST 16 (2021) | CMS-EGM-17-001 2012.06888 |
| 36 | CMS Collaboration | Performance of the CMS muon detector and muon reconstruction with proton-proton collisions at $ \sqrt{s}= $ 13 TeV | JINST 13 (2018) | CMS-MUO-16-001 1804.04528 |
| 37 | CMS Collaboration | Operation and performance of the CMS silicon strip tracker with proton-proton collisions at the CERN LHC | JINST 20 (2025) | CMS-TRK-20-002 2506.17195 |
| 38 | CMS Collaboration | The CMS trigger system | JINST 12 (2017) P01020 | CMS-TRG-12-001 1609.02366 |
| 39 | CMS Collaboration | Technical proposal for the Phase-II upgrade of the Compact Muon Solenoid | CMS Technical Proposal CERN-LHCC-2015-010, CMS-TDR-15-02, 2015 CDS |
|
| 40 | CMS Collaboration | Particle-flow reconstruction and global event description with the CMS detector | JINST 12 (2017) | CMS-PRF-14-001 1706.04965 |
| 41 | E. Bols et al. | Jet flavour classification using deepjet | JINST 15 (2020) P12012 | 2008.10519 |
| 42 | M. Dasgupta, A. Fregoso, S. Marzani, and G. P. Salam | Towards an understanding of jet substructure | JHEP 09 (2013) 029 | 1307.0007 |
| 43 | J. M. Butterworth, A. R. Davison, M. Rubin, and G. P. Salam | Jet substructure as a new Higgs search channel at the LHC | PRL 100 (2008) 242001 | 0802.2470 |
| 44 | CMS Collaboration | Performance of heavy-flavour jet identification in Lorentz-boosted topologies in proton-proton collisions at \ensuremath\sqrt(s) = 13 TeV | JINST 20 (2025) P11006 | CMS-BTV-22-001 2510.10228 |
| 45 | CMS Collaboration | Performance of missing transverse momentum reconstruction in proton-proton collisions at $ \sqrt{s} = $ 13 TeV using the CMS detector | JINST 14 (2019) | CMS-JME-17-001 1903.06078 |
| 46 | J. Alwall et al. | The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations | JHEP 07 (2014) 079 | 1405.0301 |
| 47 | T. Sjöstrand et al. | An introduction to PYTHIA8.2 | Comput. Phys. Commun. 191 (2015) 159 | 1410.3012 |
| 48 | K. Hamilton, P. Nason, E. Re, and G. Zanderighi | NNLOPS simulation of Higgs boson production | JHEP 10 (2013) 222 | 1309.0017 |
| 49 | S. Frixione, P. Nason, and C. Oleari | Matching NLO QCD computations with parton shower simulations: the POWHEG method | JHEP 11 (2007) 070 | 0709.2092 |
| 50 | S. Alioli, P. Nason, C. Oleari, and E. Re | A general framework for implementing NLO calculations in shower Monte Carlo programs: the POWHEG box | JHEP 06 (2010) 043 | 1002.2581 |
| 51 | P. Nason | A new method for combining NLO QCD with shower Monte Carlo algorithms | JHEP 11 (2004) 040 | hep-ph/0409146 |
| 52 | T. Je \v z o and P. Nason | On the treatment of resonances in next-to-leading order calculations matched to a parton shower | JHEP 12 (2015) 065 | 1509.09071 |
| 53 | J. Alwall et al. | Comparative study of various algorithms for the merging of parton showers and matrix elements in hadronic collisions | EPJC 53 (2008) 473 | 0706.2569 |
| 54 | CMS Collaboration | Extraction and validation of a new set of CMS PYTHIA8 tunes from underlying-event measurements | EPJC 80 (2020) 4 | CMS-GEN-17-001 1903.12179 |
| 55 | NNPDF Collaboration | Parton distributions from high-precision collider data | EPJC 77 (2017) 663 | 1706.00428 |
| 56 | GEANT4 Collaboration | GEANT 4---a simulation toolkit | NIM A 506 (2003) 250 | |
| 57 | CMS Collaboration | A method for correcting the substructure of multiprong jets using the Lund jet plane | JHEP 11 (2025) 038 | CMS-JME-23-001 2507.07775 |
| 58 | L. Corcodilos | The 2D Alphabet background modeling method and its use in the search for an excited bottom quark | PhD thesis, Johns Hopkins University, 2021 link |
|
| 59 | CMS Collaboration | Search for a heavy resonance decaying to a top quark and a W boson at $ \sqrt{s} = $ 13 TeV in the fully hadronic final state | JHEP 12 (2021) 106 | 2104.12853 |
| 60 | CMS Collaboration | Precision luminosity measurement in proton-proton collisions at $ \sqrt{s}= $ 13 TeV in 2015 and 2016 at CMS | EPJC 81 (2021) 800 | CMS-LUM-17-003 2104.01927 |
| 61 | CMS Collaboration | Precision luminosity measurement in proton-proton collisions at a center-of-mass energy of 13 TeV with the CMS detector at the Large Hadron Collider | CMS-LUM-20-001 2606.26832 |
|
| 62 | CMS Collaboration | The CMS statistical analysis and combination tool: Combine | Comput. Softw. Big Sci. 8 (2024) 19 | CMS-CAT-23-001 2404.06614 |
| 63 | W. Verkerke and D. Kirkby | The RooFit toolkit for data modeling | in the Int. Conf. on Computing in High Energy and Nuclear Physics (CHEP ): La Jolla CA, United States, March 24--28, 2003 Proc. 1 (2003) 3 |
physics/0306116 |
| 64 | L. Moneta et al. | The RooStats project | in the Int. Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT ): Jaipur, India, February 22--27, 2010 Proc. 1 (2010) 3 |
1009.1003 |
| 65 | T. Junk | Confidence level computation for combining searches with small statistics | NIM A 434 (1999) 435 | hep-ex/9902006 |
| 66 | A. L. Read | Presentation of search results: The CL$ _{\text{s}} $ technique | JPG 28 (2002) 2693 | |
| 67 | G. Cowan, K. Cranmer, E. Gross, and O. Vitells | Asymptotic formulae for likelihood-based tests of new physics | EPJC 71 (2011) 1554 | 1007.1727 |
|
|
Compact Muon Solenoid LHC, CERN |
|
|
|
|
|
|