CMS logoCMS event Hgg
Compact Muon Solenoid
LHC, CERN

CMS-HIG-24-003 ; CERN-EP-2026-080
Search for associated production of a Higgs boson and two vector bosons via vector boson scattering at $ \sqrt{s} = $ 13 TeV
Submitted to Physical Review Letters
Abstract: A search for Higgs boson (H) production in association with two vector bosons ($ \mathrm{V} = \mathrm{W} $, Z) via vector boson scattering (VBS) is presented using proton-proton collision data collected at $ \sqrt{s}= $ 13 TeV by the CMS experiment, corresponding to an integrated luminosity of 138 fb$ ^{-1} $. Events containing two forward jets consistent with VBS, a large-radius jet from the decay of a boosted H to a pair of b quarks, and 0, 1, or 2 charged leptons coming from V decays are selected. The process is excluded at 95%CL for observed (expected) values of the $ \mathrm{V}\mathrm{V}\mathrm{H}\mathrm{H} $ coupling modifier $ \kappa_{2\mathrm{V}} $ outside the interval 0.40 $ < \kappa_{2\mathrm{V}} < $ 1.60 (0.34 $ < \kappa_{2\mathrm{V}} < $ 1.66), assuming standard model values for all other couplings, thus establishing a novel probe of the $ \mathrm{V}\mathrm{V}\mathrm{H}\mathrm{H} $ interaction. Constraints are also set on the individual $ \kappa_{2\mathrm{W}} $ and $ \kappa_{2\mathrm{Z}} $ coupling modifiers, and on the allowed region in the $ \kappa_{2\mathrm{W}}-\kappa_{2\mathrm{Z}} $ plane.
Figures & Tables Summary References CMS Publications
Figures

png pdf
Figure 1:
Examples of tree-level Feynman diagrams for the production of $ \mathrm{V}\mathrm{V}\mathrm{H} $ via VBS, with dependencies on the H self-coupling (left) and the $ \mathrm{V}\mathrm{V}\mathrm{H}\mathrm{H} $ quartic coupling (right). The corresponding vertices are denoted by the $ \kappa_{\lambda} $ and $ \kappa_{2\mathrm{V}} $ modifiers, respectively.

png pdf
Figure 1-a:
Examples of tree-level Feynman diagrams for the production of $ \mathrm{V}\mathrm{V}\mathrm{H} $ via VBS, with dependencies on the H self-coupling (left) and the $ \mathrm{V}\mathrm{V}\mathrm{H}\mathrm{H} $ quartic coupling (right). The corresponding vertices are denoted by the $ \kappa_{\lambda} $ and $ \kappa_{2\mathrm{V}} $ modifiers, respectively.

png pdf
Figure 1-b:
Examples of tree-level Feynman diagrams for the production of $ \mathrm{V}\mathrm{V}\mathrm{H} $ via VBS, with dependencies on the H self-coupling (left) and the $ \mathrm{V}\mathrm{V}\mathrm{H}\mathrm{H} $ quartic coupling (right). The corresponding vertices are denoted by the $ \kappa_{\lambda} $ and $ \kappa_{2\mathrm{V}} $ modifiers, respectively.

png pdf
Figure 2:
Observed (solid) and expected (dashed) 95% CL constraints on the VBS $ \mathrm{V}\mathrm{V}\mathrm{H} $ production cross section as a function of $ \kappa_{2\mathrm{V}} $, with other couplings fixed to their SM values. The intersections with the predicted cross section (blue) indicate the excluded $ \kappa_{2\mathrm{V}} $ ranges.

png pdf
Figure 3:
Observed (solid) and expected (dashed) 95% CL constraints on the VBS $ \mathrm{V}\mathrm{V}\mathrm{H} $ production cross section as a function of $ \kappa_{2\mathrm{W}} $ (left) and $ \kappa_{2\mathrm{Z}} $ (right). The intersections with the predicted cross section (blue) indicate excluded coupling ranges.

png pdf
Figure 3-a:
Observed (solid) and expected (dashed) 95% CL constraints on the VBS $ \mathrm{V}\mathrm{V}\mathrm{H} $ production cross section as a function of $ \kappa_{2\mathrm{W}} $ (left) and $ \kappa_{2\mathrm{Z}} $ (right). The intersections with the predicted cross section (blue) indicate excluded coupling ranges.

png pdf
Figure 3-b:
Observed (solid) and expected (dashed) 95% CL constraints on the VBS $ \mathrm{V}\mathrm{V}\mathrm{H} $ production cross section as a function of $ \kappa_{2\mathrm{W}} $ (left) and $ \kappa_{2\mathrm{Z}} $ (right). The intersections with the predicted cross section (blue) indicate excluded coupling ranges.

png pdf
Figure 4:
Observed (solid) and expected (dashed) exclusion regions corresponding to 1, 2, and 5 standard deviations ($ \sigma $), as obtained from a likelihood scan in the two-dimensional $ \kappa_{2\mathrm{W}}-\kappa_{2\mathrm{Z}} $ plane.

png pdf
Figure A1:
Two-dimensional distributions of the DNN output and the $ |\Delta\eta_{\mathrm{j}\mathrm{j}}| $ in the all-hadronic channel, as obtained in data. These are the axes used in this channel to define the ABCD samples. A profile histogram is overlaid to better depict the statistical independence of the two variables.

png pdf
Figure A2:
Two-dimensional distributions of the DNN output and the $ |\Delta\eta_{\mathrm{j}\mathrm{j}}| $ in the all-hadronic channel, as obtained in background simulated events. These are the axes used in this channel to define the ABCD samples. A profile histogram is overlaid to better depict the statistical independence of the two variables.

png pdf
Figure A3:
Two-dimensional distributions of the DNN output and the VBS BDT output in the single-lepton channel, as obtained in data. These are the axes used in this channel to define the ABCD samples. A profile histogram is overlaid to better depict the statistical independence of the two variables.

png pdf
Figure A4:
Two-dimensional distributions of the DNN output and the VBS BDT output in the single-lepton channel, as obtained in background simulated events. These are the axes used in this channel to define the ABCD samples. A profile histogram is overlaid to better depict the statistical independence of the two variables.

png pdf
Figure A5:
Distribution of the DNN output in the regions B and D of the all-hadronic channel. The expected signal for the standard model scenario (orange) and for $ \kappa_{2\mathrm{V}} = $ 2 (red) is superimposed to the data (black markers). The cross section used for signal is computed at leading order using MADGRAPH, and is scaled by a factor 1000 (100) for the SM ($ \kappa_{2\mathrm{V}} = $ 2) signal to improve visibility.

png pdf
Figure A6:
Distribution of the DNN output in the regions A and C of the all-hadronic channel. The expected signal for the standard model scenario (orange) and for $ \kappa_{2\mathrm{V}} = $ 2 (red) is superimposed to the data (black markers). The cross section used for signal is computed at leading order using MADGRAPH, and is scaled by a factor 10 for the SM signal to improve visibility.

png pdf
Figure A7:
Distribution of the DNN output in the regions B and D of the single-lepton channel. The expected signal for the standard model scenario (orange) and for $ \kappa_{2\mathrm{V}} = $ 2 (red) is superimposed to the data (black markers). The cross section used for signal is computed at leading order using MADGRAPH, and is scaled by a factor 1000 (100) for the SM ($ \kappa_{2\mathrm{V}} = $ 2) signal to improve visibility.

png pdf
Figure A8:
Distribution of the DNN output in the regions A and C of the single-lepton channel. The expected signal for the standard model scenario (orange) and for $ \kappa_{2\mathrm{V}} = $ 2 (red) is superimposed to the data (black markers). The cross section used for signal is computed at leading order using MADGRAPH, and is scaled by a factor 10 for the SM signal to improve visibility.

png pdf
Figure A9:
Comparison of the expected (left) and observed (right) 95% CL limits on $ \kappa_{2\mathrm{V}} $. The combined limit is shown as in black, while the limits obtained in individual channel are shown as colored lines.

png pdf
Figure A9-a:
Comparison of the expected (left) and observed (right) 95% CL limits on $ \kappa_{2\mathrm{V}} $. The combined limit is shown as in black, while the limits obtained in individual channel are shown as colored lines.

png pdf
Figure A9-b:
Comparison of the expected (left) and observed (right) 95% CL limits on $ \kappa_{2\mathrm{V}} $. The combined limit is shown as in black, while the limits obtained in individual channel are shown as colored lines.

png pdf
Figure A10:
Comparison of the expected (left) and observed (right) 95% CL limits on $ \kappa_{2\mathrm{W}} $. The combined limit is shown as in black, while the limits obtained in individual channel are shown as colored lines.

png pdf
Figure A10-a:
Comparison of the expected (left) and observed (right) 95% CL limits on $ \kappa_{2\mathrm{W}} $. The combined limit is shown as in black, while the limits obtained in individual channel are shown as colored lines.

png pdf
Figure A10-b:
Comparison of the expected (left) and observed (right) 95% CL limits on $ \kappa_{2\mathrm{W}} $. The combined limit is shown as in black, while the limits obtained in individual channel are shown as colored lines.

png pdf
Figure A11:
Comparison of the expected (left) and observed (right) 95% CL limits on $ \kappa_{2\mathrm{Z}} $. The combined limit is shown as in black, while the limits obtained in individual channel are shown as colored lines.

png pdf
Figure A11-a:
Comparison of the expected (left) and observed (right) 95% CL limits on $ \kappa_{2\mathrm{Z}} $. The combined limit is shown as in black, while the limits obtained in individual channel are shown as colored lines.

png pdf
Figure A11-b:
Comparison of the expected (left) and observed (right) 95% CL limits on $ \kappa_{2\mathrm{Z}} $. The combined limit is shown as in black, while the limits obtained in individual channel are shown as colored lines.

png pdf
Figure A12:
Comparison of the expected (left) and observed (right) exclusion regions corresponding to 2 standard deviations ($ \sigma $), in the two-dimensional $ \kappa_{2\mathrm{W}}-\kappa_{2\mathrm{Z}} $ plane. The combined exclusion region is shown as in black, while the exclusion regions obtained in individual channel are shown as colored lines.

png pdf
Figure A12-a:
Comparison of the expected (left) and observed (right) exclusion regions corresponding to 2 standard deviations ($ \sigma $), in the two-dimensional $ \kappa_{2\mathrm{W}}-\kappa_{2\mathrm{Z}} $ plane. The combined exclusion region is shown as in black, while the exclusion regions obtained in individual channel are shown as colored lines.

png pdf
Figure A12-b:
Comparison of the expected (left) and observed (right) exclusion regions corresponding to 2 standard deviations ($ \sigma $), in the two-dimensional $ \kappa_{2\mathrm{W}}-\kappa_{2\mathrm{Z}} $ plane. The combined exclusion region is shown as in black, while the exclusion regions obtained in individual channel are shown as colored lines.
Tables

png pdf
Table 1:
Selection criteria used in the all-hadronic fully boosted channel. If selection criteria differ across years, they are quoted as ``2016/2017/2018''.

png pdf
Table 2:
Selection criteria used in the all-hadronic semi-boosted channel. If the selection criteria differ across years, they are quoted as ``2016/2017/2018''.

png pdf
Table 3:
Selection criteria used in the single-lepton channel. If the selection criteria differ across years, they are quoted as ``2016/2017/2018''.

png pdf
Table 4:
Selection criteria in used the OS WW dilepton channel. If the selection criteria differ across years, they are quoted as ``2016/2017/2018''.

png pdf
Table 5:
Selection criteria used in the OS Z dilepton channel. If the selection criteria differ across years, they are quoted as ``2016/2017/2018''.

png pdf
Table 6:
Selection criteria used in the SS dilepton channel. If the selection criteria differ across years, they are quoted as ``2016/2017/2018''.

png pdf
Table 7:
Summary of the selections used to define the signal region, or region A, in the all-hadronic, single-lepton, and OS dilepton channels. The selections on the ``AB axis'' and ``AC axis'' are inverted to define the regions B, C and D. Additional selections on the $ X\to\mathrm{b}\overline{\mathrm{b}} $ and $ X\to\mathrm{qq} $ scores are applied after the training to further improve the sensitivity of the search. For the all-hadronic fully boosted channel, the selections on the $ X\to\mathrm{qq} $ score are applied on the $ p_{\mathrm{T}} $-leading/subleading vector boson candidates.

png pdf
Table 8:
Data yields in regions B, C and D, used to estimate the background in region A, along with data, predicted background, and expected signal in region A. Signal yields are shown for the SM and $ \kappa_{2\mathrm{V}}= $ 2 benchmarks.

png pdf
Table 9:
Data yields, predicted background and expected signal in signal (SR) and control regions (CR) of the same-sign dilepton channel.
Summary
In summary, the first study of VVH production through vector boson scattering is presented, using proton-proton collision data recorded by the CMS experiment at the LHC in 2016--2018, at $\sqrt{s} = 13$ TeV, corresponding to an integrated luminosity of 138 fb$ ^{-1}$. Selected events are consistent with the presence of two jets originating from VBS and an H decaying into a pair of b quarks, reconstructed as a single large-radius jet. Final states with zero, one, or two charged leptons arising from the decay of two vector bosons are studied. The VBS VVH production is excluded at 95% CL for values of the $k_{2V}$ coupling modifier outside the observed (expected) range of $0.40 < k_{2V} < 1.60$ ($0.34 < k_{2V} < 1.66$), assuming all other H couplings are equal to their values in the standard model.The results represent one of the best constraints to date on $k_{2V}$ using CMS data, complementing the results obtained from searches for H pair production, and laying the foundation for future, similar studies.The $k_{2W}$ and $k_{2Z}$ coupling modifiers are also constrained independently in the observed (expected) ranges of $0.17 < k_{2W}< 1.84$ ($0.11 < k_{2W} < 1.89$) and $-0.37 < k_{2Z} < 2.38$ ($-0.54 < k_{2Z} < 2.54$), respectively. A two-dimensional scan, determining exclusion regions in the $k_{2W}-k_{2Z}$ plane, is also provided, which largely improves on the constraints coming from the CMS search for VHH production.
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 LHC Higgs Cross Section Working Group , S. Heinemeyer et al. Handbook of LHC Higgs cross sections: 3. Higgs properties CERN Report CERN-2013-004, 2013
link
1307.1347
5 LHC Higgs Cross Section Working Group , D. de Florian et al. Handbook of LHC Higgs cross sections: 4. Deciphering the nature of the Higgs sector CERN Report CERN-2017-002-M, 2016
link
1610.07922
6 CMS Collaboration Combination of searches for nonresonant Higgs boson pair production in proton-proton collisions at $ \sqrt{s} = $ 13 TeV Submitted to Journal of Physics G, 2025 CMS-HIG-20-011
2510.07527
7 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) 101801 2406.09971
8 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
9 CMS Collaboration Search for Higgs boson pair production with one associated vector boson in proton-proton collisions at $ \sqrt{s} = $ 13 TeV JHEP 10 (2024) 061 CMS-HIG-22-006
2404.08462
10 CMS Collaboration The CMS experiment at the CERN LHC JINST 3 (2008) S08004
11 CMS Collaboration Development of the CMS detector for the CERN LHC Run 3 JINST 19 (2024) P05064 CMS-PRF-21-001
2309.05466
12 CMS Collaboration Performance of the CMS Level-1 trigger in proton-proton collisions at $ \sqrt{s} = $ 13 TeV JINST 15 (2020) P10017 CMS-TRG-17-001
2006.10165
13 CMS Collaboration The CMS trigger system JINST 12 (2017) P01020 CMS-TRG-12-001
1609.02366
14 CMS Collaboration Performance of the CMS high-level trigger during LHC Run 2 JINST 19 (2024) P11021 CMS-TRG-19-001
2410.17038
15 CMS Collaboration Electron and photon reconstruction and identification with the CMS experiment at the CERN LHC JINST 16 (2021) P05014 CMS-EGM-17-001
2012.06888
16 CMS Collaboration Performance of the CMS muon detector and muon reconstruction with proton-proton collisions at $ \sqrt{s}= $ 13 TeV JINST 13 (2018) P06015 CMS-MUO-16-001
1804.04528
17 CMS Collaboration Description and performance of track and primary-vertex reconstruction with the CMS tracker JINST 9 (2014) P10009 CMS-TRK-11-001
1405.6569
18 CMS Collaboration Particle-flow reconstruction and global event description with the CMS detector JINST 12 (2017) P10003 CMS-PRF-14-001
1706.04965
19 CMS Collaboration Performance of reconstruction and identification of $ \tau $ leptons decaying to hadrons and $ \nu_\tau $ in pp collisions at $ \sqrt{s}= $ 13 TeV JINST 13 (2018) P10005 CMS-TAU-16-003
1809.02816
20 CMS Collaboration Jet energy scale and resolution in the CMS experiment in pp collisions at 8 TeV JINST 12 (2017) P02014 CMS-JME-13-004
1607.03663
21 CMS Collaboration Performance of missing transverse momentum reconstruction in proton-proton collisions at $ \sqrt{s} = $ 13 TeV using the CMS detector JINST 14 (2019) P07004 CMS-JME-17-001
1903.06078
22 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
23 CMS Collaboration ECAL 2016 refined calibration and Run2 summary plots CMS Detector Performance Summary CMS-DP-2020-021, 2020
CDS
24 CMS Collaboration Measurement of the Higgs boson production rate in association with top quarks in final states with electrons, muons, and hadronically decaying tau leptons at $ \sqrt{s} = $ 13 TeV EPJC 81 (2021) 378 CMS-HIG-19-008
2011.03652
25 CMS Collaboration Identification of hadronic tau lepton decays using a deep neural network JINST 17 (2022) P07023 CMS-TAU-20-001
2201.08458
26 M. Cacciari, G. P. Salam, and G. Soyez The anti-$ k_{\mathrm{T}} $ jet clustering algorithm JHEP 04 (2008) 063 0802.1189
27 M. Cacciari, G. P. Salam, and G. Soyez FastJet user manual EPJC 72 (2012) 1896 1111.6097
28 CMS Collaboration Pileup mitigation at CMS in 13 TeV data JINST 15 (2020) P09018 CMS-JME-18-001
2003.00503
29 D. Bertolini, P. Harris, M. Low, and N. Tran Pileup per particle identification JHEP 10 (2014) 059 1407.6013
30 H. Qu and L. Gouskos ParticleNet: Jet tagging via particle clouds PRD 101 (2020) 056019 1902.08570
31 A. J. Larkoski, S. Marzani, G. Soyez, and J. Thaler Soft drop JHEP 05 (2014) 146 1402.2657
32 M. Dasgupta, A. Fregoso, S. Marzani, and G. P. Salam Towards an understanding of jet substructure JHEP 09 (2013) 029 1307.0007
33 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
34 CMS Collaboration Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV JINST 13 (2018) P05011 CMS-BTV-16-002
1712.07158
35 E. Bols et al. Jet flavour classification using DeepJet JINST 15 (2020) P12012 2008.10519
36 CMS Collaboration Performance of the DeepJet b tagging algorithm using 41.9 fb$^{-1}$ of data from proton-proton collisions at 13 TeV with Phase 1 CMS detector CMS Detector Performance Summary CMS-DP-2018-058, 2018
CDS
37 T. Sjöstrand et al. An introduction to PYTHIA 8.2 Comput. Phys. Commun. 191 (2015) 159 1410.3012
38 B. Cabouat and T. Sjöstrand Some dipole shower studies EPJC 78 (2018) 226 1710.00391
39 O. Mattelaer On the maximal use of Monte Carlo samples: re-weighting events at NLO accuracy EPJC 76 (2016) 674 1607.00763
40 S. Frixione, P. Nason, and G. Ridolfi A positive-weight next-to-leading-order Monte Carlo for heavy flavour hadroproduction JHEP 09 (2007) 126 0707.3088
41 P. Nason A new method for combining NLO QCD with shower Monte Carlo algorithms JHEP 11 (2004) 040 hep-ph/0409146
42 S. Frixione, P. Nason, and C. Oleari Matching NLO QCD computations with parton shower simulations: the POWHEG method JHEP 11 (2007) 070 0709.2092
43 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
44 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
45 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
46 NNPDF Collaboration Parton distributions for the LHC Run II JHEP 04 (2015) 040 1410.8849
47 NNPDF Collaboration Parton distributions from high-precision collider data EPJC 77 (2017) 663 1706.00428
48 GEANT4 Collaboration GEANT 4---a simulation toolkit NIM A 506 (2003) 250
49 CDF Collaboration Measurement of $ \sigma B (W \to e \nu) $ and $ \sigma B (Z^0 \to e^+ e^-) $ in $ \bar{p}p $ collisions at $ \sqrt{s} = $ 1800 GeV PRD 44 (1991) 29
50 G. Kasieczka, B. Nachman, M. D. Schwartz, and D. Shih Automating the ABCD method with machine learning PRD 103 (2021) 035021 2007.14400
51 Particle Data Group , S. Navas et al. Review of particle physics PRD 110 (2024) 030001
52 CMS Collaboration The CMS statistical analysis and combination tool: Combine Comput. Softw. Big Sci. 8 (2024) 19 CMS-CAT-23-001
2404.06614
53 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
54 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
55 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
56 CMS Collaboration CMS luminosity measurement for the 2017 data-taking period at $ \sqrt{s}= $ 13 TeV CMS Physics Analysis Summary, 2018
link
CMS-PAS-LUM-17-004
57 CMS Collaboration CMS luminosity measurement for the 2018 data-taking period at $ \sqrt{s}= $ 13 TeV CMS Physics Analysis Summary, 2019
link
CMS-PAS-LUM-18-002
58 CMS Collaboration HEPData record for this analysis link
59 CMS Collaboration Supplemental Material URL will be inserted by publisher
Compact Muon Solenoid
LHC, CERN