CMS logoCMS event Hgg
Compact Muon Solenoid
LHC, CERN

CMS-PAS-HIG-21-020
Search for boosted Higgs bosons produced via vector boson fusion in the H $\rightarrow b\bar{b} $ decay mode using LHC proton-proton collision data at $ \sqrt{s} = $ 13 TeV
Abstract: A search is conducted for Higgs bosons produced with high transverse momentum ($ p_{\mathrm{T}} > $ 450 GeV) via vector boson fusion at the LHC proton-proton collider operating at center of mass energy $ \sqrt{s}= $ 13 TeV. The result is based on the 138 fb$ ^{-1} $ data set collected by the CMS detector in 2016, 2017, and 2018. The decay of a high-$ p_{\mathrm{T}} $ Higgs boson to a boosted bottom quark-antiquark pair is isolated by selecting large-radius jets and exploiting jet substructure and heavy flavour taggers based on advanced machine learning techniques. Independent regions targeting vector boson fusion and gluon-gluon fusion are defined based on the topology of forward quark jets. The signal strengths for both processes are extracted simultaneously by performing a maximum likelihood fit to data in the large-radius jet mass distribution. The observed signal strengths are 2.1$ ^{+1.9}_{-1.7} $ and 5.0$ ^{+2.1}_{-1.8} $ for gluon-gluon fusion and vector boson fusion, respectively.
Figures & Tables Summary References CMS Publications
Figures

png pdf
Figure 1:
Lowest order Feynman diagrams of the Higgs boson production modes with highest cross section in 13 TeV proton-proton collisions: gluon-gluon fusion (left) and vector boson fusion (right).

png pdf
Figure 2:
Soft drop mass distribution in simulated QCD events after applying DEEPDOUBLEBVL-V2 selection at different working points. The distributions are obtained from Gaussian kernel density estimation and normalized to unit area. The effect of the tagger selection on the shape is quantified with the Jensen-Shannon divergence $ D_{JS} $ [61]. The lower panel shows the absolute difference from the inclusive distribution.

png pdf
Figure 3:
MC prediction of the relative contribution of each production mode to the total Higgs signal yield in the ggF and VBF categories. The DDB passing and failing regions are shown separately.

png pdf
Figure 4:
Data and fitted soft drop mass distribution in the VBF category, summed over all $ m_{\mathrm{jj}} $ bins and data-taking periods. The DDB failing (left) and passing (right) regions are shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 4-a:
Data and fitted soft drop mass distribution in the VBF category, summed over all $ m_{\mathrm{jj}} $ bins and data-taking periods. The DDB failing (left) and passing (right) regions are shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 4-b:
Data and fitted soft drop mass distribution in the VBF category, summed over all $ m_{\mathrm{jj}} $ bins and data-taking periods. The DDB failing (left) and passing (right) regions are shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 5:
Data and fitted soft drop mass distribution in the ggF category, summed over all $ p_{\mathrm{T}} $ bins and data-taking periods. The DDB failing (left) and passing (right) regions are shown. The ggF and VBF signals are scaled to the fitted event yields. The apparent discontinuity at high mass is due to the exclusion of bins with extreme values of $ \rho $.

png pdf
Figure 5-a:
Data and fitted soft drop mass distribution in the ggF category, summed over all $ p_{\mathrm{T}} $ bins and data-taking periods. The DDB failing (left) and passing (right) regions are shown. The ggF and VBF signals are scaled to the fitted event yields. The apparent discontinuity at high mass is due to the exclusion of bins with extreme values of $ \rho $.

png pdf
Figure 5-b:
Data and fitted soft drop mass distribution in the ggF category, summed over all $ p_{\mathrm{T}} $ bins and data-taking periods. The DDB failing (left) and passing (right) regions are shown. The ggF and VBF signals are scaled to the fitted event yields. The apparent discontinuity at high mass is due to the exclusion of bins with extreme values of $ \rho $.

png pdf
Figure 6:
Two-dimensional likelihood contour of the ggF and VBF signal strengths. The color scale represents twice the negative log likelihood difference with respect to the best fit point. The observed 95% (dashed) and 68% (solid) contours are shown in white, and the best fit point as a white cross. The SM expectation is marked by a red star.

png pdf
Figure 7:
Data and fitted soft drop mass distribution in each of the two $ m_{\mathrm{jj}} $ bins in the VBF category, summed over all data-taking periods. The DDB passing region is shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 7-a:
Data and fitted soft drop mass distribution in each of the two $ m_{\mathrm{jj}} $ bins in the VBF category, summed over all data-taking periods. The DDB passing region is shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 7-b:
Data and fitted soft drop mass distribution in each of the two $ m_{\mathrm{jj}} $ bins in the VBF category, summed over all data-taking periods. The DDB passing region is shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 8:
Data and fitted soft drop mass distribution in each of the $ {p_{\mathrm{T}}} $ bins in the ggF category, summed over all data-taking periods. The DDB passing region is shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 8-a:
Data and fitted soft drop mass distribution in each of the $ {p_{\mathrm{T}}} $ bins in the ggF category, summed over all data-taking periods. The DDB passing region is shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 8-b:
Data and fitted soft drop mass distribution in each of the $ {p_{\mathrm{T}}} $ bins in the ggF category, summed over all data-taking periods. The DDB passing region is shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 8-c:
Data and fitted soft drop mass distribution in each of the $ {p_{\mathrm{T}}} $ bins in the ggF category, summed over all data-taking periods. The DDB passing region is shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 8-d:
Data and fitted soft drop mass distribution in each of the $ {p_{\mathrm{T}}} $ bins in the ggF category, summed over all data-taking periods. The DDB passing region is shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 8-e:
Data and fitted soft drop mass distribution in each of the $ {p_{\mathrm{T}}} $ bins in the ggF category, summed over all data-taking periods. The DDB passing region is shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 8-f:
Data and fitted soft drop mass distribution in each of the $ {p_{\mathrm{T}}} $ bins in the ggF category, summed over all data-taking periods. The DDB passing region is shown. The ggF and VBF signals are scaled to the fitted event yields.

png pdf
Figure 9:
Top: the ggF signal strength is shown in black fitted per $ p_{\mathrm{T}} $ bin, with the ratio of ggF/VBF fixed to the SM expectation. The combined ggF signal strength and uncertainty is shown in blue. The SM expectation is shown as a dashed line. Bottom: the VBF signal strength is shown in black fitted per $ m_{\mathrm{jj}} $ bin, with the ratio of ggF/VBF fixed to the SM expectation. The combined VBF signal strength and uncertainty is shown in blue. The SM expectation is shown as a dashed line.
Tables

png pdf
Table 1:
Summary of data-to-simulation corrections for the jet mass scale, jet mass resolution, and jet substructure selection for different data taking periods.

png pdf
Table 2:
Fitted signal strength for H $\to\mathrm{b}\overline{\mathrm{b}} $ in the ggF and VBF channels for each year of data taking and for the full data set. Data from 2016 is split into an early and late period due to mid-year changes in the detector configuration.
Summary
A search has been conducted for boosted Higgs bosons produced in the gluon-gluon fusion (ggF) and vector boson fusion (VBF) production modes. This search goes beyond the inclusive H $\to\mathrm{b}\overline{\mathrm{b}} $ measurements performed thus far to provide the first exploration of Higgs bosons produced with high transverse momentum ($ p_{\mathrm{T}} > $ 450 GeV) in the VBF channel. The signal strengths of the VBF and ggF processes are extracted simultaneously, and two-dimensional contours are determined. The observed signal strengths for the VBF and ggF processes are 5.0$ ^{+2.1}_{-1.8} $ and 2.1$ ^{+1.9}_{-1.7} $, corresponding respectively to observed (expected) significances of 3.0$ \sigma $ (0.9$ \sigma $) and 1.2$ \sigma $ (0.9$ \sigma $). The results are also presented as differential distributions in $ p_{\mathrm{T}} $ for ggF and in the invariant mass of the forward quark jets for VBF. Because measurements of the Higgs boson at high $ p_{\mathrm{T}} $ are particularly sensitive to physics beyond the standard model, these results provide an important step forward in the exploration of the Higgs boson and its interactions.
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 2013 (2013) CMS-HIG-12-036
1303.4571
4 A. Salam Weak and electromagnetic interactions Proceedings of the eighth Nobel symposium, in Elementary particle physics: relativistic groups and analyticity, N. Svartholm, ed., . Almqvist & Wiksell, Stockholm, 1968
5 S. L. Glashow Partial-symmetries of weak interactions NP 22 (1961) 579
6 S. Weinberg A model of leptons PRL 19 (1967) 1264
7 F. Englert and R. Brout Broken symmetry and the mass of gauge vector mesons PRL 13 (1964) 321
8 P. W. Higgs Broken symmetries, massless particles and gauge fields PRL 12 (1964) 132
9 P. W. Higgs Broken symmetries and the masses of gauge bosons PRL 13 (1964) 508
10 P. W. Higgs Spontaneous symmetry breakdown without massless bosons PRL 145 (1966) 1156
11 G. S. Guralnik, C. R. Hagen, and T. W. B. Kibble Global conservation laws and massless particless PRL 13 (1964) 585
12 ATLAS Collaboration Combined measurements of Higgs boson production and decay using up to 80 fb$ ^{-1} $ of proton-proton collision data at $ \sqrt{s}= $ 13 TeV collected with the ATLAS experiment PRD 101 (2020) 1909.02845
13 CMS Collaboration Combined measurements of Higgs boson couplings in proton-proton collisions at $ \sqrt{s}= $ 13 TeV EPJC 79 (2019) CMS-HIG-17-031
1809.10733
14 F. Maltoni, K. Mawatari, and M. Zaro Higgs characterisation via vector-boson fusion and associated production: NLO and parton-shower effects EPJC 74 (2014) 1311.1829
15 K. Becker et al. Precise predictions for boosted Higgs production Technical Report CERN-TH-2020-074, 2021
link
2005.07762
16 CMS Collaboration Inclusive search for highly boosted Higgs bosons decaying to bottom quark-antiquark pairs in proton-proton collisions at $ \sqrt{s}= $ 13 TeV JHEP 2020 (2020) CMS-HIG-19-003
2006.13251
17 G. Aad et al. Constraints on Higgs boson production with large transverse momentum using H $\rightarrow b\bar{b} $ decays in the ATLAS detector PRD 105 (2022) 2111.08340
18 CMS Collaboration Precision luminosity measurement in proton-proton collisions at $ \sqrt{s} = $ 13 TeV in 2015 and 2016 at CMS EPJC 81 (2021) CMS-LUM-17-003
2104.01927
19 CMS Collaboration CMS luminosity measurement for the 2017 data-taking period at $ \sqrt{s} = $ 13 TeV CMS Physics Analysis Summary, CERN, Geneva, 2018
CMS-PAS-LUM-17-004
CMS-PAS-LUM-17-004
20 CMS Collaboration CMS luminosity measurement for the 2018 data-taking period at $ \sqrt{s} = $ 13 TeV CMS Physics Analysis Summary, CERN, Geneva, 2019
CMS-PAS-LUM-18-002
CMS-PAS-LUM-18-002
21 CMS Collaboration Performance of the mass-decorrelated DeepDoubleX classifier for double-b and double-c large-radius jets with the CMS detector Detector and Performance Note, CMS-DP-2022-041, 2022
CDS
22 CMS Collaboration The CMS Experiment at the CERN LHC JINST 3 (2008) S08004
23 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
24 CMS Collaboration The CMS trigger system JINST 12 (2017) P01020 CMS-TRG-12-001
1609.02366
25 CMS Collaboration Performance of electron reconstruction and selection with the CMS detector in proton-proton collisions at $ \sqrt{s}= $ 8 TeV JINST 10 (2015) P06005 CMS-EGM-13-001
1502.02701
26 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
27 CMS Collaboration Performance of photon reconstruction and identification with the CMS detector in proton-proton collisions at $ \sqrt{s}= $ 8 TeV JINST 10 (2015) P08010 CMS-EGM-14-001
1502.02702
28 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
29 GEANT4 Collaboration GEANT 4---a simulation toolkit NIM A 506 (2003) 250
30 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 2014 (2014) 1405.0301
31 J. Alwall et al. Comparative study of various algorithms for the merging of parton showers and matrix elements in hadronic collisions EPJC 53 (2007) 473 0706.2569
32 R. Frederix, E. Re, and P. Torrielli Single-top $ t $-channel hadroproduction in the four-flavour scheme with POWHEG and aMC@NLO JHEP 09 (2012) 130 1207.5391
33 S. Kallweit et al. NLO electroweak automation and precise predictions for W+multijet production at the LHC 1412.5157
34 S. Kallweit et al. NLO QCD+EW predictions for V+jets including off-shell vector-boson decays and multijet merging JHEP 2016 (2016) 1 1511.08692
35 S. Kallweit et al. NLO QCD+EW automation and precise predictions for V+multijet production Technical Report MCNET-14-26, 2015 1505.05704
36 J. M. Lindert et al. Precise predictions for v+jets dark matter backgrounds EPJC 77 (2017) 1705.04664
37 T. Sjöstrand et al. An introduction to PYTHIA 8.2 Comput. Phys. Commun. 191 (2015) 159 1410.3012
38 J. M. Campbell and R. K. Ellis MCFM for the Tevatron and the LHC Nucl. Phys. Proc. Suppl. 205-206 (2010) 10 1007.3492
39 P. Nason A new method for combining NLO QCD with shower Monte Carlo algorithms JHEP 11 (2004) 040 hep-ph/0409146
40 S. Frixione, P. Nason, and C. Oleari Matching NLO QCD computations with parton shower simulations: the POWHEG method JHEP 11 (2007) 070 0709.2092
41 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
42 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
43 E. Re Single-top $ \mathrm{W}\mathrm{t} $-channel production matched with parton showers using the POWHEG method EPJC 71 (2011) 1547 1009.2450
44 P. F. Monni et al. MiNNLO$ _{\text {PS}} $: a new method to match NNLO QCD to parton showers JHEP 05 (2020) 143 1908.06987
45 P. F. Monni, E. Re, and M. Wiesemann MiNNLO$ _{\text {PS}} $: optimizing 2 $ \rightarrow $ 1 hadronic processes EPJC 80 (2020) 1075 2006.04133
46 T. Neumann NLO Higgs+jet production at large transverse momenta including top quark mass effects Journal of Physics Communications 2 (2018) 095017 1802.02981
47 P. Nason and C. Oleari NLO Higgs boson production via vector-boson fusion matched with shower in POWHEG JHEP 02 (2010) 037 0911.5299
48 G. Luisoni, P. Nason, C. Oleari, and F. Tramontano HW$^{\pm} $/HZ+0 and 1 jet at NLO with the POWHEG box interfaced to GoSam and their merging within MINLO JHEP 10 (2013) 083 1306.2542
49 H. B. Hartanto, B. Jager, L. Reina, and D. Wackeroth Higgs boson production in association with top quarks in the POWHEG BOX PRD 91 (2015) 094003 1501.04498
50 M. Cacciari et al. Fully differential vector-boson-fusion Higgs production at next-to-next-to-leading order PRL 115 (2015) 082002 1506.02660
51 F. A. Dreyer and A. Karlberg Vector-boson fusion Higgs production at three loops in QCD PRL 117 (2016) 072001 1606.00840
52 CMS Collaboration Extraction and validation of a new set of CMS pythia8 tunes from underlying-event measurements EPJC 80 (2020) CMS-GEN-17-001
1903.12179
53 NNPDF Collaboration Parton distributions from high-precision collider data EPJC 77 (2017) 1706.00428
54 A. M. Sirunyan et al. Particle-flow reconstruction and global event description with the CMS detector JINST 12 (2017) P10003 1706.04965
55 M. Cacciari, G. P. Salam, and G. Soyez The anti-$ k_{\mathrm{T}} $ jet clustering algorithm JHEP 2008 (2008) 063 0802.1189
56 M. Cacciari, G. P. Salam, and G. Soyez FastJet user manual EPJC 72 (2012) 1111.6097
57 CMS Collaboration Jet algorithms performance in 13 TeV data CMS Physics Analysis Summary, CERN, Geneva, 2017
CMS-PAS-JME-16-003
CMS-PAS-JME-16-003
58 D. Bertolini, P. Harris, M. Low, and N. Tran Pileup per particle identification JHEP 2014 (2014) 1407.6013
59 D. Krohn, J. Thaler, and L.-T. Wang Jet trimming JHEP 2010 (2010) 0912.1342
60 A. J. Larkoski, S. Marzani, G. Soyez, and J. Thaler Soft drop JHEP 2014 (2014) 1402.2657
61 J. Lin Divergence measures based on the Shannon entropy IEEE Transactions on Information Theory 37 (1991) 145
62 I. Moult, L. Necib, and J. Thaler New angles on energy correlation functions JHEP 2016 (2016) 1609.07483
63 J. Dolen et al. Thinking outside the ROCs: Designing decorrelated taggers (DDT) for jet substructure JHEP 2016 (2016) 1603.00027
64 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
65 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
66 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
67 A. M. Sirunyan et al. 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 1809.02816
68 CMS Collaboration Performance of the DeepTau algorithm for the discrimination of taus against jets, electron, and muons CMS Detector Performance Summary CMS-DP-2019-033, 2019
CDS
69 R. A. Fisher On the interpretation of $ \chi^{2} $ from contingency tables, and the calculation of P J. R. Stat. Soc. 85 (1922) 87
70 CMS Collaboration Determination of jet energy calibration and transverse momentum resolution in CMS JINST 6 (2011) P11002 CMS-JME-10-011
1107.4277
71 S. Mrenna and P. Skands Automated parton-shower variations in PYTHIA 8 PRD 94 (2016) 1605.08352
72 J. Butterworth et al. PDF4LHC recommendations for LHC run II JPG 43 (2016) 023001 1510.03865
73 ATLAS, C. Collaborations, and L. H. C. Group Procedure for the LHC Higgs boson search combination in Summer 2011 Technical Report CMS-NOTE-2011-005, ATL-PHYS-PUB-2011-11, 2011
74 CMS Collaboration Precise determination of the mass of the Higgs boson and tests of compatibility of its couplings with the standard model predictions using proton collisions at 7 and 8 TeV EPJC 75 (2015) 1412.8662
Compact Muon Solenoid
LHC, CERN