CMS-PAS-B2G-23-004

CMS-PAS-B2G-23-004
Search for diresonant new physics in a final state comprising a gluon and two hadronically decaying W bosons in proton-proton collisions at $ \sqrt{s}= $ 13 TeV
CMS Collaboration
14 June 2024

Abstract: A search for Kaluza-Klein (KK) gluon resonances, $ \mathrm{g_{KK}} $, decaying in cascade into two W bosons and a gluon via a scalar radion R, $ \mathrm{g_{KK} \rightarrow gR \rightarrow gWW} $, is presented. The final state with three large-radius jets, two of which contain the products of hadronically decaying W bosons is considered. The search is performed with $ \sqrt{s}= $ 13 TeV proton-proton collision data collected by the CMS experiment at the CERN LHC during 2016-2018, corresponding to an integrated luminosity of 138 fb$ ^{-1} $. Both the $ \mathrm{g_{KK}} $ and the R resonances are reconstructed. The ratio of their masses is used for event categorization, and the trijet mass distribution is used to extract a potential signal. Upper limits are set on the product of the $ \mathrm{g_{KK}} $ production cross section and branching fraction to $ \mathrm{gWW} $. Additionally, lower limits are set on the two resonance masses for an extended warped extra-dimensional model in which the quantum chromodynamics sector propagates into the extended bulk. This search is the first of its kind.
Links: CDS record (PDF) ; CADI line (restricted) ;

Figures & Tables	Summary	References	CMS Publications

Figures
png pdf	Figure 1: A schematic diagram of the decay of a $ \mathrm{g}_{\mathrm{KK}} $ boson via a radion to the final state considered in this analysis.
png pdf	Figure 2: Distributions after event preselection. Upper left: the two-dimensional ($ m_{\text{ja}} $, $ m_{\text{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_{\mathrm{KK}}}= $ 1.5 TeV) compared to the background-dominated data. For signal, contours corresponding to 80, 60, 40, and 20% fractions of the total signal event yield are shown as red to yellow curves for shape visualization. White dashed lines indicate the SR and CR areas. The one-dimensional histograms show the $ m_{\text{85}} $ (upper right), $ m_{\mathrm{jj}} $ (middle left), $ m_{\mathrm{jjj}} $ (middle right), and $ m_{\mathrm{jj}}/m_{\mathrm{jjj}} $ (lower left) distributions using simulated signal and background events as indicated in the legends. The signal events are scaled by factors of 300 and 10,000 times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m_{\mathrm{jj}} $, $ m_{\mathrm{jjj}} $) distribution. White dashed lines indicate the SR splitting.
png pdf	Figure 2-a: Distributions after event preselection. Upper left: the two-dimensional ($ m_{\text{ja}} $, $ m_{\text{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_{\mathrm{KK}}}= $ 1.5 TeV) compared to the background-dominated data. For signal, contours corresponding to 80, 60, 40, and 20% fractions of the total signal event yield are shown as red to yellow curves for shape visualization. White dashed lines indicate the SR and CR areas. The one-dimensional histograms show the $ m_{\text{85}} $ (upper right), $ m_{\mathrm{jj}} $ (middle left), $ m_{\mathrm{jjj}} $ (middle right), and $ m_{\mathrm{jj}}/m_{\mathrm{jjj}} $ (lower left) distributions using simulated signal and background events as indicated in the legends. The signal events are scaled by factors of 300 and 10,000 times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m_{\mathrm{jj}} $, $ m_{\mathrm{jjj}} $) distribution. White dashed lines indicate the SR splitting.
png pdf	Figure 2-b: Distributions after event preselection. Upper left: the two-dimensional ($ m_{\text{ja}} $, $ m_{\text{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_{\mathrm{KK}}}= $ 1.5 TeV) compared to the background-dominated data. For signal, contours corresponding to 80, 60, 40, and 20% fractions of the total signal event yield are shown as red to yellow curves for shape visualization. White dashed lines indicate the SR and CR areas. The one-dimensional histograms show the $ m_{\text{85}} $ (upper right), $ m_{\mathrm{jj}} $ (middle left), $ m_{\mathrm{jjj}} $ (middle right), and $ m_{\mathrm{jj}}/m_{\mathrm{jjj}} $ (lower left) distributions using simulated signal and background events as indicated in the legends. The signal events are scaled by factors of 300 and 10,000 times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m_{\mathrm{jj}} $, $ m_{\mathrm{jjj}} $) distribution. White dashed lines indicate the SR splitting.
png pdf	Figure 2-c: Distributions after event preselection. Upper left: the two-dimensional ($ m_{\text{ja}} $, $ m_{\text{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_{\mathrm{KK}}}= $ 1.5 TeV) compared to the background-dominated data. For signal, contours corresponding to 80, 60, 40, and 20% fractions of the total signal event yield are shown as red to yellow curves for shape visualization. White dashed lines indicate the SR and CR areas. The one-dimensional histograms show the $ m_{\text{85}} $ (upper right), $ m_{\mathrm{jj}} $ (middle left), $ m_{\mathrm{jjj}} $ (middle right), and $ m_{\mathrm{jj}}/m_{\mathrm{jjj}} $ (lower left) distributions using simulated signal and background events as indicated in the legends. The signal events are scaled by factors of 300 and 10,000 times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m_{\mathrm{jj}} $, $ m_{\mathrm{jjj}} $) distribution. White dashed lines indicate the SR splitting.
png pdf	Figure 2-d: Distributions after event preselection. Upper left: the two-dimensional ($ m_{\text{ja}} $, $ m_{\text{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_{\mathrm{KK}}}= $ 1.5 TeV) compared to the background-dominated data. For signal, contours corresponding to 80, 60, 40, and 20% fractions of the total signal event yield are shown as red to yellow curves for shape visualization. White dashed lines indicate the SR and CR areas. The one-dimensional histograms show the $ m_{\text{85}} $ (upper right), $ m_{\mathrm{jj}} $ (middle left), $ m_{\mathrm{jjj}} $ (middle right), and $ m_{\mathrm{jj}}/m_{\mathrm{jjj}} $ (lower left) distributions using simulated signal and background events as indicated in the legends. The signal events are scaled by factors of 300 and 10,000 times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m_{\mathrm{jj}} $, $ m_{\mathrm{jjj}} $) distribution. White dashed lines indicate the SR splitting.
png pdf	Figure 2-e: Distributions after event preselection. Upper left: the two-dimensional ($ m_{\text{ja}} $, $ m_{\text{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_{\mathrm{KK}}}= $ 1.5 TeV) compared to the background-dominated data. For signal, contours corresponding to 80, 60, 40, and 20% fractions of the total signal event yield are shown as red to yellow curves for shape visualization. White dashed lines indicate the SR and CR areas. The one-dimensional histograms show the $ m_{\text{85}} $ (upper right), $ m_{\mathrm{jj}} $ (middle left), $ m_{\mathrm{jjj}} $ (middle right), and $ m_{\mathrm{jj}}/m_{\mathrm{jjj}} $ (lower left) distributions using simulated signal and background events as indicated in the legends. The signal events are scaled by factors of 300 and 10,000 times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m_{\mathrm{jj}} $, $ m_{\mathrm{jjj}} $) distribution. White dashed lines indicate the SR splitting.
png pdf	Figure 2-f: Distributions after event preselection. Upper left: the two-dimensional ($ m_{\text{ja}} $, $ m_{\text{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_{\mathrm{KK}}}= $ 1.5 TeV) compared to the background-dominated data. For signal, contours corresponding to 80, 60, 40, and 20% fractions of the total signal event yield are shown as red to yellow curves for shape visualization. White dashed lines indicate the SR and CR areas. The one-dimensional histograms show the $ m_{\text{85}} $ (upper right), $ m_{\mathrm{jj}} $ (middle left), $ m_{\mathrm{jjj}} $ (middle right), and $ m_{\mathrm{jj}}/m_{\mathrm{jjj}} $ (lower left) distributions using simulated signal and background events as indicated in the legends. The signal events are scaled by factors of 300 and 10,000 times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m_{\mathrm{jj}} $, $ m_{\mathrm{jjj}} $) distribution. White dashed lines indicate the SR splitting.
png pdf	Figure 3: The $ m_{\mathrm{jjj}*} $ postfit predicted spectra in the five SRa. Upper to lower, and left to right: SR1a, SR2a, SR3a, SR4a, SR5a.
png pdf	Figure 3-a: The $ m_{\mathrm{jjj}*} $ postfit predicted spectra in the five SRa. Upper to lower, and left to right: SR1a, SR2a, SR3a, SR4a, SR5a.
png pdf	Figure 3-b: The $ m_{\mathrm{jjj}*} $ postfit predicted spectra in the five SRa. Upper to lower, and left to right: SR1a, SR2a, SR3a, SR4a, SR5a.
png pdf	Figure 3-c: The $ m_{\mathrm{jjj}*} $ postfit predicted spectra in the five SRa. Upper to lower, and left to right: SR1a, SR2a, SR3a, SR4a, SR5a.
png pdf	Figure 3-d: The $ m_{\mathrm{jjj}*} $ postfit predicted spectra in the five SRa. Upper to lower, and left to right: SR1a, SR2a, SR3a, SR4a, SR5a.
png pdf	Figure 3-e: The $ m_{\mathrm{jjj}*} $ postfit predicted spectra in the five SRa. Upper to lower, and left to right: SR1a, SR2a, SR3a, SR4a, SR5a.
png pdf	Figure 4: The $ m_{\mathrm{jjj}*} $ postfit predicted spectra in the five SRb. Upper to lower, and left to right: SR1b, SR2b, SR3b, SR4b, SR5b.
png pdf	Figure 4-a: The $ m_{\mathrm{jjj}*} $ postfit predicted spectra in the five SRb. Upper to lower, and left to right: SR1b, SR2b, SR3b, SR4b, SR5b.
png pdf	Figure 4-b: The $ m_{\mathrm{jjj}*} $ postfit predicted spectra in the five SRb. Upper to lower, and left to right: SR1b, SR2b, SR3b, SR4b, SR5b.
png pdf	Figure 4-c: The $ m_{\mathrm{jjj}*} $ postfit predicted spectra in the five SRb. Upper to lower, and left to right: SR1b, SR2b, SR3b, SR4b, SR5b.
png pdf	Figure 4-d: The $ m_{\mathrm{jjj}*} $ postfit predicted spectra in the five SRb. Upper to lower, and left to right: SR1b, SR2b, SR3b, SR4b, SR5b.
png pdf	Figure 4-e: The $ m_{\mathrm{jjj}*} $ postfit predicted spectra in the five SRb. Upper to lower, and left to right: SR1b, SR2b, SR3b, SR4b, SR5b.
png pdf	Figure 5: The upper limits on the production cross section times branching fraction $ \sigma\mathcal{B} $, at 95% CL, for the process $ \mathrm{p}\mathrm{p}\rightarrow\mathrm{g}_{\mathrm{KK}}\to\mathrm{g}\mathrm{R}\to\mathrm{g}\mathrm{W}\mathrm{W} $. The black (red) line contour indicates observed (expected) exclusion region on $ \mathrm{g}_{\mathrm{KK}} $ and R masses. The red dashed lines show the 68% standard deviation band of the expected limit contour.

Tables
png pdf	Table 1: Definition of the different SRs based on the $ m_{\mathrm{jj}} $/$ m_{\mathrm{jjj}} $ ratio and $ s_{\text{jb}} $.
png pdf	Table 2: The PNet tagger SFs calculated for exclusive $ p_{\mathrm{T}} $ and PNet tagger score ranges of W boson matched jets.
png pdf	Table 3: The sources of systematic uncertainties accounted for in the analysis. From left to right: indication of whether an uncertainty is evaluated for background (B) or signal (S), whether the uncertainty affects shape or rate, magnitudes (where applicable), and the total number of nuisance parameters (NPs) used along with their correlations across SRs. The ``*'' indicates a value or a shape template different for each signal scenario.

Summary

A search for heavy resonances decaying in cascade via an intermediate resonance to a gluon and two W bosons, such as $ \mathrm{g}_{\mathrm{KK}} \to \mathrm{g}\mathrm{R} \to \mathrm{g}\mathrm{W}\mathrm{W} $, in the all-hadronic final state has been presented. The search is performed in proton-proton collision data at a center-of-mass energy of 13 TeV, corresponding to a total integrated luminosity of 138 fb$ ^{-1} $. The final states include three large-radius jets, at least two of which are required to be massive, containing the decay products of the hadronically decaying W bosons. The topology corresponds to events where each W boson from the radion decay is reconstructed as a single merged jet. In this analysis, a previously unexplored signature is probed using jet substructure techniques relying on deep learning. No such signal is found in the analyzed data. Exclusion limits are set at 95% CL on the product of the production cross section and the branching fraction to a gluon and two W bosons in an extended warped extra-dimensional model previously examined in [11,12,13,14] This result is the first analysing the WWjet final state and complements constraints in other signatures.

References
1	CMS Collaboration	Search for heavy resonances decaying to Z($ \nu\bar{\nu} $)V(q$ \bar{q} $') in proton-proton collisions at $ \sqrt{s} = $ 13 TeV	PRD 106 (2022) 012004	2109.08268
2	CMS Collaboration	Search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state in proton-proton collisions at $ \sqrt{s} = $ 13TeV	PLB 844 (2023) 137813	2210.00043
3	CMS Collaboration	Search for heavy resonances decaying to WW, WZ, or WH boson pairs in the lepton plus merged jet final state in proton-proton collisions at $ \sqrt{s} = $ 13 TeV	PRD 105 (2022) 032008	2109.06055
4	CMS Collaboration	Search for high mass dijet resonances with a new background prediction method in proton-proton collisions at $ \sqrt{s} = $ 13 TeV	JHEP 05 (2020) 033	CMS-EXO-19-012 1911.03947
5	K. Agashe, P. Du, S. Hong, and R. Sundrum	Flavor universal resonances and warped gravity	JHEP 01 (2017) 016	1608.00526
6	K. S. Agashe et al.	LHC signals from cascade decays of warped vector resonances	JHEP 05 (2017) 078	1612.00047
7	K. Agashe et al.	Dedicated strategies for triboson signals from cascade decays of vector resonances	PRD 99 (2019) 075016	1711.09920
8	K. Agashe et al.	Detecting a boosted diboson resonance	JHEP 11 (2018) 027	1809.07334
9	Y.-P. Kuang, H.-Y. Ren, and L.-H. Xia	Further investigation of the model-independent probe of heavy neutral Higgs bosons at LHC Run 2	Chin. Phys. C 40 (2016) 023101	1506.08007
10	Y.-P. Kuang, H.-Y. Ren, and L.-H. Xia	Model-independent probe of anomalous heavy neutral Higgs bosons at the LHC	PRD 90 (2014) 115002	1404.6367
11	CMS Collaboration	Search for resonances decaying to three W bosons in proton-proton collisions at $ \sqrt{s} = $ 13 TeV	PRL 129 (2022) 021802	2201.08476
12	CMS Collaboration	Search for resonances decaying to three $ W $ bosons in the hadronic final state in proton-proton collisions at $ \sqrt s = $ 13 TeV	PRD 106 (2022) 012002	2112.13090
13	CMS Collaboration	Search for high-mass resonances decaying to a jet and a Lorentz-boosted resonance in proton-proton collisions at $ \sqrt{s} = $ 13TeV	PLB 832 (2022) 137263	CMS-EXO-20-007 2201.02140
14	CMS Collaboration	Search for narrow trijet resonances in proton-proton collisions at $ \sqrt{s} = $ 13 TeV	Accepted by PRL	CMS-EXO-22-008 2310.14023
15	CMS Collaboration	Identification of heavy, energetic, hadronically decaying particles using machine-learning techniques	JINST 15 (2020) P06005	CMS-JME-18-002 2004.08262
16	H. Qu and L. Gouskos	ParticleNet: Jet Tagging via Particle Clouds	PRD 101 (2020) 056019	1902.08570
17	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
18	CMS Collaboration	The CMS trigger system	JINST 12 (2017) P01020	CMS-TRG-12-001 1609.02366
19	CMS Collaboration	The CMS experiment at the CERN LHC	JINST 3 (2008) S08004
20	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
21	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
22	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
23	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
24	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
25	P. Nason	A new method for combining NLO QCD with shower Monte Carlo algorithms	JHEP 11 (2004) 040	hep-ph/0409146
26	S. Frixione, P. Nason, and C. Oleari	Matching NLO QCD computations with parton shower simulations: the POWHEG method	JHEP 11 (2007) 070	0709.2092
27	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
28	S. Alioli, S.-O. Moch, and P. Uwer	Hadronic top-quark pair-production with one jet and parton showering	JHEP 01 (2012) 137	1110.5251
29	S. Alioli, P. Nason, C. Oleari, and E. Re	NLO single-top production matched with shower in POWHEG: $ s $- and $ t $-channel contributions	JHEP 09 (2009) 111	0907.4076
30	R. Frederix, E. Re, and P. Torrielli	Single-top $ t $-channel hadroproduction in the four-flavour scheme with POWHEG and aMC@NLO	JHEP 09 (2012) 130	1207.5391
31	NNPDF Collaboration	Parton distributions for the LHC run II	JHEP 04 (2015) 040	1410.8849
32	T. Sjöstrand et al.	An introduction to PYTHIA 8.2	Comput. Phys. Commun. 191 (2015) 159	1410.3012
33	CMS Collaboration	Extraction and validation of a new set of CMS PYTHIA8 tunes from underlying-event measurements	EPJC 80 (2020) 4	CMS-GEN-17-001 1903.12179
34	GEANT4 Collaboration	GEANT 4---a simulation toolkit	NIM A 506 (2003) 250
35	CMS Collaboration	Technical proposal for the Phase-II upgrade of the Compact Muon Solenoid	CMS Technical Proposal CERN-LHCC-2015-010, CMS-TDR-15-02, 2015 CDS
36	M. Cacciari, G. P. Salam, and G. Soyez	The anti-$ k_{\mathrm{T}} $ jet clustering algorithm	JHEP 04 (2008) 063	0802.1189
37	M. Cacciari, G. P. Salam, and G. Soyez	FastJet user manual	EPJC 72 (2012) 1896	1111.6097
38	CMS Collaboration	Particle-flow reconstruction and global event description with the CMS detector	JINST 12 (2017) P10003	CMS-PRF-14-001 1706.04965
39	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
40	CMS Collaboration	Pileup mitigation at CMS in 13 TeV data	JINST 15 (2020) P09018	CMS-JME-18-001 2003.00503
41	D. Bertolini, P. Harris, M. Low, and N. Tran	Pileup Per Particle Identification	JHEP 10 (2014) 059	1407.6013
42	CMS Collaboration	Jet algorithms performance in 13 TeV data	CMS Physics Analysis Summary, 2017 CMS-PAS-JME-16-003	CMS-PAS-JME-16-003
43	E. Bols et al.	Jet Flavour Classification Using DeepJet	JINST 15 (2020) P12012	2008.10519
44	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
45	M. Dasgupta, A. Fregoso, S. Marzani, and G. P. Salam	Towards an understanding of jet substructure	JHEP 09 (2013) 029	1307.0007
46	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
47	A. J. Larkoski, S. Marzani, G. Soyez, and J. Thaler	Soft drop	JHEP 05 (2014) 146	1402.2657
48	CMS Collaboration	Identification techniques for highly boosted W bosons that decay into hadrons	JHEP 12 (2014) 017	CMS-JME-13-006 1410.4227
49	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
50	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
51	D. Krohn, J. Thaler, and L.-T. Wang	Jet Trimming	JHEP 02 (2010) 084	0912.1342
52	CMS Collaboration	Measurement of the inelastic proton-proton cross section at $ \sqrt{s}= $ 13 TeV	JHEP 07 (2018) 161	CMS-FSQ-15-005 1802.02613
53	CMS Collaboration	The CMS statistical analysis and combination tool: Combine	Submitted to Comput. Softw. Big Sci, 2024	CMS-CAT-23-001 2404.06614