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| CMS-B2G-23-004 ; CERN-EP-2024-250 | ||
| Search for high-mass resonances in a final state comprising a gluon and two hadronically decaying W bosons in proton-proton collisions at $ \sqrt{s} = $ 13 TeV | ||
| CMS Collaboration | ||
| 22 October 2024 | ||
| Submitted to J. High Energy Phys. | ||
| Abstract: A search for high-mass resonances decaying into a gluon, $ \mathrm{g} $, and two W bosons is presented. A Kaluza-Klein gluon, $ \mathrm{g}_\text{KK} $, decaying in cascade via a scalar radion R, $ \mathrm{g}_\text{KK}\to\mathrm{g}\mathrm{R}\to\mathrm{g}\mathrm{W}\mathrm{W} $, is considered. The final state studied consists of three large-radius jets, two of which contain the products of hadronically decaying W bosons, and the third one the hadronization products of the gluon. The analysis is performed using proton-proton collision data at $ \sqrt{s}= $ 13 TeV collected by the CMS experiment at the CERN LHC during 2016-2018, corresponding to an integrated luminosity of 138 fb$ ^{-1} $. The masses of the $ \mathrm{g}_\text{KK} $ and R candidates are reconstructed as trijet and dijet masses, respectively. These are used for event categorization and signal extraction. No excess of data events above the standard model background expectation is observed. Upper limits are set on the product of the $ \mathrm{g}_\text{KK} $ production cross section and its branching fraction via a radion R to gWW. This is the first analysis examining the resonant WW+jet signature and setting limits on the two resonance masses in an extended warped extra-dimensional model. | ||
| Links: e-print arXiv:2410.17303 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; CADI line (restricted) ; | ||
| Figures | |
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Figure 1:
A schematic diagram of the decay of a $ \mathrm{g}_\text{KK} $ boson via a radion R to the final state considered in this analysis. |
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Figure 2:
Distributions after event preselection. Upper left: the two-dimensional ($ m_{\mathrm{ja}} $, $ m_{\mathrm{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_\text{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 for shape visualization. White dashed lines indicate boundaries between SR, VR (defined in Section 6.1), and CR areas. The one-dimensional histograms show the $ m_{\mathrm{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 the labeled factors times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m^*_{\mathrm{jj}} $, $ m^*_{\mathrm{jjj}} $) distribution in data. White dashed lines indicate the SR splitting. |
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Figure 2-a:
Distributions after event preselection. Upper left: the two-dimensional ($ m_{\mathrm{ja}} $, $ m_{\mathrm{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_\text{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 for shape visualization. White dashed lines indicate boundaries between SR, VR (defined in Section 6.1), and CR areas. The one-dimensional histograms show the $ m_{\mathrm{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 the labeled factors times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m^*_{\mathrm{jj}} $, $ m^*_{\mathrm{jjj}} $) distribution in data. White dashed lines indicate the SR splitting. |
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Figure 2-b:
Distributions after event preselection. Upper left: the two-dimensional ($ m_{\mathrm{ja}} $, $ m_{\mathrm{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_\text{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 for shape visualization. White dashed lines indicate boundaries between SR, VR (defined in Section 6.1), and CR areas. The one-dimensional histograms show the $ m_{\mathrm{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 the labeled factors times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m^*_{\mathrm{jj}} $, $ m^*_{\mathrm{jjj}} $) distribution in data. White dashed lines indicate the SR splitting. |
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Figure 2-c:
Distributions after event preselection. Upper left: the two-dimensional ($ m_{\mathrm{ja}} $, $ m_{\mathrm{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_\text{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 for shape visualization. White dashed lines indicate boundaries between SR, VR (defined in Section 6.1), and CR areas. The one-dimensional histograms show the $ m_{\mathrm{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 the labeled factors times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m^*_{\mathrm{jj}} $, $ m^*_{\mathrm{jjj}} $) distribution in data. White dashed lines indicate the SR splitting. |
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Figure 2-d:
Distributions after event preselection. Upper left: the two-dimensional ($ m_{\mathrm{ja}} $, $ m_{\mathrm{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_\text{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 for shape visualization. White dashed lines indicate boundaries between SR, VR (defined in Section 6.1), and CR areas. The one-dimensional histograms show the $ m_{\mathrm{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 the labeled factors times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m^*_{\mathrm{jj}} $, $ m^*_{\mathrm{jjj}} $) distribution in data. White dashed lines indicate the SR splitting. |
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Figure 2-e:
Distributions after event preselection. Upper left: the two-dimensional ($ m_{\mathrm{ja}} $, $ m_{\mathrm{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_\text{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 for shape visualization. White dashed lines indicate boundaries between SR, VR (defined in Section 6.1), and CR areas. The one-dimensional histograms show the $ m_{\mathrm{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 the labeled factors times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m^*_{\mathrm{jj}} $, $ m^*_{\mathrm{jjj}} $) distribution in data. White dashed lines indicate the SR splitting. |
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Figure 2-f:
Distributions after event preselection. Upper left: the two-dimensional ($ m_{\mathrm{ja}} $, $ m_{\mathrm{jb}} $) distribution for a posited signal ($ {m}_{\mathrm{R}}= $ 0.75 TeV, $ {m}_{\mathrm{g}_\text{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 for shape visualization. White dashed lines indicate boundaries between SR, VR (defined in Section 6.1), and CR areas. The one-dimensional histograms show the $ m_{\mathrm{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 the labeled factors times the theoretical cross sections for visibility. Lower right: the two-dimensional ($ m^*_{\mathrm{jj}} $, $ m^*_{\mathrm{jjj}} $) distribution in data. White dashed lines indicate the SR splitting. |
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Figure 3:
The $ m^*_{\mathrm{jjj}} $ postfit spectra in the five SRxa. Upper to lower, and left to right: SR1a, SR2a, SR3a, SR4a, and SR5a. The lower panels show the pull distributions, as defined in the text, together with expected signal event yields and the systematic uncertainty normalized to $ \sigma_{\text{stat}} $. |
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Figure 3-a:
The $ m^*_{\mathrm{jjj}} $ postfit spectra in the five SRxa. Upper to lower, and left to right: SR1a, SR2a, SR3a, SR4a, and SR5a. The lower panels show the pull distributions, as defined in the text, together with expected signal event yields and the systematic uncertainty normalized to $ \sigma_{\text{stat}} $. |
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Figure 3-b:
The $ m^*_{\mathrm{jjj}} $ postfit spectra in the five SRxa. Upper to lower, and left to right: SR1a, SR2a, SR3a, SR4a, and SR5a. The lower panels show the pull distributions, as defined in the text, together with expected signal event yields and the systematic uncertainty normalized to $ \sigma_{\text{stat}} $. |
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Figure 3-c:
The $ m^*_{\mathrm{jjj}} $ postfit spectra in the five SRxa. Upper to lower, and left to right: SR1a, SR2a, SR3a, SR4a, and SR5a. The lower panels show the pull distributions, as defined in the text, together with expected signal event yields and the systematic uncertainty normalized to $ \sigma_{\text{stat}} $. |
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Figure 3-d:
The $ m^*_{\mathrm{jjj}} $ postfit spectra in the five SRxa. Upper to lower, and left to right: SR1a, SR2a, SR3a, SR4a, and SR5a. The lower panels show the pull distributions, as defined in the text, together with expected signal event yields and the systematic uncertainty normalized to $ \sigma_{\text{stat}} $. |
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Figure 3-e:
The $ m^*_{\mathrm{jjj}} $ postfit spectra in the five SRxa. Upper to lower, and left to right: SR1a, SR2a, SR3a, SR4a, and SR5a. The lower panels show the pull distributions, as defined in the text, together with expected signal event yields and the systematic uncertainty normalized to $ \sigma_{\text{stat}} $. |
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Figure 4:
The $ m^*_{\mathrm{jjj}} $ postfit spectra in the five SRxb. Upper to lower, and left to right: SR1b, SR2b, SR3b, SR4b, and SR5b. The lower panels show the pull distributions, as defined in the text, together with expected signal event yields and the systematic uncertainty normalized to $ \sigma_{\text{stat}} $. |
png pdf |
Figure 4-a:
The $ m^*_{\mathrm{jjj}} $ postfit spectra in the five SRxb. Upper to lower, and left to right: SR1b, SR2b, SR3b, SR4b, and SR5b. The lower panels show the pull distributions, as defined in the text, together with expected signal event yields and the systematic uncertainty normalized to $ \sigma_{\text{stat}} $. |
png pdf |
Figure 4-b:
The $ m^*_{\mathrm{jjj}} $ postfit spectra in the five SRxb. Upper to lower, and left to right: SR1b, SR2b, SR3b, SR4b, and SR5b. The lower panels show the pull distributions, as defined in the text, together with expected signal event yields and the systematic uncertainty normalized to $ \sigma_{\text{stat}} $. |
png pdf |
Figure 4-c:
The $ m^*_{\mathrm{jjj}} $ postfit spectra in the five SRxb. Upper to lower, and left to right: SR1b, SR2b, SR3b, SR4b, and SR5b. The lower panels show the pull distributions, as defined in the text, together with expected signal event yields and the systematic uncertainty normalized to $ \sigma_{\text{stat}} $. |
png pdf |
Figure 4-d:
The $ m^*_{\mathrm{jjj}} $ postfit spectra in the five SRxb. Upper to lower, and left to right: SR1b, SR2b, SR3b, SR4b, and SR5b. The lower panels show the pull distributions, as defined in the text, together with expected signal event yields and the systematic uncertainty normalized to $ \sigma_{\text{stat}} $. |
png pdf |
Figure 4-e:
The $ m^*_{\mathrm{jjj}} $ postfit spectra in the five SRxb. Upper to lower, and left to right: SR1b, SR2b, SR3b, SR4b, and SR5b. The lower panels show the pull distributions, as defined in the text, together with expected signal event yields and the systematic uncertainty normalized to $ \sigma_{\text{stat}} $. |
png pdf |
Figure 5:
The 95% CL upper limits on the production cross section times branching fraction $ \sigma\mathcal{B} $, for the process $ \mathrm{p}\mathrm{p}\to\mathrm{g}_\text{KK}\to\mathrm{g}\mathrm{R}\to\mathrm{g}\mathrm{W}\mathrm{W} $. The black solid (red dashed) line contour indicates the observed (expected) exclusion region of the $ \mathrm{g}_\text{KK} $ and R masses. The red dotted lines show the 68% CL band of the expected limit contour. |
| Tables | |
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Table 1:
Definition of the different SRs based on the $ m^*_{\mathrm{jj}} $/$ m^*_{\mathrm{jjj}} $ ratio and $ s_{\mathrm{jb}} $. |
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Table 2:
The $ \text{PNet}_\mathrm{W} $ scale factors calculated for exclusive $ p_{\mathrm{T}} $ and $ \text{PNet}_\mathrm{W} $ tagger score ranges of W boson matched jets. |
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Table 3:
The sources of systematic uncertainties accounted for in the analysis. From left to right: indication of whether an uncertainty is evaluated for the background (B) or signal (S), whether the uncertainty affects shape or rate, magnitudes (where applicable, or standard deviations ($ \sigma $)), 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, via an intermediate resonance, to a gluon and a pair of W bosons in the all-hadronic final states has been presented. A benchmark model, in which a Kaluza-Klein gluon decays into a radion and a gluon, $ \mathrm{g}_\text{KK}\to\mathrm{g}\mathrm{R}\to\mathrm{g}\mathrm{W}\mathrm{W} $, has been considered. The search is performed using proton-proton collision data at a center-of-mass energy of 13 TeV, collected by the CMS experiment, corresponding to a total integrated luminosity of 138 fb$ ^{-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 R 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 resonant signal above the standard model background prediction is found in the data analyzed. Exclusion limits are set at 95% confidence level on the masses of the $ \mathrm{g}_\text{KK} $ and R bosons, up to 3.55 and 2.18 TeV, respectively, and 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. This result is the first analyzing the resonant WW+jet signature and complements constraints set on similar scenarios [25,26,27,28]. |
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Compact Muon Solenoid LHC, CERN |
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