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CMS-EXO-22-008 ; CERN-EP-2023-220
Search for narrow trijet resonances in proton-proton collisions at $ \sqrt{s} = $ 13 TeV
Phys. Lett. B 855 (2024) 138815
Abstract: The first search for narrow resonances decaying to three well-separated hadronic jets is presented. The search uses proton-proton collision data corresponding to an integrated luminosity of 138 fb$ ^{-1} $ at $ \sqrt{s}= $ 13 TeV, collected at the CERN LHC. No significant deviations from the background predictions are observed between 1.75-9.00 TeV. The results provide the first mass limits on a right-handed boson $ \mathrm{Z}_{R} $ decaying to three gluons, an excited quark decaying via a vector boson to three quarks, as well as updated limits on a Kaluza-Klein gluon decaying via a radion to three gluons.
Figures Summary Additional Figures References CMS Publications
Figures

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Figure 1:
The observed $ m_{\mathrm{jjj}} $ distribution and the background-only fit to the data using the $ f_A $ fit function. Uncertainties in the fit that correspond to the 68% confidence level are depicted with the red band. The expected $ m_{\mathrm{jjj}} $ distributions for $ \mathrm{Z}_{R} $ signal masses of 2.0, 4.0, 6.0, and 8.0 TeV, with nominal width of $ {\sim} 3% $, are also shown. For illustration purposes, the normalizations correspond to $ \sigma\mathcal{B} $ values of 200, 50, 20, and 20 fb, respectively. Only 2016 data are shown for $ m_{\mathrm{jjj}} < $ 1.76 TeV because of the higher trigger thresholds in 2017 and 2018. In the bottom panel, the blue hatched bars show the difference between the observed data and the background prediction divided by the statistical uncertainty, along with expectations for the example $ \mathrm{Z}_{R} $ signal points.

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Figure 2:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to\mathrm{g}\mathrm{g}\mathrm{g})\mathcal{A} $ for the nominal (left) and narrow-width (right) scenarios. Only 2016 data are used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions assuming SM-like couplings are depicted with red curves.

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Figure 2-a:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to\mathrm{g}\mathrm{g}\mathrm{g})\mathcal{A} $ for the nominal scenario. Only 2016 data are used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions assuming SM-like couplings are depicted with red curves.

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Figure 2-b:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to\mathrm{g}\mathrm{g}\mathrm{g})\mathcal{A} $ for the narrow-width scenario. Only 2016 data are used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions assuming SM-like couplings are depicted with red curves.

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Figure 3:
Observed limits at 95% CL as a function of $ m_{\mathrm{X}} $ and $ \rho_{\mathrm{m}} $ on $ \sigma\mathcal{B}(\mathrm{X}\to{\mathrm{Y}}(\mathrm{g}\mathrm{g})\mathrm{g})\mathcal{A} $ (left) and $ \sigma\mathcal{B}(\mathrm{X}\to{\mathrm{Y}}(\mathrm{q}\mathrm{q})\mathrm{q})\mathcal{A} $ (right). Only 2016 data are used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. The legend shows the model parameters for the chosen benchmark [23,24], and their corresponding mass exclusion ranges are depicted with areas inside the black hatched contours.

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Figure 3-a:
Observed limits at 95% CL as a function of $ m_{\mathrm{X}} $ and $ \rho_{\mathrm{m}} $ on $ \sigma\mathcal{B}(\mathrm{X}\to{\mathrm{Y}}(\mathrm{g}\mathrm{g})\mathrm{g})\mathcal{A} $. Only 2016 data are used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. The legend shows the model parameters for the chosen benchmark [23], and their corresponding mass exclusion ranges are depicted with areas inside the black hatched contours.

png pdf
Figure 3-b:
Observed limits at 95% CL as a function of $ m_{\mathrm{X}} $ and $ \rho_{\mathrm{m}} $ on $ \sigma\mathcal{B}(\mathrm{X}\to{\mathrm{Y}}(\mathrm{q}\mathrm{q})\mathrm{q})\mathcal{A} $. Only 2016 data are used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. The legend shows the model parameters for the chosen benchmark [24], and their corresponding mass exclusion ranges are depicted with areas inside the black hatched contours.
Summary
In summary, the first generic search for new particles decaying to three hadronic jets has been presented. The search uses proton-proton collision data at $ \sqrt{s}= $ 13 TeV recorded by the CMS experiment in 2016-2018, corresponding to an integrated luminosity of 138 fb$^{-1}$. The three-jet invariant mass spectrum is scanned for narrow peaks corresponding to new particles. No significant excesses above the standard model background expectations are observed. Limits are set on the product of the production cross section, branching fraction, and acceptance to three resolved jets. The results are interpreted in the context of a new right-handed boson $ \mathrm{Z}_{R} $ decaying to three gluons, a Kaluza-Klein gluon $\mathrm{G}_{\mathrm{KK}}$ decaying via an intermediate radion to three gluons ($ \mathrm{g}\mathrm{g}\mathrm{g} $), and an excited quark decaying via a vector boson to three quarks ($ \mathrm{q}\mathrm{q}\mathrm{q} $). This is the first search for the three-body decay of high-mass resonances ($ \mathrm{X} $) into three resolved jets at the LHC, and also the first search for $ \mathrm{X} $ that decays into three resolved jets through an intermediate resonance ($\mathrm{Y}$) with a mass ratio $ m_{{\mathrm{Y}}}/m_{\mathrm{X}} $ between 0.3-0.8 for the $ \mathrm{g}\mathrm{g}\mathrm{g} $ decay mode and 0.2-0.8 for the $ \mathrm{q}\mathrm{q}\mathrm{q} $ decay mode, significantly extending the model parameter space explored by a previous search [20].
Additional Figures

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Additional Figure 1:
Efficiencies of the selection requirements on the benchmark signal processes: $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ with nominal width $ \Gamma_{\mathrm{Z}_{R}}/ m_{\mathrm{Z}_{R}}\sim3% $ (top left), $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ with narrow width $ \Gamma_{\mathrm{Z}_{R}}/ m_{\mathrm{Z}_{R}}\sim0.01% $ (top right), $ g_{\mathrm{KK}} \to\varphi(\mathrm{g}\mathrm{g})\mathrm{g} $ (bottom left), and $ \mathrm{q}^{*}\to \text{V}(\mathrm{q}\mathrm{q})\mathrm{q} $ (bottom right). $ \varphi $ is the radion and V is a beyond-the-SM vector boson. The efficiencies for 2016, 2017, and 2018 data-taking conditions are shown separately. The bottom two figures also show efficiencies for different $ \rho_{m} $ scenarios for cascade decays with intermediate resonances.

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Additional Figure 1-a:
Efficiencies of the selection requirements on the benchmark signal processes: $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ with nominal width $ \Gamma_{\mathrm{Z}_{R}}/ m_{\mathrm{Z}_{R}}\sim3% $ (top left), $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ with narrow width $ \Gamma_{\mathrm{Z}_{R}}/ m_{\mathrm{Z}_{R}}\sim0.01% $ (top right), $ g_{\mathrm{KK}} \to\varphi(\mathrm{g}\mathrm{g})\mathrm{g} $ (bottom left), and $ \mathrm{q}^{*}\to \text{V}(\mathrm{q}\mathrm{q})\mathrm{q} $ (bottom right). $ \varphi $ is the radion and V is a beyond-the-SM vector boson. The efficiencies for 2016, 2017, and 2018 data-taking conditions are shown separately. The bottom two figures also show efficiencies for different $ \rho_{m} $ scenarios for cascade decays with intermediate resonances.

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Additional Figure 1-b:
Efficiencies of the selection requirements on the benchmark signal processes: $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ with nominal width $ \Gamma_{\mathrm{Z}_{R}}/ m_{\mathrm{Z}_{R}}\sim3% $ (top left), $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ with narrow width $ \Gamma_{\mathrm{Z}_{R}}/ m_{\mathrm{Z}_{R}}\sim0.01% $ (top right), $ g_{\mathrm{KK}} \to\varphi(\mathrm{g}\mathrm{g})\mathrm{g} $ (bottom left), and $ \mathrm{q}^{*}\to \text{V}(\mathrm{q}\mathrm{q})\mathrm{q} $ (bottom right). $ \varphi $ is the radion and V is a beyond-the-SM vector boson. The efficiencies for 2016, 2017, and 2018 data-taking conditions are shown separately. The bottom two figures also show efficiencies for different $ \rho_{m} $ scenarios for cascade decays with intermediate resonances.

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Additional Figure 1-c:
Efficiencies of the selection requirements on the benchmark signal processes: $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ with nominal width $ \Gamma_{\mathrm{Z}_{R}}/ m_{\mathrm{Z}_{R}}\sim3% $ (top left), $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ with narrow width $ \Gamma_{\mathrm{Z}_{R}}/ m_{\mathrm{Z}_{R}}\sim0.01% $ (top right), $ g_{\mathrm{KK}} \to\varphi(\mathrm{g}\mathrm{g})\mathrm{g} $ (bottom left), and $ \mathrm{q}^{*}\to \text{V}(\mathrm{q}\mathrm{q})\mathrm{q} $ (bottom right). $ \varphi $ is the radion and V is a beyond-the-SM vector boson. The efficiencies for 2016, 2017, and 2018 data-taking conditions are shown separately. The bottom two figures also show efficiencies for different $ \rho_{m} $ scenarios for cascade decays with intermediate resonances.

png pdf
Additional Figure 1-d:
Efficiencies of the selection requirements on the benchmark signal processes: $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ with nominal width $ \Gamma_{\mathrm{Z}_{R}}/ m_{\mathrm{Z}_{R}}\sim3% $ (top left), $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ with narrow width $ \Gamma_{\mathrm{Z}_{R}}/ m_{\mathrm{Z}_{R}}\sim0.01% $ (top right), $ g_{\mathrm{KK}} \to\varphi(\mathrm{g}\mathrm{g})\mathrm{g} $ (bottom left), and $ \mathrm{q}^{*}\to \text{V}(\mathrm{q}\mathrm{q})\mathrm{q} $ (bottom right). $ \varphi $ is the radion and V is a beyond-the-SM vector boson. The efficiencies for 2016, 2017, and 2018 data-taking conditions are shown separately. The bottom two figures also show efficiencies for different $ \rho_{m} $ scenarios for cascade decays with intermediate resonances.

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Additional Figure 2:
Acceptance of the signal selection requirement $ m_{\mathrm{X}}^{GEN}/m_{\mathrm{X}}^{input} > $ 85% on the benchmark signal process $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ (top), $ g_{\mathrm{KK}} \to\varphi(\mathrm{g}\mathrm{g})\mathrm{g} $ (bottom left), and $ \mathrm{q}^{*}\to \text{V}(\mathrm{q}\mathrm{q})\mathrm{q} $ (bottom right). $ m_{\mathrm{X}}^{\text{GEN}} $ is the mass of the new resonances generated by the MC simulation. $ m_{\mathrm{X}}^{\text{input}} $ is the resonance mass point under consideration. The acceptance is defined as $ \mathcal{A} = $ N (events with $ m_{\mathrm{X}}^{\text{GEN}}/m_{\mathrm{X}}^{\text{input}} > $ 85%) / $ N $(events generated in the full phase space defined by the CMS default generator settings).

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Additional Figure 2-a:
Acceptance of the signal selection requirement $ m_{\mathrm{X}}^{GEN}/m_{\mathrm{X}}^{input} > $ 85% on the benchmark signal process $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ (top), $ g_{\mathrm{KK}} \to\varphi(\mathrm{g}\mathrm{g})\mathrm{g} $ (bottom left), and $ \mathrm{q}^{*}\to \text{V}(\mathrm{q}\mathrm{q})\mathrm{q} $ (bottom right). $ m_{\mathrm{X}}^{\text{GEN}} $ is the mass of the new resonances generated by the MC simulation. $ m_{\mathrm{X}}^{\text{input}} $ is the resonance mass point under consideration. The acceptance is defined as $ \mathcal{A} = $ N (events with $ m_{\mathrm{X}}^{\text{GEN}}/m_{\mathrm{X}}^{\text{input}} > $ 85%) / $ N $(events generated in the full phase space defined by the CMS default generator settings).

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Additional Figure 2-b:
Acceptance of the signal selection requirement $ m_{\mathrm{X}}^{GEN}/m_{\mathrm{X}}^{input} > $ 85% on the benchmark signal process $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ (top), $ g_{\mathrm{KK}} \to\varphi(\mathrm{g}\mathrm{g})\mathrm{g} $ (bottom left), and $ \mathrm{q}^{*}\to \text{V}(\mathrm{q}\mathrm{q})\mathrm{q} $ (bottom right). $ m_{\mathrm{X}}^{\text{GEN}} $ is the mass of the new resonances generated by the MC simulation. $ m_{\mathrm{X}}^{\text{input}} $ is the resonance mass point under consideration. The acceptance is defined as $ \mathcal{A} = $ N (events with $ m_{\mathrm{X}}^{\text{GEN}}/m_{\mathrm{X}}^{\text{input}} > $ 85%) / $ N $(events generated in the full phase space defined by the CMS default generator settings).

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Additional Figure 2-c:
Acceptance of the signal selection requirement $ m_{\mathrm{X}}^{GEN}/m_{\mathrm{X}}^{input} > $ 85% on the benchmark signal process $ \mathrm{Z}_{R}\to\mathrm{g}\mathrm{g}\mathrm{g} $ (top), $ g_{\mathrm{KK}} \to\varphi(\mathrm{g}\mathrm{g})\mathrm{g} $ (bottom left), and $ \mathrm{q}^{*}\to \text{V}(\mathrm{q}\mathrm{q})\mathrm{q} $ (bottom right). $ m_{\mathrm{X}}^{\text{GEN}} $ is the mass of the new resonances generated by the MC simulation. $ m_{\mathrm{X}}^{\text{input}} $ is the resonance mass point under consideration. The acceptance is defined as $ \mathcal{A} = $ N (events with $ m_{\mathrm{X}}^{\text{GEN}}/m_{\mathrm{X}}^{\text{input}} > $ 85%) / $ N $(events generated in the full phase space defined by the CMS default generator settings).

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Additional Figure 3:
The observed local significance for a $ \mathrm{g}\mathrm{g}\mathrm{g} $ resonance versus X mass, shown for resonances with nominal width (blue) and narrow width (red). The most significant excesses correspond to 2.1 (2.2) standard deviations.

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Additional Figure 4:
The observed local significance versus $ m_{\mathrm{X}} $ and $ \rho_{m} $ for resonances decaying via a cascade. The largest deviations are observed at $ \rho_{m} = 0.3, m_{\mathrm{X}} = $ 4.1 TeV for $ \mathrm{X}\to \mathrm{Y} (\mathrm{g}\mathrm{g})\mathrm{g} $ and $ \rho_{m} =$ 0.7, $ m_{\mathrm{X}} = $ 3.9 TeV for $ \mathrm{X}\to \mathrm{Y} (\mathrm{q}\mathrm{q})\mathrm{q} $. The corresponding local (global) significance values are 2.2 (0.4) and 2.1 (0.3) standard deviations, respectively.

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Additional Figure 4-a:
The observed local significance versus $ m_{\mathrm{X}} $ and $ \rho_{m} $ for resonances decaying via a cascade. The largest deviations are observed at $ \rho_{m} = 0.3, m_{\mathrm{X}} = $ 4.1 TeV for $ \mathrm{X}\to \mathrm{Y} (\mathrm{g}\mathrm{g})\mathrm{g} $ and $ \rho_{m} =$ 0.7, $ m_{\mathrm{X}} = $ 3.9 TeV for $ \mathrm{X}\to \mathrm{Y} (\mathrm{q}\mathrm{q})\mathrm{q} $. The corresponding local (global) significance values are 2.2 (0.4) and 2.1 (0.3) standard deviations, respectively.

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Additional Figure 4-b:
The observed local significance versus $ m_{\mathrm{X}} $ and $ \rho_{m} $ for resonances decaying via a cascade. The largest deviations are observed at $ \rho_{m} = 0.3, m_{\mathrm{X}} = $ 4.1 TeV for $ \mathrm{X}\to \mathrm{Y} (\mathrm{g}\mathrm{g})\mathrm{g} $ and $ \rho_{m} =$ 0.7, $ m_{\mathrm{X}} = $ 3.9 TeV for $ \mathrm{X}\to \mathrm{Y} (\mathrm{q}\mathrm{q})\mathrm{q} $. The corresponding local (global) significance values are 2.2 (0.4) and 2.1 (0.3) standard deviations, respectively.

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Additional Figure 5:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{g}\mathrm{g})\mathrm{g})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ g_{\mathrm{KK}} $ model.

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Additional Figure 5-a:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{g}\mathrm{g})\mathrm{g})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ g_{\mathrm{KK}} $ model.

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Additional Figure 5-b:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{g}\mathrm{g})\mathrm{g})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ g_{\mathrm{KK}} $ model.

png pdf
Additional Figure 5-c:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{g}\mathrm{g})\mathrm{g})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ g_{\mathrm{KK}} $ model.

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Additional Figure 5-d:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{g}\mathrm{g})\mathrm{g})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ g_{\mathrm{KK}} $ model.

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Additional Figure 5-e:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{g}\mathrm{g})\mathrm{g})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ g_{\mathrm{KK}} $ model.

png pdf
Additional Figure 5-f:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{g}\mathrm{g})\mathrm{g})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ g_{\mathrm{KK}} $ model.

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Additional Figure 5-g:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{g}\mathrm{g})\mathrm{g})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ g_{\mathrm{KK}} $ model.

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Additional Figure 6:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{q}\mathrm{q})\mathrm{q})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ \mathrm{q}^{*} $ model.

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Additional Figure 6-a:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{q}\mathrm{q})\mathrm{q})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ \mathrm{q}^{*} $ model.

png pdf
Additional Figure 6-b:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{q}\mathrm{q})\mathrm{q})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ \mathrm{q}^{*} $ model.

png pdf
Additional Figure 6-c:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{q}\mathrm{q})\mathrm{q})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ \mathrm{q}^{*} $ model.

png pdf
Additional Figure 6-d:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{q}\mathrm{q})\mathrm{q})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ \mathrm{q}^{*} $ model.

png pdf
Additional Figure 6-e:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{q}\mathrm{q})\mathrm{q})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ \mathrm{q}^{*} $ model.

png pdf
Additional Figure 6-f:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{q}\mathrm{q})\mathrm{q})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ \mathrm{q}^{*} $ model.

png pdf
Additional Figure 6-g:
Limits at 95% CL on $ \sigma\mathcal{B}(\mathrm{X}\to \mathrm{Y} (\mathrm{q}\mathrm{q})\mathrm{q})\mathcal{A} $ for resonances X in different $ \rho_{m} $ scenarios. Only 2016 data is used to derive limits below 2.0 TeV because of the higher trigger thresholds in 2017 and 2018. Theoretical predictions are also shown for the benchmark $ \mathrm{q}^{*} $ model.

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Additional Figure 7:
Three-dimensional display of the event with the highest $ m_{\mathrm{jjj}} $ of 7.20 TeV. Energy deposited in the electromagnetic (green) and hadronic (blue) calorimeters and the reconstructed tracks of charged particles (yellow) are shown. Reconstructed three most energetic jets are represented by the yellow cones.
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CMS-PAS-JME-16-003
CMS-PAS-JME-16-003
40 CMS Collaboration Pileup mitigation at CMS in 13 TeV data JINST 15 (2020) P09018 CMS-JME-18-001
2003.00503
41 CMS Collaboration Search for resonances in the dijet mass spectrum from 7 TeV pp collisions at CMS PLB 704 (2011) 123 CMS-EXO-11-015
1107.4771
42 T. Sjöstrand et al. An introduction to PYTHIA 8.2 Comput. Phys. Commun. 191 (2015) 159 1410.3012
43 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
44 NNPDF Collaboration Parton distributions from high-precision collider data EPJC 77 (2017) 663 1706.00428
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 GEANT4 Collaboration GEANT 4---a simulation toolkit NIM A 506 (2003) 250
47 R. A. Fisher On the interpretation of $ \chi^{2} $ from contingency tables, and the calculation of P J. R. Stat. Soc. 85 (1922) 87
48 ATLAS and CMS Collaborations, and LHC Higgs Combination Group Procedure for the LHC Higgs boson search combination in Summer 2011 Technical Report CMS-NOTE-2011-005, ATL-PHYS-PUB-2011-11, 2011
49 P. D. Dauncey, M. Kenzie, N. Wardle, and G. J. Davies Handling uncertainties in background shapes: the discrete profiling method JINST 10 (2015) P04015 1408.6865
50 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
51 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
52 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
53 E. Gross and O. Vitells Trial factors for the look elsewhere effect in high energy physics EPJC 70 (2010) 525 1005.1891
54 A. L. Read Presentation of search results: The CL$ _{\text{s}} $ technique JPG 28 (2002) 2693
55 T. Junk Confidence level computation for combining searches with small statistics NIM A 434 (1999) 435 hep-ex/9902006
56 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