The JEC, JER, and total systematic uncertainties in unfolded cross sections as functions of transverse momentum, for 1.5<|y|<2. The total systematic uncertainty includes also the luminosity, jet identification and trigger efficiency uncertainties.

The unfolded measured particle-level inclusive jet cross section as functions of jet pT (markers), for |y|<0.5, compared to the NLO perturbative QCD prediction (histogram), using the CT14NLO PDF set, with muR = muF = HT, and corrected for the NP effects. The experimental and theoretical systematic uncertainties are shown.

The unfolded measured particle-level inclusive jet cross section as functions of jet pT (markers), for 0.5<|y|<1, compared to the NLO perturbative QCD prediction (histogram), using the CT14NLO PDF set, with muR = muF = HT, and corrected for the NP effects. The experimental and theoretical systematic uncertainties are shown.

The unfolded measured particle-level inclusive jet cross section as functions of jet pT (markers), for 1<|y|<1.5, compared to the NLO perturbative QCD prediction (histogram), using the CT14NLO PDF set, with muR = muF = HT, and corrected for the NP effects. The experimental and theoretical systematic uncertainties are shown.

The unfolded measured particle-level inclusive jet cross section as functions of jet pT (markers), for 1.5<|y|<2, compared to the NLO perturbative QCD prediction (histogram), using the CT14NLO PDF set, with muR = muF = HT, and corrected for the NP effects. The experimental and theoretical systematic uncertainties are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = pT, for |y|<0.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = pT, for 0.5<|y|<1. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = pT, for 1<|y|<1.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = pT, for 1.5<|y|<2. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = HT, for |y|<0.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = HT, for 0.5<|y|<1. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = HT, for 1<|y|<1.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = HT, for 1.5<|y|<2. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the CT14NNLO PDF set, with mu = HT, for |y|<0.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the CT14NNLO PDF set, with mu = HT, for 0.5<|y|<1. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the CT14NNLO PDF set, with mu = HT, for 1<|y|<1.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the CT14NNLO PDF set, with mu = HT, for 1.5<|y|<2. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the NNPDF31NNLO PDF set, with mu = HT, for |y|<0.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the NNPDF31NNLO PDF set, with mu = HT, for 0.5<|y|<1. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the NNPDF31NNLO PDF set, with mu = HT, for 1<|y|<1.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the NNPDF31NNLO PDF set, with mu = HT, for 1.5<|y|<2. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

The effect of aS(MZ) variation, for |y|<0.5. The NNLO theoretical cross section predictions using the NNPDF31NNLO PDF with m = HT, calculated for different choices of aS (0.108, 0.110, 0.112, 0.114, 0.116, 0.117, 0.118, 0.119, 0.120, 0.122, and 0.124), are divided by the benchmark NNLO prediction for aS = 0.118 and the same choice of PDF set, muR, and muF. Also shown is the experimental unfolded measurement divided by the same benchmark prediction. The width of the unity line corresponds to the statistical uncertainty from the MC integration for the determination of the NNLO prediction. The error bars on the unfolded data correspond to the total experimental statistical and systematic uncertainty added in quadrature.

The effect of aS(MZ) variation, for 0.5<|y|<1. The NNLO theoretical cross section predictions using the NNPDF31NNLO PDF with m = HT, calculated for different choices of aS (0.108, 0.110, 0.112, 0.114, 0.116, 0.117, 0.118, 0.119, 0.120, 0.122, and 0.124), are divided by the benchmark NNLO prediction for aS = 0.118 and the same choice of PDF set, muR, and muF. Also shown is the experimental unfolded measurement divided by the same benchmark prediction. The width of the unity line corresponds to the statistical uncertainty from the MC integration for the determination of the NNLO prediction. The error bars on the unfolded data correspond to the total experimental statistical and systematic uncertainty added in quadrature.

The effect of aS(MZ) variation, for 1<|y|<1.5. The NNLO theoretical cross section predictions using the NNPDF31NNLO PDF with m = HT, calculated for different choices of aS (0.108, 0.110, 0.112, 0.114, 0.116, 0.117, 0.118, 0.119, 0.120, 0.122, and 0.124), are divided by the benchmark NNLO prediction for aS = 0.118 and the same choice of PDF set, muR, and muF. Also shown is the experimental unfolded measurement divided by the same benchmark prediction. The width of the unity line corresponds to the statistical uncertainty from the MC integration for the determination of the NNLO prediction. The error bars on the unfolded data correspond to the total experimental statistical and systematic uncertainty added in quadrature.

The effect of aS(MZ) variation, for 1.5<|y|<2. The NNLO theoretical cross section predictions using the NNPDF31NNLO PDF with m = HT, calculated for different choices of aS (0.108, 0.110, 0.112, 0.114, 0.116, 0.117, 0.118, 0.119, 0.120, 0.122, and 0.124), are divided by the benchmark NNLO prediction for aS = 0.118 and the same choice of PDF set, muR, and muF. Also shown is the experimental unfolded measurement divided by the same benchmark prediction. The width of the unity line corresponds to the statistical uncertainty from the MC integration for the determination of the NNLO prediction. The error bars on the unfolded data correspond to the total experimental statistical and systematic uncertainty added in quadrature.

Unfolded correlation matrix for |y|<0.5.

Unfolded correlation matrix for 0.5<|y|<1.

Unfolded correlation matrix for 1<|y|<1.5.

Unfolded correlation matrix for 1.5<|y|<2.

Statistical correlation coefficients for double-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet invariant mass ($m_{1,2}$) and the absolute rapidity of the outermost jet ($\left| y \right|_\text{max}$)

Double-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$) and the absolute rapidity of the outermost jet ($\left| y \right|_\text{max}$)

Electroweak corrections to double-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$) and the absolute rapidity of the outermost jet ($\left| y \right|_\text{max}$)

Nonperturbative corrections to double-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$) and the absolute rapidity of the outermost jet ($\left| y \right|_\text{max}$)

Statistical correlation coefficients for double-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$) and the absolute rapidity of the outermost jet ($\left| y \right|_\text{max}$)

Triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Electroweak corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Nonperturbative corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Statistical correlation coefficients for triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Electroweak corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Nonperturbative corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Statistical correlation coefficients for triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Electroweak corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Nonperturbative corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Statistical correlation coefficients for triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Electroweak corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Nonperturbative corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Statistical correlation coefficients for triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Correlation matrix associated to the statistical covariance matrix of the data and MC for the primary Lund jet plane density for AK8 jets in a one-dimensional representation with bin indices. The mapping between the bin indices and the physical binning can be imported from the XML file attached to this HepData record using the TUnfoldBinningXML class of ROOT (qualitatively, it corresponds to slicing the Lund plane horizontally from low kT to high kT).

Post-fit distributions of $M_{\ell v jj}$ in the $R2B_A$ subregion for electrons. All process yields and nuisance parameters are set to the values obtained from the background plus signal fit. The signal considered for the fit corresponds to the purely right-handed production of a W' with $m_{W'}$ of 3.6 TeV and a relative width of 1$\%$ of the $m_{W'}$, and is represented by the solid red line. The lower panels show the data minus the expected number of events, normalized to the statistical uncertainty of the data. The orange band represents the systematic uncertainties, also normalized to the statistical uncertainty of the data.

Post-fit distributions of $M_{\ell v jj}$ in the $RW'_A$ subregion for muons. All process yields and nuisance parameters are set to the values obtained from the background plus signal fit. The signal considered for the fit corresponds to the purely right-handed production of a W' with $m_{W'}$ of 3.6 TeV and a relative width of 1$\%$ of the $m_{W'}$, and is represented by the solid red line. The lower panels show the data minus the expected number of events, normalized to the statistical uncertainty of the data. The orange band represents the systematic uncertainties, also normalized to the statistical uncertainty of the data.

Post-fit distributions of $M_{\ell v jj}$ in the $RW'_A$ subregion for electrons. All process yields and nuisance parameters are set to the values obtained from the background plus signal fit. The signal considered for the fit corresponds to the purely right-handed production of a W' with $m_{W'}$ of 3.6 TeV and a relative width of 1$\%$ of the $m_{W'}$, and is represented by the solid red line. The lower panels show the data minus the expected number of events, normalized to the statistical uncertainty of the data. The orange band represents the systematic uncertainties, also normalized to the statistical uncertainty of the data.

Post-fit distributions of $M_{\ell v jj}$ in the $RT_A$ subregion for muons. All process yields and nuisance parameters are set to the values obtained from the background plus signal fit. The signal considered for the fit corresponds to the purely right-handed production of a W' with $m_{W'}$ of 3.6 TeV and a relative width of 1$\%$ of the $m_{W'}$, and is represented by the solid red line. The lower panels show the data minus the expected number of events, normalized to the statistical uncertainty of the data. The orange band represents the systematic uncertainties, also normalized to the statistical uncertainty of the data.

Post-fit distributions of $M_{\ell v jj}$ in the $RT_A$ subregion for electrons. All process yields and nuisance parameters are set to the values obtained from the background plus signal fit. The signal considered for the fit corresponds to the purely right-handed production of a W' with $m_{W'}$ of 3.6 TeV and a relative width of 1$\%$ of the $m_{W'}$, and is represented by the solid red line. The lower panels show the data minus the expected number of events, normalized to the statistical uncertainty of the data. The orange band represents the systematic uncertainties, also normalized to the statistical uncertainty of the data.

Observed and expected 95% CL upper limits on the product of the production cross section for a left-handed production of a tb quark pair in the $s$-channel, mediated by a W or W' bosons and including interference terms, given as functions of $m_{W'}$ for a relative width of 1%. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The solid red curves show the theoretical expectation at LO.

Observed and expected 95% CL upper limits on the product of the production cross section for a left-handed production of a tb quark pair in the $s$-channel, mediated by a W or W' bosons and including interference terms, given as functions of $m_{W'}$ for a relative width of 10%. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The solid red curves show the theoretical expectation at LO.

Observed and expected 95% CL upper limits on the product of the production cross section for a left-handed production of a tb quark pair in the $s$-channel, mediated by a W or W' bosons and including interference terms, given as functions of $m_{W'}$ for a relative width of 20%. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The solid red curves show the theoretical expectation at LO.

Observed and expected 95% CL upper limits on the product of the production cross section for a left-handed production of a tb quark pair in the $s$-channel, mediated by a W or W' bosons and including interference terms, given as functions of $m_{W'}$ for a relative width of 30%. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The solid red curves show the theoretical expectation at LO.

Observed and expected 95% CL upper limits on the product of the production cross section for a right-handed W' boson and the W' --> tb branching fraction, as functions of $m_{W'}$ for a relative width of 1%. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The solid red curves show the theoretical expectation at LO.

Observed and expected 95% CL upper limits on the product of the production cross section for a right-handed W' boson and the W' --> tb branching fraction, as functions of $m_{W'}$ for a relative width of 10%. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The solid red curves show the theoretical expectation at LO.

Observed and expected 95% CL upper limits on the product of the production cross section for a right-handed W' boson and the W' --> tb branching fraction, as functions of $m_{W'}$ for a relative width of 20%. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The solid red curves show the theoretical expectation at LO.

Observed and expected 95% CL upper limits on the product of the production cross section for a right-handed W' boson and the W' --> tb branching fraction, as functions of $m_{W'}$ for a relative width of 30%. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The solid red curves show the theoretical expectation at LO.

Observed 95% CL upper limit on the production cross section for a left-handed W' boson in the tb final state, as functions of $m_{W'}$ and relative width $\Gamma/m_{W'}$. Numbers in red, written diagonally, represent values of the excluded cross sections that are lower than the theoretical ones for the analyzed model.

Observed 95% CL upper limit on the production cross section for a right-handed W' boson in the tb final state, as functions of $m_{W'}$ and relative width $\Gamma/m_{W'}$. Numbers in red, written diagonally, represent values of the excluded cross sections that are lower than the theoretical ones for the analyzed model.

Observed 95% CL upper limit on the production cross section for a generalized left-right coupling of the W' boson to a t and a b quark for a mass of the W' boson of 2 TeV.

Observed 95% CL upper limit on the production cross section for a generalized left-right coupling of the W' boson to a t and a b quark for a mass of the W' boson of 2.8 TeV.

Observed 95% CL upper limit on the production cross section for a generalized left-right coupling of the W' boson to a t and a b quark for a mass of the W' boson of 3.6 TeV.

Observed 95% CL upper limit on the production cross section for a generalized left-right coupling of the W' boson to a t and a b quark for a mass of the W' boson of 4.4 TeV.

Observed 95% CL upper limit on the production cross section for a generalized left-right coupling of the W' boson to a t and a b quark for a mass of the W' boson of 5.2 TeV.

Observed 95% CL upper limit on the production cross section for a generalized left-right coupling of the W' boson to a t and a b quark for a mass of the W' boson of 6 TeV.

Expected 95% CL lower limit on $m_{W'}$ for a generalized left-right coupling of the W' boson to a t and a b quark.

Observed 95% CL lower limit on $m_{W'}$ for a generalized left-right coupling of the W' boson to a t and a b quark.

Observed and expected 95% CL upper limits on the product of the production cross section for a right-handed W' boson and the W' --> tb branching fraction, as functions of the $m_{W'}$ for a relative width of 10%. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The solid curves show the theoretical expectation at LO in the case that the couplings, and thus the partial widths, are varied together with the total width. In this interpretation the branching fraction of the W' --> tb decays is the same for each value of the width of the W' boson.

Observed and expected 95% CL upper limits on the product of the production cross section for a right-handed W' boson and the W' --> tb branching fraction, as functions of the $m_{W'}$ for a relative width of 20%. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The solid curves show the theoretical expectation at LO in the case that the couplings, and thus the partial widths, are varied together with the total width. In this interpretation the branching fraction of the W' --> tb decays is the same for each value of the width of the W' boson.

Observed and expected 95% CL upper limits on the product of the production cross section for a right-handed W' boson and the W' --> tb branching fraction, as functions of the $m_{W'}$ for a relative width of 30%. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The solid curves show the theoretical expectation at LO in the case that the couplings, and thus the partial widths, are varied together with the total width. In this interpretation the branching fraction of the W' --> tb decays is the same for each value of the width of the W' boson.

Observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(gg)g) \mathcal{A}$ for a cascade decay trijet resonance. The acceptance $\mathcal{A}$ is defined as $\mathcal{A} = N$(events with $m_{X}^{GEN} > 85\% m_{X}^{input}$) / $N$(events generated in the full phase space defined by the CMS default generator settings). Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Mass exclusion ranges of the benchmark signal scenarios are depicted with hatched areas inside the black contours.

Observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(qq)q) \mathcal{A}$ for a cascade decay trijet resonance. The acceptance $\mathcal{A}$ is defined as $\mathcal{A} = N$(events with $m_{X}^{GEN} > 85\% m_{X}^{input}$) / $N$(events generated in the full phase space defined by the CMS default generator settings). Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Mass exclusion ranges of the benchmark signal scenarios are depicted with hatched areas inside the black contours.

Efficiencies of the selection requirements on the benchmark signal processes: $Z_{R} \to ggg$ with nominal width ($\Gamma_{X}/m_{X}\sim 3\%$). A value of -1 means that the corresponding efficiency is not calculated for this year.

Efficiencies of the selection requirements on the benchmark signal processes: $Z_{R} \to ggg$ with narrow width ($\Gamma_{X}/m_{X}\sim 0.01\%$). A value of -1 means that the corresponding efficiency is not calculated for this year.

Efficiencies of the selection requirements on the benchmark signal processes: $G_{KK} \to {\varphi}(gg)g$, where $\varphi$ is the radion. A value of -1 means that the corresponding efficiency is not calculated for this year.

Efficiencies of the selection requirements on the benchmark signal processes: $q^{*} \to V(qq)q$, where $V$ is a beyond-the-SM vector boson. A value of -1 means that the corresponding efficiency is not calculated for this year.

Acceptance of the signal selection requirement $m_{X}^{\text{GEN}}/m_{X}^{\text{input}} > 85\%$ on the benchmark signal process $Z_{R} \to ggg$. The acceptance is defined as $\mathcal{A} = N$(events with $m_{X}^{\text{GEN}}/m_{X}^{\text{input}} > 85\%$)/$N$(events generated in the full phase space defined by the CMS default generator settings).

Acceptance of the signal selection requirement $m_{X}^{\text{GEN}}/m_{X}^{\text{input}} > 85\%$ on the benchmark signal process $G_{KK} \to {\varphi}(gg)g$.

Acceptance of the signal selection requirement $m_{X}^{\text{GEN}}/m_{X}^{\text{input}} > 85\%$ on the benchmark signal process $q^{*} \to V(qq)q$.

Observed local significance for a 3-body decay $ggg$ resonance, shown for resonances with nominal width (blue solid line) and narrow width (red dashed line).

Observed local significance for a cascade decay $ggg$ resonance.

Observed local significance for a cascade decay $qqq$ resonance.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(gg)g) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.2$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(gg)g) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.3$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(gg)g) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.4$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(gg)g) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.5$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(gg)g) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.6$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(gg)g) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.7$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(gg)g) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.8$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(qq)q) \mathcal{A}$ for a cascade decay trijet resonance $m_{Y} / m_{X} = 0.2$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(qq)q) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.3$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(qq)q) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.4$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(qq)q) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.5$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(qq)q) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.6$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(qq)q) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.7$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal.

Expected and observed limits at 95% CL on $\sigma \mathcal{B} (X \to Y(qq)q) \mathcal{A}$ for a cascade decay trijet resonance with $m_{Y} / m_{X} = 0.8$. Only 2016 data are used to derive limits below 2.0 TeV because of higher trigger thresholds in 2017 and 2018. Theoretical predictions of the benchmark are depicted with the red curve. A value of -1 in the table means that the corresponding theoretical prediction is not calculated for this signal

Cut flow table of the selection requirments for the $Z_{R}$ model scenarios. Values shown are absolute efficiencies, e.g., values shown in the column of 'Efficiency ($\Delta_{R}^{max} < 3.0$)' represent the cumulative efficiencies achieved through all selection requirements applied up to and including the current selection criterion.

Cut flow table of the selection requirments for the $G_{KK}$ model scenarios. Values shown are absolute efficiencies, e.g., values shown in the column of 'Efficiency ($\Delta_{R}^{max} < 3.0$)' represent the cumulative efficiencies achieved through all selection requirements applied up to and including the current selection criterion.

Cut flow table of the selection requirments for the $q^{*}$ model scenarios. Values shown are absolute efficiencies, e.g., values shown in the column of 'Efficiency ($\Delta_{R}^{max} < 3.0$)' represent the cumulative efficiencies achieved through all selection requirements applied up to and including the current selection criterion.

Predicted production cross section of the benchmark signal process $pp \to Z_{R} \to ggg$.

Predicted production cross section of the benchmark signal process $pp \to G_{KK} \to \varphi(gg)g$.

Predicted production cross section of the benchmark signal process $pp \to q^{*} \to V(qq)q$.

Transverse dilepton-$p_{T}^{miss}$ mass pre-fit distribution for selected events in SR2 of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Dilepton mass pre-fit distribution for selected events in SR3 of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Dilepton $p_T$ pre-fit distribution for selected events in SR3 of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Dijet $p_T$ pre-fit distribution for selected events in the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Lepton-dijet $p_T$ pre-fit distribution for selected events in the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Maximum $p_T$ of the visible particles divided by the missing $p_T$, for selected events in the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between jets, for selected events in the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the lepton and missing $p_T$, for selected events in the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the lepton and the dijet system, for selected events in the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta R$ distance between the leptons, for selected events in the non-prompt validation region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the di-lepton system and the missing $p_T$, for selected events in the non-prompt validation region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the lepton and the di-jet system, for selected events in the non-prompt validation region of the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the lepton-dijet system and the missing $p_T$, for selected events in the non-prompt validation region of the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Leading lepton $p_T$ pre-fit distribution for selected events in the top control region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Trailing lepton $p_T$ pre-fit distribution for selected events in the top control region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Dilepton mass pre-fit distribution for selected events in the Drell-Yan control region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Missing $p_T$ pre-fit distribution for selected events in the Drell-Yan control region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Missing $p_T$ pre-fit distribution for selected events in the $WW$ control region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Dilepton $p_T$ pre-fit distribution for selected events in the $WW$ control region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Minimum $p_T$ of the visible particles divided by the missing $p_T$, for selected events in the top control region of the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between jets, for selected events in the top control region of the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the lepton and missing $p_T$, for selected events in the $W$+jets control region of the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the lepton and the dijet system, for selected events in the $W$+jets control region of the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Unrolled $m_{ll}-m_{T}^{l min, p_{T}^{miss}}$ post-fit distributions in the di-leptonic channel in SR1 for the full data set. The histogram bins are spaced uniformly. Each group of five bins (from left to right) corresponds to $m_{T}^{l min, p_{T}^{miss}}$ distribution in a $m_{ll}$ region, placed in ascending order. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$.

Unrolled $m_{ll}-m_{T}^{l min, p_{T}^{miss}}$ post-fit distributions in the di-leptonic channel in SR2 for the full data set. The histogram bins are spaced uniformly. Each group of five bins (from left to right) corresponds to $m_{T}^{l min, p_{T}^{miss}}$ distribution in a $m_{ll}$ region, placed in ascending order. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$.

Unrolled $m_{ll}-m_{T}^{l min, p_{T}^{miss}}$ post-fit distributions in the di-leptonic channel in SR3 for the full data set. The histogram bins are spaced uniformly. Each group of five bins (from left to right) corresponds to $m_{T}^{l min, p_{T}^{miss}}$ distribution in a $m_{ll}$ region, placed in ascending order. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$.

Post-fit BDT distributions in the semi-leptonic channel for the full data set in the top control region. The signal prediction represents the mass point: $m_{s} = 160$ GeV, $m_{\chi} = 100$ GeV, $m_{Z'} = 500$ GeV

Post-fit BDT distributions in the semi-leptonic channel for the full data set in the $W$+jets control region. The signal prediction represents the mass point: $m_{s} = 160$ GeV, $m_{\chi} = 100$ GeV, $m_{Z'} = 500$ GeV

Post-fit BDT distributions in the semi-leptonic channel in the 2016 signal region. The signal prediction represents the mass point: $m_{s} = 160$ GeV, $m_{\chi} = 100$ GeV, $m_{Z'} = 500$ GeV

Post-fit BDT distributions in the semi-leptonic channel in the 2017+2018 signal region. The signal prediction represents the mass point: $m_{s} = 160$ GeV, $m_{\chi} = 100$ GeV, $m_{Z'} = 500$ GeV

Contour of the 95% CL observed upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

Contour of the 95% CL expected + 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

Contour of the 95% CL expected + 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

Contour of the 95% CL expected upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

Contour of the 95% CL expected - 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

Contour of the 95% CL expected - 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

Contour of the 95% CL observed upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

Contour of the 95% CL expected + 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

Contour of the 95% CL expected + 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

Contour of the 95% CL expected upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

Contour of the 95% CL expected - 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

Contour of the 95% CL expected - 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

Contour of the 95% CL observed upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

Contour of the 95% CL expected + 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

Contour of the 95% CL expected + 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

Contour of the 95% CL expected upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

Contour of the 95% CL expected - 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

Contour of the 95% CL expected - 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

Contour of the 95% CL observed upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

Contour of the 95% CL expected + 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

Contour of the 95% CL expected + 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

Contour of the 95% CL expected upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

Contour of the 95% CL expected - 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

Contour of the 95% CL expected - 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

The $\sigma / \sigma_{theory}$ 95% CL upper limit values for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

The $\sigma / \sigma_{theory}$ 95% CL upper limit values for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

The $\sigma / \sigma_{theory}$ 95% CL upper limit values for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

The $\sigma / \sigma_{theory}$ 95% CL upper limit values for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

Covariance matrix of the two parameters $A$ and $m$ of the linear 2-to-5-jets-bin adjustment in the background Monte Carlo. Please see the text of the paper for an explanation of $A$ and $m$. Best fit values of $A$ and m are available as a separate table in this HEPData record.

Best fit values of the two parameters $A$ and $m$ of the linear 2-to-6-jets-bin adjustment in the background Monte Carlo. Please see the text of the paper for an explanation of $A$ and $m$. Uncertainties on $A$ and $m$ can be obtained from the covariance matrix of the fit, available as a separate table in this HEPData Record.

Covariance matrix of the two parameters $A$ and $m$ of the linear 2-to-6-jets-bin adjustment in the background Monte Carlo. Please see the text of the paper for an explanation of $A$ and $m$. Best fit values of $A$ and m are available as a separate table in this HEPData record.

This table contains the pre-fit background model (i.e. setting all nuisance parameters to 0), the post-fit background model (i.e. setting all nuisance parameters to their best fit values given the observed data), and the observed data in the 4 Jets bin. Uncertainties are provided, but per-bin uncertainties do not capture the correlations between bins with nuisance parameter variations. For a full analysis, the full covariance matrix between the search regions, also present in this HEPData record, should be used.

This table contains the pre-fit background model (i.e. setting all nuisance parameters to 0), the post-fit background model (i.e. setting all nuisance parameters to their best fit values given the observed data), and the observed data in the 5 Jets bin. Uncertainties are provided, but per-bin uncertainties do not capture the correlations between bins with nuisance parameter variations. For a full analysis, the full covariance matrix between the search regions, also present in this HEPData record, should be used.

This table contains the pre-fit background model (i.e. setting all nuisance parameters to 0), the post-fit background model (i.e. setting all nuisance parameters to their best fit values given the observed data), and the observed data in the $\geq 6$ Jets bin. Uncertainties are provided, but per-bin uncertainties do not capture the correlations between bins with nuisance parameter variations. For a full analysis, the full covariance matrix between the search regions, also present in this HEPData record, should be used.

Covariance matrix between search regions, estimated by toy MC runs, varying the nuisance parameters according to their covariance matrix before performing any fit. Note that the two columns ($S_T$ Bin (axis 1)) and ($N_{jets}$ Bin (axis 1)) together define the x-axis of the covariance, and the two columns ($S_T$ Bin (axis 2)) and ($N_{jets}$ Bin (axis 2)) together define the y-axis of the covariance.

Covariance matrix between search regions, estimated by toy MC runs, varying the nuisance parameters according to their covariance matrix in the background-only fit. Note that the two columns ($S_T$ Bin (axis 1)) and (NJets Bin (axis 1)) together define the x-axis of the covariance, and the two columns ($S_T$ Bin (axis 2)) and (NJets Bin (axis 2)) together define the y-axis of the covariance.

Scan through (gluino mass, neutralino mass) parameter-space. This table has the gluino and neutralino mass as the independent parameters, and the following as dependent parameters: 1. Expected upper limits (95% $CL_s$) on signal strength, with $\pm 1\sigma$ and $\pm 2\sigma$ uncertainty terms from limited statistics. 2. Observed upper limits (95% $CL_s$) on signal strength, with a $\pm 1\sigma$ uncertainty from the theoretical prediction of the gluino production cross section. 3. Observed upper limits (95% $CL_s$) on gluino production cross section.

Scan through (squark mass, neutralino mass) parameter-space. This table has the squark and neutralino mass as the independent parameters, and the following as dependent parameters: 1. Expected upper limits (95% $CL_s$) on signal strength, with $\pm 1\sigma$ and $\pm 2\sigma$ uncertainty terms from limited statistics. 2. Observed upper limits (95% $CL_s$) on signal strength, with a $\pm 1\sigma$ uncertainty from the theoretical prediction of the squark production cross section. 3. Observed upper limits (95% $CL_s$) on squark production cross section.