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A search for production of the supersymmetric partners of the top quark, top squarks, is presented. The search is based on proton-proton collision events containing multiple jets, no leptons, and large transverse momentum imbalance. The data were collected with the CMS detector at the CERN LHC at a center-of-mass energy of 13 TeV, and correspond to an integrated luminosity of 137 fb$^{-1}$. The targeted signal production scenarios are direct and gluino-mediated top squark production, including scenarios in which the top squark and neutralino masses are nearly degenerate. The search utilizes novel algorithms based on deep neural networks that identify hadronically decaying top quarks and W bosons, which are expected in many of the targeted signal models. No statistically significant excess of events is observed relative to the expectation from the standard model, and limits on the top squark production cross section are obtained in the context of simplified supersymmetric models for various production and decay modes. Exclusion limits as high as 1310 GeV are established at the 95% confidence level on the mass of the top squark for direct top squark production models, and as high as 2260 GeV on the mass of the gluino for gluino-mediated top squark production models. These results represent a significant improvement over the results of previous searches for supersymmetry by CMS in the same final state.
Top quark tagging efficiencies are shown as a function of the generator-level top quark $p_T$ for the merged tagging algorithm and resolved tagging algorithm described in the paper. This plot shows the efficiencies as calculated in a sample of simulated $t\bar{t}$ events in which one top quark decays leptonically, while the other decays hadronically. In addition to the individual algorithms shown as orange squares (boosted top quarks) and green inverted triangles (resolved top quarks), the total top quark tagging efficiency (blue dots) is also shown.
W boson tagging efficiencies are shown as a function of the generator-level W boson $p_T$ for the merged tagging algorithm described in the paper. This plot shows the W boson tagging efficiency when calculated in a sample of simulated WW events.
Comparison between data and simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $p_T^{miss}$ after scaling the simulation to match the total yield in data. The hatched region indicates the total shape uncertainty in the simulation.
The ratio between the observed data and the simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $p_T^{miss}$ after scaling the simulation to match the total yield in data.
Comparison between data and simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $N_t$ after scaling the simulation to match the total yield in data. The hatched region indicates the total shape uncertainty in the simulation.
The ratio between the observed data and the simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $N_t$ after scaling the simulation to match the total yield in data.
Comparison between data and simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $N_W$ after scaling the simulation to match the total yield in data. The hatched region indicates the total shape uncertainty in the simulation.
The ratio between the observed data and the simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $N_W$ after scaling the simulation to match the total yield in data.
Comparison between data and simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $N_{\text{res}}$ after scaling the simulation to match the total yield in data. The hatched region indicates the total shape uncertainty in the simulation.
The ratio between the observed data and the simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $N_{\text{res}}$ after scaling the simulation to match the total yield in data.
Observed event yields in data (black points) and predicted SM background (filled histograms) for the low $\Delta$m search bins 0--52. The signal models are denoted in the legend with the masses in GeV of the SUSY particles in parentheses: $(m_{\tilde{t}}, m_{\tilde{\chi}^0_1})$ or $(m_{\tilde{g}}, m_{\tilde{\chi}^0_1})$ for the T2 or T1 signal models, respectively. The hatched bands correspond to the total uncertainty in the background prediction. The (unstacked) distributions for two example signal models are also shown.
The ratio of the data to the total background prediction for the low $\Delta$m search bins 0--52. The hatched bands correspond to the total uncertainty in the background prediction.
Observed event yields in data (black points) and predicted SM background (filled histograms) for the high $\Delta$m search bins 53--104. The signal models are denoted in the legend with the masses in GeV of the SUSY particles in parentheses: $(m_{\tilde{t}}, m_{\tilde{\chi}^0_1})$ or $(m_{\tilde{g}}, m_{\tilde{\chi}^0_1})$ for the T2 or T1 signal models, respectively. The hatched bands correspond to the total uncertainty in the background prediction. The (unstacked) distributions for two example signal models are also shown.
The ratio of the data to the total background prediction for the high $\Delta$m search bins 53--104. The hatched bands correspond to the total uncertainty in the background prediction.
Observed event yields in data (black points) and predicted SM background (filled histograms) for the high $\Delta$m search bins 105--152 with ${N_b = 2}$. The signal models are denoted in the legend with the masses in GeV of the SUSY particles in parentheses: $(m_{\tilde{t}}, m_{\tilde{\chi}^0_1})$ or $(m_{\tilde{g}}, m_{\tilde{\chi}^0_1})$ for the T2 or T1 signal models, respectively. The hatched bands correspond to the total uncertainty in the background prediction. The (unstacked) distributions for two example signal models are also shown.
The ratio of the data to the total background prediction for the high $\Delta$m search bins 105--152 with ${N_b = 2}$. The hatched bands correspond to the total uncertainty in the background prediction.
Observed event yields in data (black points) and predicted SM background (filled histograms) for the high $\Delta$m search bins 153--182 with ${N_b \geq 3}$. The signal models are denoted in the legend with the masses in GeV of the SUSY particles in parentheses: $(m_{\tilde{t}}, m_{\tilde{\chi}^0_1})$ or $(m_{\tilde{g}}, m_{\tilde{\chi}^0_1})$ for the T2 or T1 signal models, respectively. The hatched bands correspond to the total uncertainty in the background prediction. The (unstacked) distributions for two example signal models are also shown.
The ratio of the data to the total background prediction for the high $\Delta$m search bins 153--182 with ${N_b \geq 3}$. The hatched bands correspond to the total uncertainty in the background prediction.
The observed 95% CL upper limit on the production cross section of the T2tt simplified model as a function of the top squark and LSP masses. No interpretation is provided for signal models for which ${|{m_{\tilde{t}} - m_{\tilde{\chi}^0_1} - m_t}| < 25 GeV}$ and ${m_{\tilde{t}} < 275 GeV}$ as described in the text.
The expected 95% CL upper limit on the production cross section of the T2tt simplified model as a function of the top squark and LSP masses. No interpretation is provided for signal models for which ${|{m_{\tilde{t}} - m_{\tilde{\chi}^0_1} - m_t}| < 25 GeV}$ and ${m_{\tilde{t}} < 275 GeV}$ as described in the text.
The observed exclusion contour of the T2tt simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$). No interpretation is provided for signal models for which ${|{m_{\tilde{t}} - m_{\tilde{\chi}^0_1} - m_t}| < 25 GeV}$ and ${m_{\tilde{t}} < 275 GeV}$ as described in the text.
The mean expected exclusion contour of the T2tt simplified model and the region containing 68 and 95\% ($\pm 1$ and $2\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis. No interpretation is provided for signal models for which ${|{m_{\tilde{t}} - m_{\tilde{\chi}^0_1} - m_t}| < 25 GeV}$ and ${m_{\tilde{t}} < 275 GeV}$ as described in the text.
The observed 95% CL upper limit on the production cross section of the T2bW simplified model as a function of the top squark and LSP masses.
The expected 95% CL upper limit on the production cross section of the T2bW simplified model as a function of the top squark and LSP masses.
The observed exclusion contour of the T2bW simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).
The mean expected exclusion contour of the T2bW simplified model and the region containing 68 and 95\% ($\pm 1$ and $2\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.
The observed 95% CL upper limit on the production cross section of the T2tb simplified model as a function of the top squark and LSP masses.
The expected 95% CL upper limit on the production cross section of the T2tb simplified model as a function of the top squark and LSP masses.
The observed exclusion contour of the T2tb simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).
The mean expected exclusion contour of the T2tb simplified model and the region containing 68 and 95\% ($\pm 1$ and $2\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.
The observed 95% CL upper limit on the production cross section of the T2ttC simplified model as a function of the top squark mass and the difference between the top squark and LSP masses.
The expected 95% CL upper limit on the production cross section of the T2ttC simplified model as a function of the top squark mass and the difference between the top squark and LSP masses.
The observed exclusion contour of the T2ttC simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).
The mean expected exclusion contour of the T2ttC simplified model and the region containing 68\% ($\pm 1\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.
The observed 95% CL upper limit on the production cross section of the T2bWC simplified model as a function of the top squark mass and the difference between the top squark and LSP masses.
The expected 95% CL upper limit on the production cross section of the T2bWC simplified model as a function of the top squark mass and the difference between the top squark and LSP masses.
The observed exclusion contour of the T2bWC simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).
The mean expected exclusion contour of the T2bWC simplified model and the region containing 68\% ($\pm 1\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.
The observed 95% CL upper limit on the production cross section of the T2cc simplified model as a function of the top squark mass and the difference between the top squark and LSP masses.
The expected 95% CL upper limit on the production cross section of the T2cc simplified model as a function of the top squark mass and the difference between the top squark and LSP masses.
The observed exclusion contour of the T2cc simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).
The mean expected exclusion contour of the T2cc simplified model and the region containing 68\% ($\pm 1\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.
The observed 95% CL upper limit on the production cross section of the T1tttt simplified model as a function of the gluino and LSP masses.
The expected 95% CL upper limit on the production cross section of the T1tttt simplified model as a function of the gluino and LSP masses.
The observed exclusion contour of the T1tttt simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).
The mean expected exclusion contour of the T1tttt simplified model and the region containing 68 and 95\% ($\pm 1$ and $2\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.
The observed 95% CL upper limit on the production cross section of the T1ttbb simplified model as a function of the gluino and LSP masses.
The expected 95% CL upper limit on the production cross section of the T1ttbb simplified model as a function of the gluino and LSP masses.
The observed exclusion contour of the T1ttbb simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).
The mean expected exclusion contour of the T1ttbb simplified model and the region containing 68 and 95\% ($\pm 1$ and $2\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.
The observed 95% CL upper limit on the production cross section of the T5ttcc simplified model as a function of the gluino and LSP masses. The upper limits do not take into account contributions from direct top squark pair production; however, its effect is small for $m_{\tilde{\chi}^0_1} > 600 GeV$, which corresponds to the phase space beyond the exclusions based on direct top squark pair production. The excluded regions based on direct top squark pair production from this search and earlier searches are indicated by the hatched areas.
The expected 95% CL upper limit on the production cross section of the T5ttcc simplified model as a function of the gluino and LSP masses. The uppser limits do not take into account contributions from direct top squark pair production; however, its effect is small for $m_{\tilde{\chi}^0_1} > 600 GeV$, which corresponds to the phase space beyond the exclusions based on direct top squark pair production. The excluded regions based on direct top squark pair production from this search and earlier searches are indicated by the hatched areas.
The observed exclusion contour of the T5ttcc simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$). The expected and observed upper limits do not take into account contributions from direct top squark pair production; however, its effect is small for $m_{\tilde{\chi}^0_1} > 600 GeV$, which corresponds to the phase space beyond the exclusions based on direct top squark pair production. The excluded regions based on direct top squark pair production from this search and earlier searches are indicated by the hatched areas.
The mean expected exclusion contour of the T5ttcc simplified model and the region containing 68% and 95% ($\pm 1$ and $2\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis. The expected and observed upper limits do not take into account contributions from direct top squark pair production; however, its effect is small for $m_{\tilde{\chi}^0_1} > 600 GeV$, which corresponds to the phase space beyond the exclusions based on direct top squark pair production. The excluded regions based on direct top squark pair production from this search and earlier searches are indicated by the hatched areas.
A search for dark matter in events with a displaced nonresonant muon pair and missing transverse momentum is presented. The analysis is performed using an integrated luminosity of 138 fb$^{-1}$ of proton-proton (pp) collision data at a center-of-mass energy of 13 TeV produced by the LHC in 2016-2018. No significant excess over the predicted backgrounds is observed. Upper limits are set on the product of the inelastic dark matter production cross section $\sigma$(pp $\to$ A' $\to$$\chi_1$$\chi_2$) and the decay branching fraction $\mathcal{B}$($\chi_2$$\to$$\chi_1 \mu^+ \mu^-$), where A' is a dark photon and $\chi_1$ and $\chi_2$ are states in the dark sector with near mass degeneracy. This is the first dedicated collider search for inelastic dark matter.
Definition of ABCD bins and yields in data, per match category. The predicted yield in the bin with the smallest backgrounds (bin D) is extracted from the simultaneous four-bin fit by assuming zero signal, which corresponds to $(\text{Obs. B} \times \text{Obs. C}) / (\text{Obs. A})$ in this limit.
Simulated muon reconstruction efficiency of standard (blue squares) and displaced (red circles) reconstruction algorithms as a function of transverse vertex displacement $v_{xy}$. The two dashed vertical gray lines denote the ends of the fiducial tracker and muon detector regions, respectively.
Measured min-$d_{xy}$ distribution in the 2-match category, after requiring the $d_{xy}$ muon to pass the isolation requirement $I_{\mathrm{rel}}^{\mathrm{PF}} <0.25$ (i. e., the B and D bins of the ABCD plane). Overlaid with a red histogram is the background predicted from the region of the ABCD plane failing the same requirement (the A and C bins), as well as three signal benchmark hypotheses (as defined in the legends), assuming $\alpha_D = \alpha_{\mathrm{EM}}$ (the fine-structure constant). The red hatched bands correspond to the background prediction uncertainty. The last bin includes the overflow.
Two-dimensional exclusion surfaces for $\Delta = 0.1 \, m_1$ as a function of the DM mass $m_1$ and the signal strength $y$, with $m_{A'} = 3 \, m_1$. Filled histograms denote observed limits on $\sigma(\mathrm{pp} \to A' \to \chi_2 \chi_1) \, \mathcal{B}(\chi_2 \to \chi_1 \mu^+ \mu^-)$. Solid (dashed) curves denote the observed (expected) exclusion limits at 95% CL, with 68% CL uncertainty bands around the expectation. Regions above the curves are excluded, depending on the $\alpha_D$ hypothesis: $\alpha_{\mathrm{D}} = \alpha_{\mathrm{EM}}$ (dark blue) or 0.1 (light magenta).
Two-dimensional exclusion surfaces for $\Delta = 0.4 \, m_1$ as a function of the DM mass $m_1$ and the signal strength $y$, with $m_{A'} = 3 \, m_1$. Filled histograms denote observed limits on $\sigma(\mathrm{pp} \to A' \to \chi_2 \chi_1) \, \mathcal{B}(\chi_2 \to \chi_1 \mu^+ \mu^-)$. Solid (dashed) curves denote the observed (expected) exclusion limits at 95% CL, with 68% CL uncertainty bands around the expectation. Regions above the curves are excluded, depending on the $\alpha_D$ hypothesis: $\alpha_{\mathrm{D}} = \alpha_{\mathrm{EM}}$ (dark blue) or 0.1 (light magenta).
The first collider search for dark matter arising from a strongly coupled hidden sector is presented and uses a data sample corresponding to 138 fb$^{-1}$, collected with the CMS detector at the CERN LHC, at $\sqrt{s} =$ 13 TeV. The hidden sector is hypothesized to couple to the standard model (SM) via a heavy leptophobic Z' mediator produced as a resonance in proton-proton collisions. The mediator decay results in two "semivisible" jets, containing both visible matter and invisible dark matter. The final state therefore includes moderate missing energy aligned with one of the jets, a signature ignored by most dark matter searches. No structure in the dijet transverse mass spectra compatible with the signal is observed. Assuming the Z' has a universal coupling of 0.25 to the SM quarks, an inclusive search, relevant to any model that exhibits this kinematic behavior, excludes mediator masses of 1.5-4.0 TeV at 95% confidence level, depending on the other signal model parameters. To enhance the sensitivity of the search for this particular class of hidden sector models, a boosted decision tree (BDT) is trained using jet substructure variables to distinguish between semivisible jets and SM jets from background processes. When the BDT is employed to identify each jet in the dijet system as semivisible, the mediator mass exclusion increases to 5.1 TeV, for wider ranges of the other signal model parameters. These limits exclude a wide range of strongly coupled hidden sector models for the first time.
The normalized distribution of the characteristic variable $R_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $R_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $R_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $\Delta\phi_{\text{min}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $\Delta\phi_{\text{min}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $\Delta\phi_{\text{min}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $m_{\text{SD}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $m_{\text{SD}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $m_{\text{SD}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $D_{p_{\text{T}}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $D_{p_{\text{T}}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $D_{p_{\text{T}}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized BDT discriminator distribution for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models.
The normalized BDT discriminator distribution for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models.
The normalized BDT discriminator distribution for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The $m_{\text{T}}$ distribution for the high-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{3}(x) = \exp(p_{1}x)x^{p_{2}(1+p_{3}\ln(x))}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{3}(x) = \exp(p_{1}x)x^{p_{2}(1+p_{3}\ln(x))}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{3}(x) = \exp(p_{1}x)x^{p_{2}(1+p_{3}\ln(x))}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The 95% CL upper limits on the product of the cross section and branching fraction from the inclusive search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the inclusive search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the inclusive search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the BDT-based search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the BDT-based search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the BDT-based search for the $\alpha_{\text{dark}}$ variations.
The three two-dimensional signal model parameter scans.
The three two-dimensional signal model parameter scans.
The three two-dimensional signal model parameter scans.
Metrics representing the performance of the BDT for the benchmark signal model ($m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$), compared to each of the major SM background processes.
Metrics representing the performance of the BDT for the benchmark signal model ($m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$), compared to each of the major SM background processes.
Metrics representing the performance of the BDT for the benchmark signal model ($m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$), compared to each of the major SM background processes.
The range of effects on the signal yield for each systematic uncertainty and the total. Values less than 0.01% are rounded to 0.0%.
The range of effects on the signal yield for each systematic uncertainty and the total. Values less than 0.01% are rounded to 0.0%.
The range of effects on the signal yield for each systematic uncertainty and the total. Values less than 0.01% are rounded to 0.0%.
The normalized distribution of the variable $m_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $m_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $m_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $\Delta\eta(\text{J}_{1},\text{J}_{2})$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $\Delta\eta(\text{J}_{1},\text{J}_{2})$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $\Delta\eta(\text{J}_{1},\text{J}_{2})$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $p_{\text{T}}^{\text{miss}}$ for the simulated SM backgrounds and several signal models. The $R_{\text{T}}$ requirement is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $p_{\text{T}}^{\text{miss}}$ for the simulated SM backgrounds and several signal models. The $R_{\text{T}}$ requirement is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $p_{\text{T}}^{\text{miss}}$ for the simulated SM backgrounds and several signal models. The $R_{\text{T}}$ requirement is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\text{e}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\text{e}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\text{e}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\mu}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\mu}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\mu}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of $\Delta\eta(\text{J}_{1},\text{J}_{2})$ vs. $R_{\text{T}}$ for the simulated QCD background. The preselection requirements on both variables are omitted, but all other preselection requirements are applied.
The normalized distribution of $\Delta\eta(\text{J}_{1},\text{J}_{2})$ vs. $R_{\text{T}}$ for the simulated QCD background. The preselection requirements on both variables are omitted, but all other preselection requirements are applied.
The normalized distribution of $\Delta\eta(\text{J}_{1},\text{J}_{2})$ vs. $R_{\text{T}}$ for the simulated QCD background. The preselection requirements on both variables are omitted, but all other preselection requirements are applied.
The normalized distribution of $p_{\text{T}}^{\text{miss}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $p_{\text{T}}^{\text{miss}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $p_{\text{T}}^{\text{miss}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $R_{\text{T}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $R_{\text{T}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $R_{\text{T}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distributions of the BDT input variable $\tau_{21}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{21}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{21}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{32}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{32}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{32}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{2}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{2}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{2}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{3}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{3}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{3}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $g_{\text{jet}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $g_{\text{jet}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $g_{\text{jet}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{major}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{major}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{major}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{minor}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{minor}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{minor}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\Delta\phi(\vec{J},\vec{p}_{\text{T}}^{\text{miss}})$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\Delta\phi(\vec{J},\vec{p}_{\text{T}}^{\text{miss}})$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\Delta\phi(\vec{J},\vec{p}_{\text{T}}^{\text{miss}})$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{\pm}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{\pm}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{\pm}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{e}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{e}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{e}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\mu}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\mu}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\mu}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{0}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{0}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{0}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\gamma}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\gamma}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\gamma}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
Comparison of different the dijet mass $m_{\text{J}\text{J}}$, the transverse mass $m_{\text{T}}$, and the Monte Carlo (MC) mass $m_{\text{MC}}$ for a signal model with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. No selection is applied, except that there must be at least two jets. $m_{\text{MC}}$ is computed by adding the generator-level four-vectors for invisible particles to the dijet system, to represent the achievable resolution if the invisible component were fully measured. The last bin of each histogram includes the overflow events.
Comparison of different the dijet mass $m_{\text{J}\text{J}}$, the transverse mass $m_{\text{T}}$, and the Monte Carlo (MC) mass $m_{\text{MC}}$ for a signal model with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. No selection is applied, except that there must be at least two jets. $m_{\text{MC}}$ is computed by adding the generator-level four-vectors for invisible particles to the dijet system, to represent the achievable resolution if the invisible component were fully measured. The last bin of each histogram includes the overflow events.
Comparison of different the dijet mass $m_{\text{J}\text{J}}$, the transverse mass $m_{\text{T}}$, and the Monte Carlo (MC) mass $m_{\text{MC}}$ for a signal model with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. No selection is applied, except that there must be at least two jets. $m_{\text{MC}}$ is computed by adding the generator-level four-vectors for invisible particles to the dijet system, to represent the achievable resolution if the invisible component were fully measured. The last bin of each histogram includes the overflow events.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
The proportions of each SM background process in the high-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the high-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the high-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the low-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the low-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the low-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the high-SVJ2 signal region.
The proportions of each SM background process in the high-SVJ2 signal region.
The proportions of each SM background process in the high-SVJ2 signal region.
The proportions of each SM background process in the low-SVJ2 signal region.
The proportions of each SM background process in the low-SVJ2 signal region.
The proportions of each SM background process in the low-SVJ2 signal region.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
Relative efficiencies in % for each step of the event selection process for the major background processes. Statistical uncertainties, at most 1.8%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for the major background processes. Statistical uncertainties, at most 1.8%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for the major background processes. Statistical uncertainties, at most 1.8%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.5%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.5%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.5%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 2.6%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 2.6%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 2.6%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 1.2%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 1.2%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 1.2%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.9%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.9%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.9%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
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