Showing 10 of 3089 results
The first observation of the decay $\Xi^-_\mathrm{b}$$\to$$\psi$(2S)$\Xi^-$ and measurement of the branching ratio of $\Xi^-_\mathrm{b}$$\to$$\psi$(2S)$\Xi^-$ to $\Xi^-_\mathrm{b}$$\to$ J/$\psi$$\Xi^-$ are presented. The J/$\psi$ and $\psi$(2S) mesons are reconstructed using their dimuon decay modes. The results are based on proton-proton colliding beam data from the LHC collected by the CMS experiment at $\sqrt{s}$ = 13 TeV in 2016-2018, corresponding to an integrated luminosity of 140 fb$^{-1}$. The branching fraction ratio is measured to be $\mathcal{B}$($\Xi^-_\mathrm{b}$$\to$$\psi$(2S)$\Xi^-$)/$\mathcal{B}$($\Xi^-_\mathrm{b}$$\to$ J/$\psi$$\Xi^-$) = 0.84$^{+0.21}_{-0.19}$ (stat) $\pm$ 0.10 (syst) $\pm$ 0.02 ($\mathcal{B}$), where the last uncertainty comes from the uncertainties in the branching fractions of the charmonium states. New measurements of the $\Xi_\mathrm{b}^{\ast{}0}$ baryon mass and natural width are also presented, using the $\Xi_\mathrm{b}^-\pi^+$ final state, where the $\Xi^-_\mathrm{b}$ baryon is reconstructed through the decays J/$\psi \Xi^-$, $\psi$(2S)$\Xi^-$, J/$\psi \Lambda$K$^-$, and J/$\psi \Sigma^0$K$^-$. Finally, the fraction of the $\Xi^-_\mathrm{b}$ baryons produced from $\Xi_\mathrm{b}^{\ast{}0}$ decays is determined.
The measured ratio of branching fractions
Measured mass
Measured mass difference
Measured natural width
The measured inclusive ratio of production cross sections
A search for the production of long-lived particles in proton-proton collisions at a center-of-mass energy of 13 TeV at the CERN LHC is presented. The search is based on data collected by the CMS experiment in 2016-2018, corresponding to a total integrated luminosity of 137 fb$^{-1}$. This search is designed to be sensitive to long-lived particles with mean proper decay lengths between 0.1 and 1000 mm, whose decay products produce a final state with at least one displaced vertex and missing transverse momentum. A machine learning algorithm, which improves the background rejection power by more than an order of magnitude, is applied to improve the sensitivity. The observation is consistent with the standard model background prediction, and the results are used to constrain split supersymmetry (SUSY) and gauge-mediated SUSY breaking models with different gluino mean proper decay lengths and masses. This search is the first CMS search that shows sensitivity to hadronically decaying long-lived particles from signals with mass differences between the gluino and neutralino below 100 GeV. It sets the most stringent limits to date for split-SUSY models and gauge-mediated SUSY breaking models with gluino proper decay length less than 6 mm.
Distributions of $S_{\mathrm{ML}}$ for data, simulated background and signal events with $n_{\mathrm{track}}$ of 3. The distributions are shown for split-SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1900 GeV. Different gluino proper decay lengths are shown as $c\tau$ in the legend. All distributions are normalized to unity.
Distributions of $S_{\mathrm{ML}}$ for data, simulated background and signal events with $n_{\mathrm{track}}$ of 3. The distributions are shown for split-SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1800 GeV. Different gluino proper decay lengths are shown as $c\tau$ in the legend. All distributions are normalized to unity.
Distributions of $S_{\mathrm{ML}}$ for data, simulated background and signal events with $n_{\mathrm{track}}$ of 4. The distributions are shown for split-SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1900 GeV. Different gluino proper decay lengths are shown as $c\tau$ in the legend. All distributions are normalized to unity.
Distributions of $S_{\mathrm{ML}}$ for data, simulated background and signal events with $n_{\mathrm{track}}$ of 4. The distributions are shown for split-SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1800 GeV. Different gluino proper decay lengths are shown as $c\tau$ in the legend. All distributions are normalized to unity.
Distributions of $S_{\mathrm{ML}}$ for data, simulated background and signal events with $n_{\mathrm{track}}$ of $\geq$ 5. The distributions are shown for split-SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1900 GeV. Different gluino proper decay lengths are shown as $c\tau$ in the legend. All distributions are normalized to unity.
Distributions of $S_{\mathrm{ML}}$ for data, simulated background and signal events with $n_{\mathrm{track}}$ of $\geq$ 5. The distributions are shown for split-SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1800 GeV. Different gluino proper decay lengths are shown as $c\tau$ in the legend. All distributions are normalized to unity.
The distribution of $n_{\mathrm{track}}$ in different $S_{\mathrm{ML}}$ regions for simulated background events. Events with 0 $ < S_{\mathrm{ML}} < $ 0.2 (blue), 0.2 $ < S_{\mathrm{ML}} < $ 0.6 (red), and 0.6 $ < S_{\mathrm{ML}} < $ 1.0 (green) are compared. All distributions are normalized to unity. The similar $n_{\mathrm{track}}$ distributions demonstrate that $n_{\mathrm{track}}$ and $S_{\mathrm{ML}}$ are decorrelated.
The distribution of $d_{\mathrm{BV}}$ in $K_{\mathrm{S}}^{\mathrm{0}}$ vertices in data (black) and simulation (purple). The lower panel shows the ratio between data and simulation.
The vertex reconstruction efficiency for artificially displaced vertices in data (black) and simulation (red). In this example, the artificially displaced vertices are corrected to mimic split-SUSY signal events with gluino mass of 2000 GeV and neutralino mass of 1800 GeV.
The ML tagging efficiency for artificially displaced vertices in data (black) and simulation (red). In this example, the artificially displaced vertices are corrected to mimic split-SUSY signal events with gluino mass of 2000 GeV and neutralino mass of 1800 GeV.
Number of predicted and observed events in the control, validation, and search regions. Predictions are calculated using Eqs. (2) and (3) and fitting the data under the background-only hypothesis. Regions are organized by $S_{\mathrm{ML}}$ and $n_{\mathrm{track}}$ values, and region names corresponding with Fig. 7 are given in parentheses. The predicted number of events that pass the $S_{\mathrm{ML}}$ selection and the observed number of events that pass or fail the $S_{\mathrm{ML}}$ selection are shown in seperate rows.
The 95% CL upper limit on the product of the cross section and branching fraction squared for the split-SUSY signal model with a mass splitting of 100 GeV, shown as a function of gluino mass and $c\tau$. The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the limit plot.
The 95% CL upper limit on the product of the cross section and branching fraction squared for the split-SUSY signal model with a mass splitting of 100 GeV, shown as a function of gluino mass and $c\tau$. The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the limit plot.
The 95% CL upper limit on the product of the cross section and branching fraction squared for the split-SUSY model with a $c\tau$ of 10 mm, shown as a function of gluino mass and mass splitting. The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the limit plot.
The 95% CL upper limit on the product of the cross section and branching fraction squared for the split-SUSY model with a $c\tau$ of 10 mm, shown as a function of gluino mass and mass splitting. The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the limit plot.
The 95% CL upper limit on the product of the cross section and branching fraction squared for the GMSB SUSY signal model, shown as a function of gluino mass and $c\tau$. The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the limit plot.
The 95% CL upper limit on the product of the cross section and branching fraction squared for the GMSB SUSY signal model, shown as a function of gluino mass and $c\tau$. The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the limit plot.
A search for a new $Z'$ gauge boson predicted by $L_{\mu}-L_{\tau}$ models, based on charged-current Drell-Yan production, $pp \rightarrow W^{\pm(*)} \rightarrow Z' \mu^{\pm} \nu \rightarrow \mu^{\pm}\mu^{\mp}\mu^{\pm}\nu$, is presented. The data sample used corresponds to an integrated luminosity of 140 fb$^{-1}$ of proton-proton collisions at $\sqrt{s} = 13$ TeV recorded by the ATLAS detector at the Large Hadron Collider. The search examines a final state of $3\mu$ plus large missing transverse momentum. Upper limits are set on the $Z'$ production cross-section times branching ratio in the mass range of 5-81 GeV. After combining with the previous $Z'$ search using the neutral-current Drell-Yan production with a $4\mu$ final state, the most stringent exclusion limits to date are achieved in the parameter space of the $Z'$ coupling strength and mass.
Observed and expected upper limits at 95% CL on the production cross-section times branching fraction of the process $pp\to W\to Z^{\prime}$ $\mu \nu \to \mu \mu \mu \nu$ as a function of $m_{Z^{\prime}}$.
Observed and expected upper limits at 95% CL on the coupling parameter $g_{Z^{\prime}}$ as a function of $m_{Z^{\prime}}$ from the statistical combination of the $3\mu$ and $4\mu$ channels.
Exclusion contour compared to the limits from the Neutrino Trident and the $B_{S}$ mixing experimental results.
Summary of observed and expected background yields in the SR after the likelihood fit under the background-only hypothesis.
An inclusive search for long-lived exotic particles (LLPs) decaying to final states with a pair of muons is presented. The search uses data corresponding to an integrated luminosity of 36.6 fb$^{-1}$ collected by the CMS experiment from the proton-proton collisions at $\sqrt{s}$ = 13.6 TeV in 2022, the first year of Run 3 of the CERN LHC. The experimental signature is a pair of oppositely charged muons originating from a common vertex spatially separated from the proton-proton interaction point by distances ranging from several hundred $\mu$m to several meters. The sensitivity of the search benefits from new triggers for displaced dimuons developed for Run 3. The results are interpreted in the framework of the hidden Abelian Higgs model, in which the Higgs boson decays to a pair of long-lived dark photons, and of an $R$-parity violating supersymmetry model, in which long-lived neutralinos decay to a pair of muons and a neutrino. The limits set on these models are the most stringent to date in wide regions of lifetimes for LLPs with masses larger than 10 GeV.
Efficiencies of the Run 2 and Run 3 displaced dimuon triggers as a function of $c\tau$ for the HAHM signal events with $m_{Z_D} = 20\ GeV$. The efficiency is defined as the fraction of simulated events that satisfy the requirements of the following sets of trigger paths: the Run 2 (2018) triggers (dashed black); the Run 3 (2022, L3) triggers (blue); the Run 3 (2022, L2) triggers (red); and the OR of all these triggers (Run 3 (2022), black). The lower panel shows the ratio of the overall Run 3 (2022) efficiency to the Run 2 (2018) efficiency.
Efficiencies of the various displaced dimuon trigger paths and their combination as a function of $c\tau$ for the HAHM signal events with $m(Z_D) = 20\ GeV$. The efficiency is defined as the fraction of simulated events that satisfy the detector acceptance and the requirements of the following sets of trigger paths: the Run 2 (2018) triggers (dashed black); the Run 3 (2022, L3) triggers (blue); the Run 3 (2022, L2) triggers (red); and the OR of all these triggers (Run 3 (2022), black). The lower panel shows the ratio of the overall Run 3 (2022) efficiency to the Run 2 (2018) efficiency.
Efficiencies in the STA-STA (green) and TMS-TMS (red) dimuon categories, as well as their combination (black) as a function of $c\tau$ for the HAHM signal events with $m_{Z_D} = 20\ GeV$. Solid curves show efficiencies achieved with the Run 3 triggers, whereas dashed curves show efficiencies for the subset of events selected by the triggers used in the 2018 Run 2 analysis. The efficiency is defined as the fraction of signal events that satisfy the criteria of the indicated trigger as well as the full set of offline selection criteria. The lower panel shows the relative improvement of the overall signal efficiency brought in by improvements in the trigger.
Overall efficiencies in the STA-STA (green) and TMS-TMS (red) dimuon categories, as well as their combination (black) as a function of $c\tau$ for the HAHM signal events with $m(Z_D) = 20\ GeV$. The solid curves show efficiencies achieved with the 2022 Run 3 triggers, whereas dashed curves show efficiencies for the subset of events selected by the triggers used in the 2018 Run 2 analysis. The efficiency is defined as the fraction of signal events that satisfy the criteria of the indicated trigger as well as the full set of offline selection criteria. The lower panel shows the relative improvement of the overall signal efficiency brought in by improvements in the trigger.
Comparison of the observed (black points) and expected (histograms) numbers of events in nonoverlapping $m_{\mu \mu}$ intervals in the STA-STA dimuon category, in the signal region optimized for the HAHM model. Yellow and green stacked histograms represent mean expected background contributions from QCD and DY, respectively, while statistical uncertainties in the total expected background are shown as hatched histograms. Signal contributions expected from simulated signals indicated in the legends are shown in red and blue. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow. All uncertainties shown are statistical only.
Comparison of the observed (black points) and expected (histograms) numbers of events in nonoverlapping $m_{\mu \mu}$ intervals in the STA-STA dimuon category, in the signal region optimized for the HAHM model. Yellow and green stacked filled histograms represent mean expected background contributions from QCD and DY, respectively, while statistical uncertainties in the total expected background are shown as hatched histograms. Signal contributions expected from simulated signals indicated in the legends are shown in red and blue. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.
Comparison of the observed (black points) and expected (histograms) numbers of events in nonoverlapping $m^{corr}_{\mu\mu}$ intervals in the STA-STA dimuon category, in the signal region optimized for the RPV SUSY model. Yellow and green stacked histograms represent mean expected background contributions from QCD and DY, respectively, while statistical uncertainties in the total expected background are shown as hatched histograms. Signal contributions expected from simulated signals indicated in the legends are shown in red and blue. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow. All uncertainties shown are statistical only.
Comparison of the observed (black points) and expected (histograms) numbers of events in nonoverlapping $m^{corr}_{\mu\mu}$ intervals in the STA-STA dimuon category, in the signal region optimized for the RPV SUSY model. Yellow and green stacked filled histograms represent mean expected background contributions from QCD and DY, respectively, while statistical uncertainties in the total expected background are shown as hatched histograms. Signal contributions expected from simulated signals indicated in the legends are shown in red and blue. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.
Distribution of min($d_0 / \sigma_{d_0}$) for TMS-TMS dimuons with $|\Delta\Phi| < \pi/30$, for events in all mass intervals combined. Events are required to satisfy all nominal selection criteria with the exception of the $d_0 / \sigma_{d_0}$ requirement. Notations are as in the Fig. 10 caption.
Distribution of min($d_0 / \sigma_{d_0}$) for TMS-TMS dimuons with $|\Delta\Phi| < \pi/30$, for events in all mass intervals combined, for both the validation (min($d_0 / \sigma_{d_0}$) < 6) and signal (min($d_0 / \sigma_{d_0}$) > 6) regions. The number of observed events (black circles) is overlaid with the stacked histograms showing the expected numbers of QCD (yellow) and DY (green) background events. Statistical uncertainties in the total expected background are shown as hatched histograms. Signal contributions expected from simulated signals indicated in the legends are shown in red and blue. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. Events are required to satisfy all nominal selection criteria with the exception of the $d_0 / \sigma_{d_0}$ requirement. The last bin includes events in the histogram overflow.
Distribution of min($d_0 / \sigma_{d_0}$) for TMS-TMS dimuons with $|\Delta\Phi| < \pi/4$, for events in all mass intervals combined. Events are required to satisfy all nominal selection criteria with the exception of the $d_0 / \sigma_{d_0}$ requirement. Notations are as in the Fig. 10 caption.
Distribution of min($d_0 / \sigma_{d_0}$) for TMS-TMS dimuons with $|\Delta\Phi| < \pi/4$, for events in all mass intervals combined, for both the validation (min($d_0 / \sigma_{d_0}$) < 6) and signal (min($d_0 / \sigma_{d_0}$) > 6) regions. The number of observed events (black circles) is overlaid with the stacked histograms showing the expected numbers of QCD (yellow) and DY (green) background events. Statistical uncertainties in the total expected background are shown as hatched histograms. Signal contributions expected from simulated signals indicated in the legends are shown in red and blue. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. Events are required to satisfy all nominal selection criteria with the exception of the $d_0 / \sigma_{d_0}$ requirement. The last bin includes events in the histogram overflow.
Comparison of observed and expected numbers of events in the TMS-TMS dimuon category, in the RPV SUSY study that requires $|\Delta\Phi| < \pi/4$, in bins of $m^{corr}_{\mu\mu}$. The number of observed events (black circles) is overlaid with the stacked histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m^{corr}_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: 6-10. Contributions expected from signal events predicted by the RPV SUSY model with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow. All uncertainties shown are statistical only.
Comparison of observed and expected numbers of events in bins of $m^{corr}_{\mu\mu}$ in the TMS-TMS dimuon category, in the signal regions optimized for the RPV SUSY model. The number of observed events (black circles) is overlaid with the stacked filled histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m^{corr}_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: 6-10. Hatched histograms show statistical uncertainties in the total expected background. Contributions expected from signal events predicted by the RPV SUSY model with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.
Comparison of observed and expected numbers of events in the TMS-TMS dimuon category, in the RPV SUSY study that requires $|\Delta\Phi| < \pi/4$, in bins of $m^{corr}_{\mu\mu}$. The number of observed events (black circles) is overlaid with the stacked histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m^{corr}_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: 10-20. Contributions expected from signal events predicted by the RPV SUSY model with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow. All uncertainties shown are statistical only.
Comparison of observed and expected numbers of events in bins of $m^{corr}_{\mu\mu}$ in the TMS-TMS dimuon category, in the signal regions optimized for the RPV SUSY model. The number of observed events (black circles) is overlaid with the stacked filled histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m^{corr}_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: 10-20. Hatched histograms show statistical uncertainties in the total expected background. Contributions expected from signal events predicted by the RPV SUSY model with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.
Comparison of observed and expected numbers of events in the TMS-TMS dimuon category, in the RPV SUSY study that requires $|\Delta\Phi| < \pi/4$, in bins of $m^{corr}_{\mu\mu}$. The number of observed events (black circles) is overlaid with the stacked histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m^{corr}_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: > 20. Contributions expected from signal events predicted by the RPV SUSY model with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow. All uncertainties shown are statistical only.
Comparison of observed and expected numbers of events in bins of $m^{corr}_{\mu\mu}$ in the TMS-TMS dimuon category, in the signal regions optimized for the RPV SUSY model. The number of observed events (black circles) is overlaid with the stacked filled histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m^{corr}_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: >20. Hatched histograms show statistical uncertainties in the total expected background. Contributions expected from signal events predicted by the RPV SUSY model with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.
Comparison of observed and expected numbers of events in the TMS-TMS dimuon category, in the HAHM study that requires $|\Delta\Phi| < \pi/30$, in bins of $m_{\mu\mu}$. The number of observed events (black circles) is overlaid with the stacked histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: 6-10. Signal contributions expected from simulated $H \rightarrow Z_DZ_D$ events with the parameters indicated in the legends are shown as red and blue histograms. Other notations are as in the Fig. 12 caption.
Comparison of observed and expected numbers of events in bins of $m_{\mu\mu}$ in the TMS-TMS dimuon category, in the signal regions optimized for the HAHM. The number of observed events (black circles) is overlaid with the stacked filled histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: 6-10. Hatched histograms show statistical uncertainties in the total expected background. Signal contributions expected from simulated $H \rightarrow Z_DZ_D$ events with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.
Comparison of observed and expected numbers of events in the TMS-TMS dimuon category, in the HAHM study that requires $|\Delta\Phi| < \pi/30$, in bins of $m_{\mu\mu}$. The number of observed events (black circles) is overlaid with the stacked histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: 10-20. Signal contributions expected from simulated $H \rightarrow Z_DZ_D$ events with the parameters indicated in the legends are shown as red and blue histograms. Other notations are as in the Fig. 12 caption.
Comparison of observed and expected numbers of events in bins of $m_{\mu\mu}$ in the TMS-TMS dimuon category, in the signal regions optimized for the HAHM. The number of observed events (black circles) is overlaid with the stacked filled histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: 10-20. Hatched histograms show statistical uncertainties in the total expected background. Signal contributions expected from simulated $H \rightarrow Z_DZ_D$ events with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.
Comparison of observed and expected numbers of events in the TMS-TMS dimuon category, in the HAHM study that requires $|\Delta\Phi| < \pi/30$, in bins of $m_{\mu\mu}$. The number of observed events (black circles) is overlaid with the stacked histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: > 20. Signal contributions expected from simulated $H \rightarrow Z_DZ_D$ events with the parameters indicated in the legends are shown as red and blue histograms. Other notations are as in the Fig. 12 caption.
Comparison of observed and expected numbers of events in bins of $m_{\mu\mu}$ in the TMS-TMS dimuon category, in the signal regions optimized for the HAHM. The number of observed events (black circles) is overlaid with the stacked filled histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: >20. Hatched histograms show statistical uncertainties in the total expected background. Signal contributions expected from simulated $H \rightarrow Z_DZ_D$ events with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 10\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 10\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 20\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 20\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 30\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 30\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 40\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 40\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 50\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 50\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 60\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 60\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 10\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 10\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 20\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 20\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 30\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 30\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 40\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 40\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 50\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 50\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 60\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 60\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.
The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 125\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The predicted cross section for $m(\tilde{q}) = 125\ GeV$ is 7200 pb, and falls outside the y-axis range.
The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 125\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The predicted cross section for $m(\tilde{q}) = 125\ GeV$ is 7200 pb, and falls outside the y-axis range.
The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 200\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The predicted cross section for $m(\tilde{q}) = 200 GeV$ is 840 pb, and falls outside the y-axis range.
The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 200\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The predicted cross section for $m(\tilde{q}) = 200 GeV$ is 840 pb, and falls outside the y-axis range.
The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 350\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The predicted cross section for $m(\tilde{q}) = 350\ GeV$ is 50 pb, and falls outside the y-axis range.
The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 350\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The predicted cross section for $m(\tilde{q}) = 350\ GeV$ is 50 pb, and falls outside the y-axis range.
The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 700\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The gray horizontal line indicates the theoretical value of the squark-antisquark production cross section with the uncertainties shown as the gray shaded band.
The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 700\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The gray horizontal line indicates the theoretical value of the squark-antisquark production cross section with the uncertainties shown as the gray shaded band.
The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 1150\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The gray horizontal line indicates the theoretical value of the squark-antisquark production cross section with the uncertainties shown as the gray shaded band.
The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 1150\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The gray horizontal line indicates the theoretical value of the squark-antisquark production cross section with the uncertainties shown as the gray shaded band.
The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 1600\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The gray horizontal line indicates the theoretical value of the squark-antisquark production cross section with the uncertainties shown as the gray shaded band.
The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 1600\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The gray horizontal line indicates the theoretical value of the squark-antisquark production cross section with the uncertainties shown as the gray shaded band.
Fractions of signal events with zero (green), one (blue), and two (red) STA muons matched to TMS muons by the STA to TMS association procedure, as a function of generated $L_{xy}$, in all HAHM signal samples combined.
Efficiencies of the Run 2 and Run 3 displaced dimuon triggers as a function of $c\tau$ for the HAHM signal events with $m(Z_D) = 50\ GeV$. The efficiency is defined as the fraction of simulated events that satisfy the requirements of the following sets of trigger paths: the Run 2 (2018) triggers (dashed black); the Run 3 (2022, L3) triggers (blue); the Run 3 (2022, L2) triggers (red); and the OR of all these triggers (Run 3 (2022), black). The lower panel shows the ratio of the overall Run 3 (2022) efficiency to the Run 2 (2018) efficiency.
Efficiencies of the Run 2 (2018) (red) and Run 3 (2022) (black) sets of displaced dimuon triggers as a function of $m(Z_D)$ for the HAHM signal events with $c\tau = 1\ cm$. The efficiency is defined as the fraction of simulated events that satisfy the detector acceptance and the requirements of the indicated set of trigger paths. The lower panel shows the ratio of the Run 3 (2022) efficiency to the Run 2 (2018) efficiency.
Efficiencies of the Run 2 (2018) (red) and Run 3 (2022) (black) sets of displaced dimuon triggers as a function of $m(Z_D)$ for the HAHM signal events with $c\tau = 10\ m$. The efficiency is defined as the fraction of simulated events that satisfy the detector acceptance and the requirements of the indicated set of trigger paths. The lower panel shows the ratio of the Run 3 (2022) efficiency to the Run 2 (2018) efficiency.
Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM signal with $m(Z_D) = 20\ GeV$ in different years of data taking. Efficiencies are computed as the ratios of the number of simulated signal events in which at least one dimuon candidate passes all 2016 (dashed green), 2018 (dashed red), and 2022 (solid black) trigger and offline selection criteria to the total number of simulated signal events. The lower panel shows the ratio of the 2022 efficiency to the 2018 efficiency (dashed red) and to the 2016 efficiency (dashed green).
Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM signal with $m(Z_D) = 50\ GeV$ in different years of data taking. Efficiencies are computed as the ratios of the number of simulated signal events in which at least one dimuon candidate passes all 2016 (dashed green), 2018 (dashed red), and 2022 (solid black) trigger and offline selection criteria to the total number of simulated signal events. The lower panel shows the ratio of the 2022 efficiency to the 2018 efficiency (dashed red) and to the 2016 efficiency (dashed green).
Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM model with $m(Z_D) = 10\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM model with $m(Z_D) = 20\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM model with $m(Z_D) = 30\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM model with $m(Z_D) = 40\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM model with $m(Z_D) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM model with $m(Z_D) = 60\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 125\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 200\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 350\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 700\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 1150\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 1600\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 700\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 500\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 1150\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 500\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 1600\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 500\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.
Signal efficiencies in the TMS-TMS dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ smaller than 20 cm in the HAHM signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.
Signal efficiencies in the STA-STA dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ smaller than 20 cm in the HAHM signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.
Signal efficiencies in the TMS-TMS dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ 20-70 cm in the HAHM signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.
Signal efficiencies in the STA-STA dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ 20-70 cm in the HAHM signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.
Signal efficiencies in the STA-STA dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ 70-500 cm in the HAHM signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.
Signal efficiencies in the TMS-TMS dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ smaller than 20 cm in the RPV SUSY signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.
Signal efficiencies in the STA-STA dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ smaller than 20 cm in the RPV SUSY signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.
Signal efficiencies in the TMS-TMS dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ 20-70 cm in the RPV SUSY signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.
Signal efficiencies in the STA-STA dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ 20-70 cm in the RPV SUSY signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.
Signal efficiencies in the STA-STA dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ 70-500 cm in the RPV SUSY signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.
Energy correlators that describe energy-weighted distances between two or three particles in a jet are measured using an event sample of $\sqrt{s}$ = 13 TeV proton-proton collisions collected by the CMS experiment and corresponding to an integrated luminosity of 36.3 fb$^{-1}$. The measured distributions reveal two key features of the strong interaction: confinement and asymptotic freedom. By comparing the ratio of the two measured distributions with theoretical calculations that resum collinear emissions at approximate next-to-next-to-leading logarithmic accuracy matched to a next-to-leading order calculation, the strong coupling is determined at the Z boson mass: $\alpha_\mathrm{S}(m_\mathrm{Z})$ = 0.1229$^{+0.0040}_{-0.0050}$, the most precise $\alpha_\mathrm{S}(m_\mathrm{Z})$ value obtained using jet substructure observables.
Unfolded E2C distributions in data compared to MC predictions.
Unfolded E2C distributions in data compared to MC predictions.
Unfolded E2C distributions in data compared to MC predictions.
Unfolded E2C distributions in data compared to MC predictions.
Unfolded E2C distributions in data compared to MC predictions.
Unfolded E2C distributions in data compared to MC predictions.
Unfolded E2C distributions in data compared to MC predictions.
Unfolded E2C distributions in data compared to MC predictions.
Unfolded E3C distributions in data compared to MC predictions.
Unfolded E3C distributions in data compared to MC predictions.
Unfolded E3C distributions in data compared to MC predictions.
Unfolded E3C distributions in data compared to MC predictions.
Unfolded E3C distributions in data compared to MC predictions.
Unfolded E3C distributions in data compared to MC predictions.
Unfolded E3C distributions in data compared to MC predictions.
Unfolded E3C distributions in data compared to MC predictions.
Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.
Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.
Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.
Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.
Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.
Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.
Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.
Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.
The fitted slopes of the E3C/E2C data distributions as a function of jet pt are used to illustrate the dependency of alphas on jet pt.
Unfolded E3C/E2C distributions in data compared to MC predictions.
Unfolded E3C/E2C distributions in data compared to MC predictions.
Unfolded E3C/E2C distributions in data compared to MC predictions.
Unfolded E3C/E2C distributions in data compared to MC predictions.
Unfolded E3C/E2C distributions in data compared to MC predictions.
Unfolded E3C/E2C distributions in data compared to MC predictions.
Unfolded E3C/E2C distributions in data compared to MC predictions.
Unfolded E3C/E2C distributions in data compared to MC predictions.
The chi2 scan result using eq.3 for different alphas.
The correlation matrix is composed by 10 jet pt region, each region is represented by a block in the plot. Inside each block, there are 22 xL bins same as the E2C, E3C and E3C/E2C distributions. Therefore, the x and y bins of the correlation matrix is given by, binNumber = pT_index * 22 + xL_index.
The correlation matrix is composed by 10 jet pt region, each region is represented by a block in the plot. Inside each block, there are 22 xL bins same as the E2C, E3C and E3C/E2C distributions. Therefore, the x and y bins of the correlation matrix is given by, binNumber = pT_index * 22 + xL_index.
The correlation matrix is composed by 10 jet pt region, each region is represented by a block in the plot. Inside each block, there are 22 xL bins same as the E2C, E3C and E3C/E2C distributions. Therefore, the x and y bins of the correlation matrix is given by, binNumber = pT_index * 22 + xL_index.
The energy weight of E2C as defined in eq.1 in the paper is used in the unfolding, the binning is listed in this table.
The energy weight of E3C as defined in eq.1 in the paper is used in the unfolding, the binning is listed in this table.
A search is described for the production of a pair of bottom-type vector-like quarks (B VLQs) with mass greater than 1000 GeV. Each B VLQ decays into a b quark and a Higgs boson, a b quark and a Z boson, or a t quark and a W boson. This analysis considers both fully hadronic final states and those containing a charged lepton pair from a Z boson decay. The products of the H $to$ bb boson decay and of the hadronic Z or W boson decays can be resolved as two distinct jets or merged into a single jet, so the final states are classified by the number of reconstructed jets. The analysis uses data corresponding to an integrated luminosity of 138 fb$^{-1}$ collected in proton-proton collisions at $\sqrt{s}$ = 13 TeV with the CMS detector at the LHC from 2016 to 2018. No excess over the expected background is observed. Lower limits are set on the B VLQ mass at 95% confidence level. These depend on the B VLQ branching fractions and are 1570 and 1540 GeV for 100% B $\to$ bH and 100% B $\to$ bZ, respectively. In most cases, the mass limits obtained exceed previous limits by at least 100 GeV.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 4-jet bHbH channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 4-jet bHbZ channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 4-jet bZbZ channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bHbH channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bHbZ channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bZbZ channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bHtW channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bZtW channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bHbH channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bHbZ channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bZbZ channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bHtW channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bZtW channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the semileptonic 3-jet bHbZ channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the semileptonic 3-jet bZbZ channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the semileptonic 4-jet bHbZ channel.
Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the semileptonic 4-jet bZbZ channel.
The limit at 95% CL on the cross section for VLQ pair production for the branching fraction hypothesis 0% $\mathcal{B}(B \to bH)$, 100% $\mathcal{B}(B \to bH)$, and 0% $\mathcal{B}(B \to bH)$
The limit at 95% CL on the cross section for VLQ pair production for the branching fraction hypothesis 25% $\mathcal{B}(B \to bH)$, 25% $\mathcal{B}(B \to bH)$, and 50% $\mathcal{B}(B \to bH)$
The limit at 95% CL on the cross section for VLQ pair production for the branching fraction hypothesis 50% $\mathcal{B}(B \to bH)$, 50% $\mathcal{B}(B \to bH)$, and 0% $\mathcal{B}(B \to bH)$
The limit at 95% CL on the cross section for VLQ pair production for the branching fraction hypothesis 100% $\mathcal{B}(B \to bH)$, 0% $\mathcal{B}(B \to bH)$, and 0% $\mathcal{B}(B \to bH)$
Median expected exclusion limits on the VLQ mass at 95% CL as a function of the branching fractions $\mathcal{B}(B \to bH)$ and $\mathcal{B}(B \to tW)$, with $\mathcal{B}(B \to tW) = 1 - \mathcal{B}(B \to bH) - \mathcal{B}(B \to bZ)$. The grey area corresponds to the region where the exclusion limit is less than 1000 GeV.
Median observed exclusion limits on the VLQ mass at 95% CL as a function of the branching fractions $\mathcal{B}(B \to bH)$ and $\mathcal{B}(B \to tW)$, with $\mathcal{B}(B \to tW) = 1 - \mathcal{B}(B \to bH) - \mathcal{B}(B \to bZ)$. The grey area corresponds to the region where the exclusion limit is less than 1000 GeV.
A search for exotic decays of the Higgs boson (H) with a mass of 125 GeV to a pair of light pseudoscalars $\mathrm{a}_1$ is performed in final states where one pseudoscalar decays to two b quarks and the other to a pair of muons or $\tau$ leptons. A data sample of proton-proton collisions at $\sqrt{s}$ = 13 TeV corresponding to an integrated luminosity of 138 fb$^{-1}$ recorded with the CMS detector is analyzed. No statistically significant excess is observed over the standard model backgrounds. Upper limits are set at 95% confidence level (CL) on the Higgs boson branching fraction to $\mu\mu$bb and to $\tau\tau$bb, via a pair of $\mathrm{a}_1$s. The limits depend on the pseudoscalar mass $m_{\mathrm{a}_1}$ and are observed to be in the range (0.17-3.3) $\times$ 10$^{-4}$ and (1.7-7.7) $\times$ 10$^{-2}$ in the $\mu\mu$bb and $\tau\tau$bb final states, respectively. In the framework of models with two Higgs doublets and a complex scalar singlet (2HDM+S), the results of the two final states are combined to determine model-independent upper limits on the branching fraction $\mathcal{B}$(H $\to$ $\mathrm{a}_1\mathrm{a}_1$ $\to$ $\ell\ell$bb) at 95% CL, with $\ell$ being a muon or a $\tau$ lepton. For different types of 2HDM+S, upper bounds on the branching fraction $\mathcal{B}$(H $\to$ $\mathrm{a}_1\mathrm{a}_1$) are extracted from the combination of the two channels. In most of the Type II 2HDM+S parameter space, $\mathcal{B}($H $\to$ $\mathrm{a}_1\mathrm{a}_1$) values above 0.23 are excluded at 95% CL for $m_{\mathrm{a}_1}$ values between 15 and 60 GeV.
Observed and expected upper limits at 95% CL on B($\text{H} \rightarrow \text{a}_{1}\text{a}_{1} \rightarrow \mu\mu$bb) as functions of $m_{\text{a}_{1}}$. The inner and outer bands indicate the regions containing the distribution of limits located within 68 and 95% confidence intervals, respectively, of the expectation under the background-only hypothesis.
Observed and expected upper limits at 95% CL on B($\text{H} \rightarrow \text{a}_{1}\text{a}_{1} \rightarrow \tau\tau$bb) in percent as functions of $m_{\text{a}_{1}}$, for the combination of the $\mu\tau_{\text{h}}$, $e\tau_{\text{h}}$, and $e\mu$ channels. The inner and outer bands indicate the regions containing the distribution of limits located within 68 and 95% confidence intervals, respectively, of the expectation under the background-only hypothesis.
Observed and expected upper limits at 95% CL on B($\text{H} \rightarrow \text{a}_{1}\text{a}_{1} \rightarrow ll$bb) in percent, where $l$ stands for muons or $\tau$ leptons, obtained from the combination of the $\mu\mu$bb and $\tau\tau$bb channels. The results are obtained as functions $m_{\text{a}_{1}}$ for 2HDM+S models, independent of the type and tan $\beta$ parameter. The inner and outer bands indicate the regions containing the distribution of limits located within 68 and 95% confidence intervals, respectively, of the expectation under the background-only hypothesis.
Observed upper limits at 95% CL on B($\text{H} \rightarrow \text{a}_{1}\text{a}_{1}$) in percent, obtained from the combination of the $\mu\mu$bb and $\tau\tau$bb channels. The results are obtained as functions of $m_{\text{a}_{1}}$ for 2HDM+S Type I (independent of tan$\beta$), Type II (tan$\beta$=2.0), Type III (tan$\beta$=2.0), and Type IV (tan$\beta$=0.6), respectively.
This Letter presents a differential cross-section measurement of Lund subjet multiplicities, suitable for testing current and future parton shower Monte Carlo algorithms. This measurement is made in dijet events in 140 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collision data collected with the ATLAS detector at CERN's Large Hadron Collider. The data are unfolded to account for acceptance and detector-related effects, and are then compared with several Monte Carlo models and to recent resummed analytical calculations. The experimental precision achieved in the measurement allows tests of higher-order effects in QCD predictions. Most predictions fail to accurately describe the measured data, particularly at large values of jet transverse momentum accessible at the Large Hadron Collider, indicating the measurement's utility as an input to future parton shower developments and other studies probing fundamental properties of QCD and the production of hadronic final states up to the TeV-scale.
$N_{Lund}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}, k_t \geq 0.5~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 0.5~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 0.5~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 0.5~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 0.5~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}, k_t \geq 1.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 1.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 1.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 1.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 1.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}, k_t \geq 2.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 2.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 2.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 2.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 2.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}, k_t \geq 5.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 5.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 5.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 5.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 5.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}, k_t \geq 10.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 10.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 10.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 10.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 10.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}, k_t \geq 20.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 20.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 20.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 20.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 20.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}, k_t \geq 50.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 50.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 50.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 50.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 50.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}, k_t \geq 100.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 100.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}, k_t \geq 100.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins, Central $\eta$
$N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$
$N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$\lt N_{Lund} \gt$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$\lt N_{Lund} \gt$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Central $\eta$
$\lt N_{Lund} \gt$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Forward $\eta$
$\lt N_{Lund} \gt$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$\lt N_{Lund} \gt$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Central $\eta$
$\lt N_{Lund} \gt$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Forward $\eta$
$\lt N_{Lund} \gt$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$\lt N_{Lund} \gt$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Central $\eta$
$\lt N_{Lund} \gt$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Forward $\eta$
$\lt N_{Lund} \gt$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$\lt N_{Lund} \gt$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Central $\eta$
$\lt N_{Lund} \gt$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Forward $\eta$
$\lt N_{Lund} \gt$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$\lt N_{Lund} \gt$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Central $\eta$
$\lt N_{Lund} \gt$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Forward $\eta$
$\lt N_{Lund}^{Primary} \gt$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$
$\lt N_{Lund}^{Primary} \gt$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Central $\eta$
$\lt N_{Lund}^{Primary} \gt$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Forward $\eta$
$\lt N_{Lund}^{Primary} \gt$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$
$\lt N_{Lund}^{Primary} \gt$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Central $\eta$
$\lt N_{Lund}^{Primary} \gt$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Forward $\eta$
$\lt N_{Lund}^{Primary} \gt$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$
$\lt N_{Lund}^{Primary} \gt$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Central $\eta$
$\lt N_{Lund}^{Primary} \gt$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Forward $\eta$
$\lt N_{Lund}^{Primary} \gt$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$
$\lt N_{Lund}^{Primary} \gt$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Central $\eta$
$\lt N_{Lund}^{Primary} \gt$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Forward $\eta$
$\lt N_{Lund}^{Primary} \gt$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$
$\lt N_{Lund}^{Primary} \gt$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Central $\eta$
$\lt N_{Lund}^{Primary} \gt$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Forward $\eta$
Inclusive $\lt N_{Lund} \gt$
Inclusive $\lt N_{Lund}^{Primary} \gt$
Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$
MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$
A search for beyond the standard model spin-0 bosons, $\phi$, that decay into pairs of electrons, muons, or tau leptons is presented. The search targets the associated production of such bosons with a W or Z gauge boson, or a top quark-antiquark pair, and uses events with three or four charged leptons, including hadronically decaying tau leptons. The proton-proton collision data set used in the analysis was collected at the LHC from 2016 to 2018 at a center-of-mass energy of 13 TeV, and corresponds to an integrated luminosity of 138 fb$^{-1}$. The observations are consistent with the predictions from standard model processes. Upper limits are placed on the product of cross sections and branching fractions of such new particles over the mass range of 15 to 350 GeV with scalar, pseudoscalar, or Higgs-boson-like couplings, as well as on the product of coupling parameters and branching fractions. Several model-dependent exclusion limits are also presented. For a Higgs-boson-like $\phi$ model, limits are set on the mixing angle of the Higgs boson with the $\phi$ boson. For the associated production of a $\phi$ boson with a top quark-antiquark pair, limits are set on the coupling to top quarks. Finally, limits are set for the first time on a fermiophilic dilaton-like model with scalar couplings and a fermiophilic axion-like model with pseudoscalar couplings.
Cross sections for the W$\phi$, Z$\phi$, and $t\bar{t}\phi$ signal models as a function of the $\phi$ boson mass in GeV. All cross sections are inclusive of all W, Z, $t\bar{t}$ and $\phi$ decay modes.
Binned representation of the control and signal regions for the combined multilepton event selection and the combined 2016–2018 data set. The control region bins follow their definitions as given in Table 1 of the paper, and the signal region bins correspond to the channels as defined by the lepton flavor composition. The normalizations of the background samples in the control regions are described in Sections 5.1 and 5.2 of the paper. All three (four) lepton events are required to have $\mathrm{Q_{\ell}=1 (0)}$, and those satisfying any of the control region requirements are removed from the signal region bins. All subsequent selections given in Tables 2 and 3 of the paper are based on events given in the signal region bins. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the statistical uncertainties in the background prediction.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $t\bar{t} \phi$ Scalar with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The $M_{OSSF}$ spectrum for the combined 2L1T, 2L2T, 3L, 3L1T, and 4L event selection (excluding the $\mathrm{Z\gamma}$ control region) and the combined 2016-2018 data set. All three (four) lepton events are required to have $\mathrm{Q_{\ell}=1 (0)}$. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the statistical uncertainties in the background prediction.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $t\bar{t} \phi$ Scalar with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the low mass $W\phi($ee$)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $t\bar{t} \phi$ Scalar with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the high mass $W\phi($ee$)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $t\bar{t} \phi$ Pseudoscalar with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the low mass $W\phi($ee$)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $t\bar{t} \phi$ Pseudoscalar with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the high mass $W\phi($ee$)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $t\bar{t} \phi$ Pseudoscalar with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the low mass $Z\phi($ee$)$ SR event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $W\phi$ Scalar with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the high mass $Z\phi($ee$)$ SR event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $W\phi$ Scalar with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the low mass $t\bar{t}\phi($ee$)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $W\phi$ Scalar with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the high mass $t\bar{t}\phi($ee$)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $W\phi$ Pseudoscalar with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the low mass $t\bar{t}\phi($ee$)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $W\phi$ Pseudoscalar with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the high mass $t\bar{t}\phi($ee$)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $W\phi$ Pseudoscalar with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the low mass $t\bar{t}\phi($ee$)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $W\phi$ Higgs-like with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the high mass $t\bar{t}\phi($ee$)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $W\phi$ Higgs-like with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the low mass $W\phi(\mu\mu)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $W\phi$ Higgs-like with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the high mass $W\phi(\mu\mu)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $Z\phi$ Scalar with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the low mass $W\phi(\mu\mu)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $Z\phi$ Scalar with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the high mass $W\phi(\mu\mu)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $Z\phi$ Scalar with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the low mass $Z\phi(\mu\mu)$ SR event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $Z\phi$ Pseudoscalar with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the high mass $Z\phi(\mu\mu)$ SR event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $Z\phi$ Pseudoscalar with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the low mass $t\bar{t}\phi(\mu\mu)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $Z\phi$ Pseudoscalar with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the high mass $t\bar{t}\phi(\mu\mu)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $Z\phi$ Higgs-like with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the low mass $t\bar{t}\phi(\mu\mu)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $Z\phi$ Higgs-like with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the high mass $t\bar{t}\phi(\mu\mu)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $Z\phi$ Higgs-like with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the low mass $t\bar{t}\phi(\mu\mu)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $t\bar{t} \phi (ee)$ Scalar with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the high mass $t\bar{t}\phi(\mu\mu)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $t\bar{t} \phi (\mu\mu)$ Scalar with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $W\phi(\tau\tau)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $t\bar{t} \phi (\tau\tau)$ Scalar with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $Z\phi(\tau\tau)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $t\bar{t} \phi (ee)$ Pseudoscalar with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $W\phi(\tau\tau)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $t\bar{t} \phi (\mu\mu)$ Pseudoscalar with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $Z\phi(\tau\tau)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $t\bar{t} \phi (\tau\tau)$ PS with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $W\phi(\tau\tau)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $t\bar{t} \phi (ee)$ Higgs-like with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $Z\phi(\tau\tau)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $t\bar{t} \phi (\mu\mu)$ Higgs-like with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $t\bar{t} \phi (\tau\tau)$ H-like with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $W\phi (ee)$ Scalar with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $W\phi (\mu\mu)$ Scalar with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR4 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $W\phi (\tau\tau)$ Scalar with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR5 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $W\phi (ee)$ Pseudoscalar with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR6 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $W\phi (\mu\mu)$ Pseudoscalar with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR7 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $W\phi (\tau\tau)$ Pseudoscalar with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with scalar couplings in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $W\phi (ee)$ Higgs-like with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with pseudoscalar couplings in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $W\phi (\mu\mu)$ Higgs-like with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with scalar couplings in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $W\phi (\tau\tau)$ Higgs-like with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with pseudoscalar couplings in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $Z\phi (ee)$ Scalar with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with scalar couplings in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $Z\phi (\mu\mu)$ Scalar with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with pseudoscalar couplings in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $Z\phi (\tau\tau)$ Scalar with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with scalar couplings in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $Z\phi (ee)$ Pseudoscalar with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with pseudoscalar couplings in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $Z\phi (\mu\mu)$ Pseudoscalar with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with scalar couplings in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $Z\phi (\tau\tau)$ Pseudoscalar with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with pseudoscalar couplings in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $Z\phi (ee)$ Higgs-like with $\phi$ decaying into dielectron pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with scalar couplings in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $Z\phi (\mu\mu)$ Higgs-like with $\phi$ decaying into dimuon pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with pseudoscalar couplings in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.
Observed and expected upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $Z\phi (\tau\tau)$ Higgs-like with $\phi$ decaying into ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with H-like production in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.
Overlay of observed upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $t \bar{t} \phi$ Scalar with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding Limit on $\sigma B(ee)$, $\sigma B(\mu\mu)$ and $\sigma B(\tau\tau)$ plots.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with H-like production in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.
Overlay of observed upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $t \bar{t} \phi$ Pseudoscalar with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding Limit on $\sigma B(ee)$, $\sigma B(\mu\mu)$ and $\sigma B(\tau\tau)$ plots.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with H-like production in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.
Overlay of observed upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $W\phi$ Scalar with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding Limit on $\sigma B(ee)$, $\sigma B(\mu\mu)$ and $\sigma B(\tau\tau)$ plots.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with H-like production in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.
Overlay of observed upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $W\phi$ Pseudoscalar with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding Limit on $\sigma B(ee)$, $\sigma B(\mu\mu)$ and $\sigma B(\tau\tau)$ plots.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with H-like production in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.
Overlay of observed upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $W\phi$ Higgs-like with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding Limit on $\sigma B(ee)$, $\sigma B(\mu\mu)$ and $\sigma B(\tau\tau)$ plots.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with H-like production in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.
Overlay of observed upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $Z\phi$ Scalar with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding Limit on $\sigma B(ee)$, $\sigma B(\mu\mu)$ and $\sigma B(\tau\tau)$ plots.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal with scalar couplings in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal.
Overlay of observed upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $Z\phi$ Pseudoscalar with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding Limit on $\sigma B(ee)$, $\sigma B(\mu\mu)$ and $\sigma B(\tau\tau)$ plots.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal with pseudoscalar couplings in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal.
Overlay of observed upper limits at 95% CL on the product of the signal production cross section and branching fraction of the $Z\phi$ Higgs-like with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding Limit on $\sigma B(ee)$, $\sigma B(\mu\mu)$ and $\sigma B(\tau\tau)$ plots.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal with scalar couplings in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal.
Overlay of observed upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $t \bar{t} \phi$ Scalar with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding to one flavor limit plots.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal with pseudoscalar couplings in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal.
Overlay of observed upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $t \bar{t} \phi$ Pseudoscalar with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding to one flavor limit plots.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal with scalar couplings in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal.
Overlay of observed upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $t \bar{t} \phi$ H-like with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding to one flavor limit plots.
The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal with pseudoscalar couplings in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal.
Overlay of observed upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $W\phi$ Scalar with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding to one flavor limit plots.
The 95% confidence level upper limits on $g^2_{tS}$ for the dilaton-like $t\bar{t} \phi$ signal model. Masses of the $\phi$ boson above 300 GeV are not probed for the dilaton-like signal model as the $\phi$ branching fraction into top quark-antiquark pairs becomes nonnegligible.
Overlay of observed upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $W\phi$ Pseudoscalar with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding to one flavor limit plots.
The 95% confidence level upper limits on $g^2_{tPS}$ for the axion-like $t\bar{t} \phi$ signal model. Masses of the $\phi$ boson above 300 GeV are not probed for the axion-like signal model as the $\phi$ branching fraction into top quark-antiquark pairs becomes nonnegligible.
Overlay of observed upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $W\phi$ Higgs-like with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding to one flavor limit plots.
The 95% confidence level upper limits on the product of $sin^2 \theta$ and branching fraction for the H-like production of X$\phi \rightarrow$ ee. The vertical gray band indicates the mass region not considered in the analysis.
Overlay of observed upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $Z\phi$ Scalar with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding to one flavor limit plots.
The 95% confidence level upper limits on the product of $sin^2 \theta$ and branching fraction for the H-like production of X$\phi \rightarrow \mu\mu$. The vertical gray band indicates the mass region not considered in the analysis.
Overlay of observed upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $Z\phi$ Pseudoscalar with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding to one flavor limit plots.
The 95% confidence level upper limits on $sin^2 \theta$ for the H-like production and decay of X$\phi$ signal model.
Overlay of observed upper limits at 95% CL on the product of the coupling parameter and branching fraction of the $Z\phi$ Higgs-like with $\phi$ decaying into dielectron, dimuon or ditau pair. Theory cross section for all signals is provived in separate figure Cross section ($pp \rightarrow \ X\phi) [pb]$ and tabulated observed and expected upper limits for each signal model on corresponding to one flavor limit plots.
Cross section in units of pb for the W$\phi$, Z$\phi$, and $t\bar{t}\phi$ signals as a function of the $\phi$ boson mass in GeV. All cross sections are inclusive of all W, Z, $t\bar{t}$ and $\phi$ decay modes.
Product of acceptance and efficiency for $t\bar{t} \phi (ee)$ Scalar signal model in each signal region of the dielectron channel with inclusive t\bar{t} decay.
The 95% confidence level expected and observed upper limits on the product of $g^{2}_{tS}$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $t\bar{t} \phi$ signal with scalar couplings, where $g_{tS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $t\bar{t} \phi (\mu\mu)$ Scalar signal model in each signal region of the dimuon channel with inclusive t\bar{t} decay.
The 95% confidence level expected and observed upper limits on the product of $g^{2}_{tS}$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $t\bar{t} \phi$ signal with scalar couplings, where $g_{tS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $t\bar{t} \phi (\tau\tau)$ Scalar signal model in each signal region of the ditau channel with inclusive t\bar{t} decay.
The 95% confidence level expected and observed upper limits on the product of $g^{2}_{tS}$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $t\bar{t} \phi$ signal with scalar couplings, where $g_{tS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.
Product of acceptance and efficiency for $t\bar{t} \phi (ee)$ Pseudoscalar signal model in each signal region of the dielectron channel with inclusive t\bar{t} decay.
The 95% confidence level expected and observed upper limits on the product of $g^{2}_{tPS}$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $t\bar{t} \phi$ signal with pseudoscalar couplings, where $g_{tPS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $t\bar{t} \phi (\mu\mu)$ Pseudoscalar signal model in each signal region of the dimuon channel with inclusive t\bar{t} decay.
The 95% confidence level expected and observed upper limits on the product of $g^{2}_{tPS}$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $t\bar{t} \phi$ signal with pseudoscalar couplings, where $g_{tPS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $t\bar{t} \phi (\tau\tau)$ PS signal model in each signal region of the ditau channel with inclusive t\bar{t} decay.
The 95% confidence level expected and observed upper limits on the product of $g^{2}_{tPS}$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $t\bar{t} \phi$ signal with pseudoscalar couplings, where $g_{tPS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.
Product of acceptance and efficiency for $W\phi (ee)$ Scalar signal model in each signal region of the dielectron channel with leptonic W decay.
The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $t\bar{t} \phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $W\phi (\mu\mu)$ Scalar signal model in each signal region of the dimuon channel with leptonic W decay.
The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $t\bar{t} \phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $W\phi (\tau\tau)$ Scalar signal model in each signal region of the ditau channel with leptonic W decay.
The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $t\bar{t} \phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.
Product of acceptance and efficiency for $W\phi (ee)$ Pseudoscalar signal model in each signal region of the dielectron channel with leptonic W decay.
The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $W\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $W\phi (\mu\mu)$ Pseudoscalar signal model in each signal region of the dimuon channel with leptonic W decay.
The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $W\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $W\phi (\tau\tau)$ Pseudoscalar signal model in each signal region of the ditau channel with leptonic W decay.
The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $W\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.
Product of acceptance and efficiency for $W\phi (ee)$ Higgs-like signal model in each signal region of the dielectron channel with leptonic W decay.
The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $W\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $W\phi (\mu\mu)$ Higgs-like signal model in each signal region of the dimuon channel with leptonic W decay.
The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $W\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $W\phi (\tau\tau)$ Higgs-like signal model in each signal region of the ditau channel with leptonic W decay.
The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $W\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.
Product of acceptance and efficiency for $Z\phi (ee)$ Scalar signal model in each signal region of the dielectron channel with leptonic Z decay.
The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $W\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $Z\phi (\mu\mu)$ Scalar signal model in each signal region of the dimuon channel with leptonic Z decay.
The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $W\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $Z\phi (\tau\tau)$ Scalar signal model in each signal region of the ditau channel with leptonic Z decay.
The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $W\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.
Product of acceptance and efficiency for $Z\phi (ee)$ Pseudoscalar signal model in each signal region of the dielectron channel with leptonic Z decay.
The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $Z\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $Z\phi (\mu\mu)$ Pseudoscalar signal model in each signal region of the dimuon channel with leptonic Z decay.
The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $Z\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $Z\phi (\tau\tau)$ Pseudoscalar signal model in each signal region of the ditau channel with leptonic Z decay.
The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $Z\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.
Product of acceptance and efficiency for $Z\phi (ee)$ Higgs-like signal model in each signal region of the dielectron channel with leptonic Z decay.
The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $Z\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $Z\phi (\mu\mu)$ Higgs-like signal model in each signal region of the dimuon channel with leptonic Z decay.
The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $Z\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.
Product of acceptance and efficiency for $Z\phi (\tau\tau)$ Higgs-like signal model in each signal region of the ditau channel with leptonic Z decay.
The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $Z\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.
Example of the signal shape paramertization for W$\phi$ signal, $\phi\rightarrow ee $. Only for illustration purpose. All signals parametrization for all coupling scenarios are provided in SignalParametrizationele.root file and README file with instructions under Additional resources.
The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $Z\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.
Example of the signal shape paramertization for W$\phi$ signal, $\phi\rightarrow $\mu\mu$ $. Only for illustration purpose. All signals parametrization for all coupling scenarios are provided in SignalParametrizationmu.root file and README file with instructions under Additional resources.
The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $Z\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.
Example of the signal shape paramertization for W$\phi$ signal, $\phi\rightarrow $\tau\tau$ $. Only for illustration purpose. All signals parametrization for all coupling scenarios are provided in SignalParametrizationtau.root file and README file with instructions under Additional resources.
The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $Z\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.
The 95% confidence level expected and observed upper limits on the product of the mixing angle $sin^2 \theta$ and branching fraction for combined X$\phi$ signal model. Limits for Higgs-like production of $\phi$ boson in the dielectron channel. The inner (green) and the outer (yellow) bands indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The vertical gray band indicates the mass region corresponding to the Z boson mass window veto. Branching fractions B($\phi \rightarrow $ ee) is arbitrary.
The 95% confidence level observed upper limits on the product of $\sigma$($t \bar{t} \phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $t \bar{t} \phi$ signal with scalar couplings, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $t \bar{t} \phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
The 95% confidence level expected and observed upper limits on the product of the mixing angle $sin^2 \theta$ and branching fraction for combined X$\phi$ signal model. Limits for Higgs-like production of $\phi$ boson in the dimuon channel. The inner (green) and the outer (yellow) bands indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The vertical gray band indicates the mass region corresponding to the Z boson mass window veto. Branching fractions B($\phi \rightarrow \mu\mu$) is arbitrary.
The 95% confidence level observed upper limits on the product of $\sigma$($t \bar{t} \phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $t \bar{t} \phi$ signal with pseudoscalar couplings, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $t \bar{t} \phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
The 95% confidence level expected and observed upper limits on $sin^2 \theta$ where $\theta$ is mixing angle, for combined dimuon and ditau channels of X$\phi$ signal model. The inner(green) and the outer (yellow) bands indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis.
The 95% confidence level observed upper limits on the product of $\sigma$($W\phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $W\phi$ signal with scalar couplings, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $W\phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
The 95% confidence level expected and observed upper limits on the square of the Yukawa coupling to top quarks $g^2_{S}$ for combined dimuon and ditau channels of $t\bar{t} \phi$ signal model with dilaton-like $\phi$ boson. The inner (green) and the outer (yellow) bands indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis.
The 95% confidence level observed upper limits on the product of $\sigma$($W\phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $W\phi$ signal with pseudoscalar couplings, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $W\phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
The 95% confidence level expected and observed upper limits on the square of the Yukawa coupling to top quarks $g^2_{PS}$ for combined dimuon and ditau channels of $t\bar{t} \phi$ signal model with ”fermi-philic” axion-like $\phi$ boson. The inner (green) and the outer (yellow) bands indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis.
The 95% confidence level observed upper limits on the product of $\sigma$($W\phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $W\phi$ signal with H-like production, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $W\phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra $M_{ee}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The 95% confidence level observed upper limits on the product of $\sigma$($Z\phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $Z\phi$ signal with scalar couplings, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $Z\phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra $M_{ee}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The 95% confidence level observed upper limits on the product of $\sigma$($Z\phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $Z\phi$ signal with pseudoscalar couplings, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $Z\phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra Min. $M_{ee}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The 95% confidence level observed upper limits on the product of $\sigma$($Z\phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $Z\phi$ signal with H-like production, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $Z\phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra Min. $M_{ee}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The 95% confidence level observed upper limits on the product of $g^{2}_{tS}$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $t \bar{t} \phi$ signal with scalar couplings, where $g_{tS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra Min. $M_{ee}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The 95% confidence level observed upper limits on the product of $g^{2}_{tPS}$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $t \bar{t} \phi$ signal with pseudoscalar couplings, where $g_{tPS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra Min. $M_{ee}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The 95% confidence level observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $t \bar{t} \phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra $M_{ee}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The 95% confidence level observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $W\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra $M_{ee}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The 95% confidence level observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $W\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra Min. $M_{ee}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The 95% confidence level observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $W\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra Min. $M_{ee}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The 95% confidence level observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $Z\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra Min. $M_{ee}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The 95% confidence level observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $Z\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra Min. $M_{ee}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The 95% confidence level observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $Z\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.
Mass spectra $M_{\mu\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $t\bar{t} \phi$ signal (with inclusive $t\bar{t}$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra $M_{\mu\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $t\bar{t} \phi$ signal (with inclusive $t\bar{t}$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{\mu\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $t\bar{t} \phi$ signal (with inclusive $t\bar{t}$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{\mu\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $t\bar{t} \phi$ signal (with inclusive $t\bar{t}$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{\mu\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $t\bar{t} \phi$ signal (with inclusive $t\bar{t}$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{\mu\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $t\bar{t} \phi$ signal (with inclusive $t\bar{t}$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra $M_{\mu\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra $M_{\mu\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{\mu\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{\mu\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{\mu\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{\mu\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{e\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for an H-like $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{e\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for an H-like $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{l\tau}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for an H-like $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{l\tau}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{\tau\tau}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{\tau\tau}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{e\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{l\tau}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{\tau\tau}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{e\mu}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for an H-like $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{l\tau}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for an H-like $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{\tau\tau}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
The product of acceptance and efficiency, $A\varepsilon$, for an H-like $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.
Mass spectra Min. $M_{l\tau}$ or $M_{\tau\tau}$ (GeV) for the full Run 2 data set. In the attached figure the lower panel shows the ratio of observed events to the total expected SM background prediction, and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after fitting the data under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses are indicated in the legend. For reinterpretation we provide signal parameterization and instructions to extract it in Additional resources.
Selected signal shapes of the $W\phi$(ee) signal for illustration purposes. All shape parametrizations for all coupling scenarios of the $X\phi$(ee) signal are provided in the SignalShapes_XPhiToEleEle.root file, and a README file with instructions is provided under Additional Resources.
Selected signal shapes of the $W\phi$$(\mu\mu)$ signal for illustration purposes. All shape parametrizations for all coupling scenarios of the $X\phi$$(\mu\mu)$ signal are provided in the SignalShapes_XPhiToMuMu.root file, and a README file with instructions is provided under Additional Resources.
Selected signal shapes of the $W\phi$$(\tau\tau)$ signal for illustration purposes. All shape parametrizations for all coupling scenarios of the $X\phi$$(\tau\tau)$ signal are provided in the SignalShapes_XPhiToTauTau.root file, and a README file with instructions is provided under Additional Resources.
A search is presented for fractionally charged particles with charge below 1$e$, using their small energy loss in the tracking detector as a key variable to observe a signal. The analyzed data set corresponds to an integrated luminosity of 138 fb$^{-1}$ of proton-proton collisions collected at $\sqrt{s}$ = 13 TeV in 2016-2018 at the CERN LHC. This is the first search at the LHC for new particles with charges between $e/$3 and $e$. Masses up to 640 GeV and charges as low as $e/$3 are excluded at 95% confidence level. These are the most stringent limits to date for the considered Drell-Yan-like production mode.
Signal yields for two charge scenarios considered in the analysis, as well as their associated uncertainties.
Signal yields for two charge scenarios considered in the analysis, as well as their associated uncertainties.
Signal yields for two charge scenarios considered in the analysis, as well as their associated uncertainties.
Signal yields for two charge scenarios considered in the analysis, as well as their associated uncertainties.
Distribution of $N_{\text{hits}}^{\text{low dE/dx}}$ in the SR and the CR for the early 2016 data set, as well as for an FCP signal at a mass of 100 GeV and different charge scenarios. The vertical bars and the shaded area correspond to the statistical uncertainty in the SR and the CR, respectively. The p-value of the fit is 6%. The two lower panels show the ratio of the number of tracks observed in the CR (upper) and SR (lower), and the fit function. The vertical bars correspond to the uncertainty from statistical sources, while the shaded area shows the systematic uncertainty in the fit due to the choice of the fitting function and the binomial fit range as explained in low dE/dx the main text. Comparing with respect to the binomial fit starting at $N_{\text{hits}}^{\text{low dE/dx}} = 2$, and not $N_{\text{hits}}^{\text{low dE/dx}} = 1$, is needed to account for the fact that early 2016 data is more strongly affected low dE/dx by instrumental effects that widen the N hits distribution.
Distribution of $N_{\text{hits}}^{\text{low dE/dx}}$ in the SR and the CR for the late 2016 data set, as well as for an FCP signal at a mass of 100 GeV and different charge scenarios. The vertical bars and the shaded area correspond to the statistical uncertainty in the SR and the CR, respectively. The p-value of the fit is 78%. The two lower panels show the ratio of the number of tracks observed in the CR (upper) and SR (lower), and the fit function. The vertical bars correspond to the uncertainty from statistical sources, while the shaded area shows the systematic uncertainty in the fit due to the choice of the fitting function and the binomial fit range as explained in low dE/dx the main text.
Distribution of $N_{\text{hits}}^{\text{low dE/dx}}$ in the SR and the CR for the 2017 data set, as well as for an FCP signal at a mass of 100 GeV and different charge scenarios. The vertical bars and the shaded area correspond to the statistical uncertainty in the SR and the CR, respectively. The p-value of the fit is 65%. The two lower panels show the ratio of the number of tracks observed in the CR (upper) and SR (lower), and the fit function. The vertical bars correspond to the uncertainty from statistical sources, while the shaded area shows the systematic uncertainty in the fit due to the choice of the fitting function and the binomial fit range as explained in low dE/dx the main text.
Distribution of $N_{\text{hits}}^{\text{low dE/dx}}$ in the SR and the CR for the 2018 data set, as well as for an FCP signal at a mass of 100 GeV and different charge scenarios. The vertical bars and the shaded area correspond to the statistical uncertainty in the SR and the CR, respectively. The p-value of the fit is 9%. The two lower panels show the ratio of the number of tracks observed in the CR (upper) and SR (lower), and the fit function. The vertical bars correspond to the uncertainty from statistical sources, while the shaded area shows the systematic uncertainty in the fit due to the choice of the fitting function and the binomial fit range as explained in low dE/dx the main text.
Exclusion region (hatched) at 95% CL in the FCP charge-mass plane for the considered signal. The expected exclusion is shown with the associated 1 and 2 standard deviations $\sigma$ bands. Signal points at charges 0.9, 0.8, 2/3, 0.5, and 1/3 e are connected by straight lines to guide the eye. This is a conservative interpolation. Previous exclusions from CMS [Phys. Rev. D 87 (2013) 092008), JHEP 07 (2013) 122] as well as OPAL [Phys. Lett. B 572 (2003) 8] are given for comparison.
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