Showing 10 of 136 results
Measurements of both the inclusive and differential production cross sections of a top-quark-top-antiquark pair in association with a $Z$ boson ($t\bar{t}Z$) are presented. Final states with two, three or four isolated leptons (electrons or muons) are targeted. The measurements use the data recorded by the ATLAS detector in $pp$ collisions at $\sqrt{s}=13$ TeV at the Large Hadron Collider during the years 2015-2018, corresponding to an integrated luminosity of $140$ fb$^{-1}$. The inclusive cross section is measured to be $\sigma_{t\bar{t}Z}= 0.86 \pm 0.04~\mathrm{(stat.)} \pm 0.04~\mathrm{(syst.)}~$pb and found to be in agreement with the most advanced Standard Model predictions. The differential measurements are presented as a function of a number of observables that probe the kinematics of the $t\bar{t}Z$ system. Both the absolute and normalised differential cross-section measurements are performed at particle level and parton level for specific fiducial volumes, and are compared with NLO+NNLL theoretical predictions. The results are interpreted in the framework of Standard Model effective field theory and used to set limits on a large number of dimension-6 operators involving the top quark. The first measurement of spin correlations in $t\bar{t}Z$ events is presented: the results are in agreement with the Standard Model expectations, and the null hypothesis of no spin correlations is disfavoured with a significance of $1.8$ standard deviations.
All the entries of this HEP data record are listed. Figure and Table numbers are the same as in the paper.
Definition of the dilepton signal regions.
Definition of the trilepton signal regions.
Definition of the tetralepton signal regions.
Definition of the fiducial volumes at particle- and parton-level. Leptons refer exclusively to electrons and muons - they are dressed with additional radiation at particle-level, but not at parton-level.
Definition of the dilepton $t\bar{t}$ validation regions.
Pre-fit distribution of the number of $b$-jets in 2L-$e\mu$-6j2b, this distribution is not used in the fit.
Pre-fit distribution of the DNN output 2L-$e\mu$-6j1b, this distribution is not used in the fit.
Pre-fit distribution of the DNN output 2L-$e\mu$-5j2b, this distribution is not used in the fit.
Pre-fit distribution of the DNN output 2L-$e\mu$-6j2b, this distribution is not used in the fit.
Definition of the tetralepton control region.
Definition of the trilepton fakes control regions.
Pre-fit distribution of jet multiplicity in CR-$t\bar{t}$-e region.
Pre-fit distribution of loose lepton transverse momentum in CR-$t\bar{t}$-$\mu$ region.
Pre-fit distribution of the transverse mass of the trailing lepton and the missing transverse momentum in CR-Z-e region.
Post-fit distribution of jet multiplicity in CR-$t\bar{t}$-e region
Post-fit distribution of loose lepton transverse momentum in CR-$t\bar{t}$-$\mu$ region
Post-fit distribution of the transverse mass of the trailing lepton and the missing transverse momentum in CR-Z-e region
Post-fit distribution of NN output in SR-2L-5j2b region.
Post-fit distribution of NN output in SR-2L-6j1b region.
Post-fit distribution of NN output in SR-2L-6j2b region.
Post-fit distribution of DNN-$t\bar{t}Z$ output in 3L-SR-ttZ region.
Post-fit distribution of DNN-$t\bar{t}Z$ outputt in 3L-SR-tZq region.
Post fit events yields in 3L-SR-WZ region.
Post-fit distribution of NN output in 4L-SR-SF region.
Post-fit distribution of NN output in 4L-SR-DF region.
Post-fit distribution of b-tagger output for leading b-jet in 4L-CR-ZZ region.
Measured values of the background normalizations obtained from the combined fit. The uncertainties include statistical and systematic sources.
Measured $\sigma_{t\bar{t}\text{Z}}$ cross sections obtained from the fits in the different lepton channels. The uncertainties include statistical and systematic sources.
Grouped impact of systematic uncertainties in the combined inclusive fit to data.
Unfolded absolute cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 8 top-left).
Unfolded absolute cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 8 top-right).
Unfolded normalized cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 8 bottom-left).
Unfolded normalized cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 8 bottom-right).
Unfolded absolute cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 17 top-left and Figure 11 top-left).
Unfolded absolute cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 17 top-right).
Unfolded normalized cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 17 bottom-left).
Unfolded normalized cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 17 bottom-right).
Unfolded absolute cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 18 top-left and Figure 11 top-right).
Unfolded absolute cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 18 top-right).
Unfolded normalized cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 18 bottom-left).
Unfolded normalized cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 18 bottom-right).
Unfolded absolute cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 19 top-left and Figure 11 bottom-left).
Unfolded absolute cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 19, top-right).
Unfolded normalized cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 19, bottom-left).
Unfolded normalized cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 19, bottom-right).
Unfolded absolute cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 20 top-left and Figure 11 bottom-right).
Unfolded absolute cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 20, top-right).
Unfolded normalized cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 20, bottom-left)
Unfolded normalized cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 20, bottom-right)
Unfolded absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 21 top-left and Figure 12 top-left).
Unfolded absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 21, top-right).
Unfolded normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 21, bottom-left).
Unfolded normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 21, top-right).
Unfolded absolute cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 22 top-left and Figure 12 bottom-left).
Unfolded absolute cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 22, top-right).
Unfolded normalized cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 22, bottom-left).
Unfolded normalized cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 22, bottom-right).
Unfolded absolute cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 23 top-left and Figure 12 bottom-right).
Unfolded absolute cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 23, top-right).
Unfolded normalized cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 23, bottom-left).
Unfolded normalized cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 23, bottom-right).
Unfolded absolute cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 24 top-left and Figure 12 top-right).
Unfolded absolute cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 24, top-right).
Unfolded normalized cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 24, bottom-left).
Unfolded normalized cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 24, bottom-right).
Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level (Figure 25 top-left and Figure 9 top-left).
Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level (Figure 25 top-right).
Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level (Figure 25 bottom-left).
Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level (Figure 25 bottom-right).
Unfolded absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at particle-level (Figure 26 top-left and Figure 10 bottom-left).
Unfolded absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at parton-level (Figure 26 top-right).
Unfolded normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at particle-level (Figure 26 bottom-left).
Unfolded normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at parton-level (Figure 26 bottom-right).
Unfolded absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at particle-level (Figure 27 top-left and Figure 10 bottom-right).
Unfolded absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at parton-level (Figure 27 top-right).
Unfolded normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at particle-level (Figure 27 bottom-left).
Unfolded normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at parton-level (Figure 27 bottom-right).
Unfolded absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at particle-level (Figure 28 top-left and Figure 10 top-left).
Unfolded absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at parton-level (Figure 28 top-right).
Unfolded normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at particle-level (Figure 28 bottom-left).
Unfolded normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at parton-level (Figure 28 bottom-right).
Unfolded absolute cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level (Figure 29 left and Figure 9 bottom-left).
Unfolded normalized cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level (Figure 29 right).
Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at particle-level (Figure 30 top-left and Figure 9 top-right).
Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at parton-level (Figure 30 top-right).
Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at particle-level (Figure 30 bottom-left).
Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at parton-level (Figure 30 bottom-right).
Unfolded absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at particle-level (Figure 31 top-left and Figure 10 top-right).
Unfolded absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at parton-level (Figure 31 top-right).
Unfolded normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at particle-level (Figure 31 bottom-left).
Unfolded normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at parton-level (Figure 31 bottom-right).
Unfolded absolute cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level (Figure 32 left and Figure 9 bottom-right).
Unfolded normalized cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level (Figure 32 right).
Bootstrap replicas (0-499) for data in all regions used in inclusive cross section measurement. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data in all regions used in inclusive cross section measurement. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $|\Delta\Phi(t\bar{t}, Z)|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $|\Delta\Phi(t\bar{t}, Z)|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $|\Delta\Phi(Z, t_{lep})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $|\Delta\Phi(Z, t_{lep})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $m^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $m^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $N_{\text{jets}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $N_{\text{jets}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $|y^{t\bar{t}Z}|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $|y^{t\bar{t}Z}|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $H_{\text{T}}^{\text{l}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $H_{\text{T}}^{\text{l}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $y^{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $y^{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $p_{T}^{\mathrm{top}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $p_{T}^{\mathrm{top}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable cos $\theta^{*}_{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable cos $\theta^{*}_{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $p_{\text{T}}^{\ell, non-Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $p_{\text{T}}^{\ell, non-Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $H_{\text{T}}^{\text{l}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $H_{\text{T}}^{\text{l}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $m^{t\bar{t}Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $m^{t\bar{t}Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $N_{\text{jets}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $N_{\text{jets}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $|\Delta y(Z, t_{lep})|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $|\Delta y(Z, t_{lep})|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $p^{Z}_{T}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $p^{Z}_{T}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $p_{T}^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $p_{T}^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Parton-level acceptance and selection efficiency histograms for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable.
Parton-level acceptance and selection efficiency histograms for $|\Delta y(Z, t_{lep})|$ variable.
Parton-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.
Parton-level acceptance and selection efficiency histograms for $p_{\text{T}}^{\ell, non-Z}$ variable.
Parton-level acceptance and selection efficiency histograms for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable.
Parton-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.
Parton-level acceptance and selection efficiency histograms for cos $\theta_{Z}^{*}$ variable.
Parton-level acceptance and selection efficiency histograms for $p^{Z}_{T}$ variable.
Parton-level acceptance and selection efficiency histograms for $|y^{Z}$| variable.
Parton-level acceptance and selection efficiency histograms for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable.
Parton-level acceptance and selection efficiency histograms for $m^{t\bar{t}}$ variable.
Parton-level acceptance and selection efficiency histograms for $m^{t\bar{t}Z}$ variable.
Parton-level acceptance and selection efficiency histograms for $p_{T}^{\mathrm{top}}$ variable.
Parton-level acceptance and selection efficiency histograms for $p_{T}^{t\bar{t}}$ variable.
Parton-level acceptance and selection efficiency histograms for $|y^{t\bar{t}Z}|$ variable.
Particle-level acceptance and selection efficiency histograms for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable.
Particle-level acceptance and selection efficiency histograms for $|\Delta y(Z, t_{lep})|$ variable.
Particle-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.
Particle-level acceptance and selection efficiency histograms for $N_{\text{jets}}$ variable.
Particle-level acceptance and selection efficiency histograms for $p_{\text{T}}^{\ell, non-Z}$ variable.
Particle-level acceptance and selection efficiency histograms for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable.
Particle-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.
Particle-level acceptance and selection efficiency histograms for $N_{\text{jets}}$ variable.
Particle-level acceptance and selection efficiency histograms for cos $\theta_{Z}^{*}$ variable.
Particle-level acceptance and selection efficiency histograms for $p^{Z}_{T}$ variable.
Particle-level acceptance and selection efficiency histograms for $|y^{Z}$| variable.
Particle-level acceptance and selection efficiency histograms for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable.
Particle-level acceptance and selection efficiency histograms for $m^{t\bar{t}}$ variable.
Particle-level acceptance and selection efficiency histograms for $m^{t\bar{t}Z}$ variable.
Particle-level acceptance and selection efficiency histograms for $p_{T}^{\mathrm{top}}$ variable.
Particle-level acceptance and selection efficiency histograms for $p_{T}^{t\bar{t}}$ variable.
Particle-level acceptance and selection efficiency histograms for $|y^{t\bar{t}Z}|$ variable.
Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-4L-DF.
Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-4L-SF.
Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-4L-DF.
Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-4L-SF.
Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-4L-DF.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-4L-SF.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-4L-DF.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-4L-SF.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at particle-level in region SR-4L-DF.
Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at particle-level in region SR-4L-SF.
Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at parton-level in region SR-4L-DF.
Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at parton-level in region SR-4L-SF.
Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-4L-DF.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-4L-SF.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-4L-DF.
Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-4L-SF.
Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-4L-DF.
Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-4L-SF.
Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $N_{\text{jets}}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $p^{Z}_{T}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-4L-DF.
Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-4L-SF.
Migration matrix for $p^{Z}_{T}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-4L-DF.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-4L-SF.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-4L-DF.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-4L-SF.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $|y^{Z}$| variable at particle-level in region SR-3L-ttZ.
Migration matrix for $|y^{Z}$| variable at particle-level in region SR-3L-tZq.
Migration matrix for $|y^{Z}$| variable at particle-level in region SR-3L-WZ.
Migration matrix for $|y^{Z}$| variable at particle-level in region SR-4L-DF.
Migration matrix for $|y^{Z}$| variable at particle-level in region SR-4L-SF.
Migration matrix for $|y^{Z}$| variable at particle-level in region CR-4L-ZZ.
Migration matrix for $|y^{Z}$| variable at parton-level in region SR-3L-ttZ.
Migration matrix for $|y^{Z}$| variable at parton-level in region SR-3L-tZq.
Migration matrix for $|y^{Z}$| variable at parton-level in region SR-3L-WZ.
Migration matrix for $|y^{Z}$| variable at parton-level in region SR-4L-DF.
Migration matrix for $|y^{Z}$| variable at parton-level in region SR-4L-SF.
Migration matrix for $|y^{Z}$| variable at parton-level in region CR-4L-ZZ.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-4L-DF.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-4L-SF.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-4L-DF.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-4L-SF.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region CR-4L-ZZ.
Covariance matrix for absolute cross section as a function of $p_{T}^{\mathrm{top}}$ at particle-level.
Covariance matrix for normalized cross section as a function of $p_{T}^{\mathrm{top}}$ at particle-level.
Covariance matrix for absolute cross section as a function of $p_{T}^{\mathrm{top}}$ at parton-level.
Covariance matrix for normalized cross section as a function of $p_{T}^{\mathrm{top}}$ at parton-level.
Covariance matrix for absolute cross section as a function of $p_{T}^{t\bar{t}}$ at particle-level.
Covariance matrix for normalized cross section as a function of $p_{T}^{t\bar{t}}$ at particle-level.
Covariance matrix for absolute cross section as a function of $p_{T}^{t\bar{t}}$ at parton-level.
Covariance matrix for normalized cross section as a function of $p_{T}^{t\bar{t}}$ at parton-level.
Covariance matrix for absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at particle-level.
Covariance matrix for normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at particle-level.
Covariance matrix for absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at parton-level.
Covariance matrix for normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at parton-level.
Covariance matrix for absolute cross section as a function of $m^{t\bar{t}Z}$ at particle-level.
Covariance matrix for normalized cross section as a function of $m^{t\bar{t}Z}$ at particle-level.
Covariance matrix for absolute cross section as a function of $m^{t\bar{t}Z}$ at parton-level.
Covariance matrix for normalized cross section as a function of $m^{t\bar{t}Z}$ at parton-level.
Covariance matrix for absolute cross section as a function of $m^{t\bar{t}}$ at particle-level.
Covariance matrix for normalized cross section as a function of $m^{t\bar{t}}$ at particle-level.
Covariance matrix for absolute cross section as a function of $m^{t\bar{t}}$ at parton-level.
Covariance matrix for normalized cross section as a function of $m^{t\bar{t}}$ at parton-level.
Covariance matrix for absolute cross section as a function of $|y^{t\bar{t}Z}|$ at particle-level.
Covariance matrix for normalized cross section as a function of $|y^{t\bar{t}Z}|$ at particle-level.
Covariance matrix for absolute cross section as a function of $|y^{t\bar{t}Z}|$ at parton-level.
Covariance matrix for normalized cross section as a function of $|y^{t\bar{t}Z}|$ at parton-level.
Covariance matrix for absolute cross section as a function of cos $\theta_{Z}^{*}$ at particle-level.
Covariance matrix for normalized cross section as a function of cos $\theta_{Z}^{*}$ at particle-level.
Covariance matrix for absolute cross section as a function of cos $\theta_{Z}^{*}$ at parton-level.
Covariance matrix for normalized cross section as a function of cos $\theta_{Z}^{*}$ at parton-level.
Covariance matrix for absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at particle-level.
Covariance matrix for normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at particle-level.
Covariance matrix for absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at parton-level.
Covariance matrix for normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at parton-level.
Covariance matrix for absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at particle-level.
Covariance matrix for normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at particle-level.
Covariance matrix for absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at parton-level.
Covariance matrix for normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at parton-level.
Covariance matrix for absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ at particle-level.
Covariance matrix for normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ at particle-level.
Covariance matrix for absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ at parton-level.
Covariance matrix for normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ at parton-level.
Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ at in the tetralepton channel particle-level.
Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ at in the tetralepton channel particle-level.
Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ at in the tetralepton channel parton-level.
Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at parton-level.
Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level.
Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level.
Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level.
Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level.
Covariance matrix for absolute cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level.
Covariance matrix for normalized cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level.
Covariance matrix for absolute cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level.
Covariance matrix for normalized cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level.
Covariance matrix for absolute cross section as a function of $p^{Z}_{T}$ at particle-level.
Covariance matrix for normalized cross section as a function of $p^{Z}_{T}$ at particle-level.
Covariance matrix for absolute cross section as a function of $p^{Z}_{T}$ at parton-level.
Covariance matrix for normalized cross section as a function of $p^{Z}_{T}$ at parton-level.
Covariance matrix for absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at particle-level.
Covariance matrix for normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at particle-level.
Covariance matrix for absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at parton-level.
Covariance matrix for normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at parton-level.
Covariance matrix for absolute cross section as a function of $|y^{Z}$| at particle-level.
Covariance matrix for normalized cross section as a function of $|y^{Z}$| at particle-level.
Covariance matrix for absolute cross section as a function of $|y^{Z}$| at parton-level.
Covariance matrix for normalized cross section as a function of $|y^{Z}$| at parton-level.
Ranking of nuisance parameters and background normalizations on signal strength for inclusive cross section measurement in combination of all channels
Observed and expected 68% and 95% credible intervals for the top-boson operators, in the marginalised linear fit.
Observed and expected 68% and 95% credible intervals for the top-boson operators, in the marginalised quadratic fit.
Observed and expected 68% and 95% credible intervals for the top-boson operators, in the independent quadratic fits (allowing only one Wilson Coefficient to be non-zero).
Observed and expected 68% and 95% credible intervals for the four-quark operators, in the marginalised linear fit.
Observed and expected 68% and 95% credible intervals for the four-quark operators, in the marginalised quadratic fit.
Observed and expected 68% and 95% credible intervals for the four-quark operators, in the independent quadratic fits (allowing only one Wilson Coefficient to be non-zero).
Observed and expected 68% and 95% credible intervals for Fisher-rotated directions of EFT sensitivity, in the marginalised linear fit.
Correlation matrix of the input particle-level observables used in the EFT fit.
A test of lepton flavor universality in B$^{\pm}$$\to$ K$^{\pm}\mu^+\mu^-$ and B$^{\pm}$$\to$ K$^{\pm}$e$^+$e$^-$ decays, as well as a measurement of differential and integrated branching fractions of a nonresonant B$^{\pm}$$\to$ K$^{\pm}\mu^+\mu^-$ decay are presented. The analysis is made possible by a dedicated data set of proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded in 2018, by the CMS experiment at the LHC, using a special high-rate data stream designed for collecting about 10 billion unbiased b hadron decays. The ratio of the branching fractions $\mathcal{B}$(B$^{\pm}$$\to$ K$^{\pm}\mu^+\mu^-$) to $\mathcal{B}$(B$^{\pm}$$\to$ K$^{\pm}$e$^+$e$^-$) is determined from the measured double ratio $R$(K) of these decays to the respective branching fractions of the B$^\pm$$\to$ J/$\psi$K$^\pm$ with J/$\psi$$\to$$\mu^+\mu^-$ and e$^+$e$^-$ decays, which allow for significant cancellation of systematic uncertainties. The ratio $R$(K) is measured in the range 1.1 $\lt$$q^2$$\lt$ 6.0 GeV$^2$, where $q$ is the invariant mass of the lepton pair, and is found to be $R$(K) = 0.78 $^{+0.47}_{-0.23}$, in agreement with the standard model expectation $R$(K) $\approx$ 1. This measurement is limited by the statistical precision of the electron channel. The integrated branching fraction in the same $q^2$ range, $\mathcal{B}$(B$^{\pm}$$\to$ K$^{\pm}\mu^+\mu^-$) = (12.42 $\pm$ 0.68) $\times$ 10$^{-8}$, is consistent with the present world-average value and has a comparable precision.
The differential $\text{B}^+ \to \text{K}^+\mu^+\mu^-$ branching fraction measured in the individual $q^2$ bins. The uncertainties in the yields are statistical uncertainties from the fit, while the branching fraction uncertainties include both the statistical and systematic components.
Differential branching fraction $d\mathcal{B}/dq^2$, with theoretical predictions obtained with the HEPFiT, SuperIso, Flavio, and EOS packages. The HEPFiT predictions are available only for $q^2 < 8\ \mathrm{GeV}^2$.
Relative uncertainties in the differential branching fraction measurement of $\mathrm{B}^+\to\mathrm{K}^+\mu^+\mu^-$ per $q^2$ bin.
Correlation matrix for the differential branching fraction extraction between different $q^2$ bins in the simultaneous fit.
The product of acceptance and efficiency ($A\epsilon$) of the $\mathcal{B}(\mathrm{B}^+\to\mathrm{K}^+\mu^+\mu^-)$ channel, as a function of the muon pair $q^2$, as measured in simulated signal events, after all the corrections applied. In the figure, regions corresponding to resonances are displayed with red markers.
Same as Table 5, but for the bins containing the J$\psi$ and $\psi$(2S) resonances.
Integrated branching fraction $\mathcal{B}(\mathrm{B}^\pm \to \mathrm{K}^\pm\mu^+\mu^-)$ in the low-$q^2$ region.
Ratio of branching fractions $\mathcal{B}(\text{B}^\pm \to \text{K}^\pm\mu^+\mu^-)$ to $\mathcal{B}(\text{B}^\pm \to \text{K}^\pm\text{e}^+\text{e}^-)$, determined from the measured double ratio $R$(K) of these decays to the respective branching fractions of the decay chains $\text{B}^\pm\to\text{J/}\psi\text{K}^\pm$ with $\text{J/}\psi\to\mu^+\mu^-$ and $\text{e}^+\text{e}^-$.
Negative log likelihood function from the fit profiled as a function of the inverse ratio $R(\mathrm{K})^{-1}$.
Higgsinos with masses near the electroweak scale can solve the hierarchy problem and provide a dark matter candidate, while detecting them at the LHC remains challenging if their mass splitting is $\mathcal{O}(1 \text{GeV})$. This Letter presents a novel search for nearly mass-degenerate Higgsinos in events with an energetic jet, missing transverse momentum, and a low-momentum track with a significant transverse impact parameter using 140 fb$^{-1}$ of proton-proton collision data at $\sqrt{s}=13$ TeV collected by the ATLAS experiment. For the first time since LEP, a range of mass splittings between the lightest charged and neutral Higgsinos from $0.3$ GeV to $0.9$ GeV is excluded at 95$\%$ confidence level, with a maximum reach of approximately $170$ GeV in the Higgsino mass.
Number of expected and observed data events in the SR (top), and the model-independent upper limits obtained from their consistency (bottom). The symbol $\tau_{\ell}$ ($\tau_{h}$) refers to fully-leptonic (hadron-involved) tau decays. The Others category includes contributions from minor background processes including $t\bar{t}$, single-top and diboson. The individual uncertainties can be correlated and do not necessarily sum up in quadrature to the total uncertainty. The bottom section shows the observed 95% CL upper limits on the visible cross-section ($\langle\epsilon\sigma\rangle_{\mathrm{obs}}^{95}$), on the number of generic signal events ($S_{\mathrm{obs}}^{95}$) as well as the expected limit ($S_{\mathrm{exp}}^{95}$) given the expected number (and $\pm 1\sigma$ deviations from the expectation) of background events.
Number of expected and observed data events in the SR (top), and the model-independent upper limits obtained from their consistency (bottom). The symbol $\tau_{\ell}$ ($\tau_{h}$) refers to fully-leptonic (hadron-involved) tau decays. The Others category includes contributions from minor background processes including $t\bar{t}$, single-top and diboson. The individual uncertainties can be correlated and do not necessarily sum up in quadrature to the total uncertainty. The bottom section shows the observed 95% CL upper limits on the visible cross-section ($\langle\epsilon\sigma\rangle_{\mathrm{obs}}^{95}$), on the number of generic signal events ($S_{\mathrm{obs}}^{95}$) as well as the expected limit ($S_{\mathrm{exp}}^{95}$) given the expected number (and $\pm 1\sigma$ deviations from the expectation) of background events.
Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.
Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.
Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.
Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.
Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.
Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.
Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.
Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.
Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.
Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.
Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.
Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.
Expected and observed CLs values per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.
Expected and observed CLs values per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.
Expected and observed CLs values per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.
Expected and observed CLs values per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.
Expected and observed cross-section upper-limit per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.
Expected and observed cross-section upper-limit per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.
Expected and observed cross-section upper-limit per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.
Expected and observed cross-section upper-limit per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.
Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.
Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.
Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.
Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.
Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.
Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.
Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.
Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.
Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.
Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.
Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.
Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.
Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.
Event selection cutflows for signal samples with $m(\tilde{\chi}_{1}^0)$ = 150 GeV and $\Delta m(\tilde{\chi}_{1}^\pm, \tilde{\chi}_{1}^0)$ = 1.5, 1.0, and 0.75 GeV, including all six production processes ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$). The cross-section used to obtain the initial number of events ($\sigma(\mathrm{n}_{\mathrm{jets}}) \geq 1$) refers to an emission of at least one gluon or quark with $p_{\mathrm{T}} > 50$ GeV at the parton level.
Event selection cutflows for signal samples with $m(\tilde{\chi}_{1}^0)$ = 150 GeV and $\Delta m(\tilde{\chi}_{1}^\pm, \tilde{\chi}_{1}^0)$ = 1.5, 1.0, and 0.75 GeV, including all six production processes ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$). The cross-section used to obtain the initial number of events ($\sigma(\mathrm{n}_{\mathrm{jets}}) \geq 1$) refers to an emission of at least one gluon or quark with $p_{\mathrm{T}} > 50$ GeV at the parton level.
Event selection cutflows for signal samples with $m(\tilde{\chi}_{1}^0)$ = 150 GeV and $\Delta m(\tilde{\chi}_{1}^\pm, \tilde{\chi}_{1}^0)$ = 0.5, 0.35, and 0.25 GeV, including all six production processes ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$). The cross-section used to obtain the initial number of events ($\sigma(\mathrm{n}_{\mathrm{jets}}) \geq 1$) refers to an emission of at least one gluon or quark with $p_{\mathrm{T}} > 50$ GeV at the parton level.
Event selection cutflows for signal samples with $m(\tilde{\chi}_{1}^0)$ = 150 GeV and $\Delta m(\tilde{\chi}_{1}^\pm, \tilde{\chi}_{1}^0)$ = 0.5, 0.35, and 0.25 GeV, including all six production processes ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$). The cross-section used to obtain the initial number of events ($\sigma(\mathrm{n}_{\mathrm{jets}}) \geq 1$) refers to an emission of at least one gluon or quark with $p_{\mathrm{T}} > 50$ GeV at the parton level.
This paper presents a search for pair production of higgsinos, the supersymmetric partners of the Higgs bosons, in scenarios with gauge-mediated supersymmetry breaking. Each higgsino is assumed to decay into a Higgs boson and a nearly massless gravitino. The search targets events where each Higgs boson decays into $b\bar{b}$, leading to a reconstructed final state with at least three energetic $b$-jets and This paper presents a search for pair production of higgsinos, the supersymmetric partners of the Higgs bosons, in scenarios with gauge-mediated supersymmetry breaking. Each higgsino is assumed to decay into a Higgs boson and a nearly massless gravitino. The search targets events where each Higgs boson decays into $b\bar{b}$, leading to a reconstructed final state with at least three energetic $b$-jets and missing transverse momentum. Two complementary analysis channels are used, with each channel specifically targeting either low or high values of the higgsino mass. The low-mass (high-mass) channel exploits 126 (139) fb$^{-1}$ of $\sqrt{s}=13$ TeV data collected by the ATLAS detector during Run 2 of the Large Hadron Collider. No significant excess above the Standard Model prediction is found. At 95% confidence level, masses between 130 GeV and 940 GeV are excluded for higgsinos decaying exclusively into Higgs bosons and gravitinos. Exclusion limits as a function of the higgsino decay branching ratio to a Higgs boson are also reported.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Pre-fit data and background (reweighted $2b$) predictions for each $4b$ SR $E_\text{T}^\text{miss}$ and $m_\text{eff}$ bin of the low-mass channel for the 2016 data-taking period. The bottom panel shows the significance of any differences between the observed $4b$ data and the background prediction. The $1\sigma$ and $2\sigma$ bands are shown in green and yellow, respectively. All systematics are included except the background normalization, which is 2.3%.
Pre-fit data and background (reweighted $2b$) predictions for each $4b$ SR $E_\text{T}^\text{miss}$ and $m_\text{eff}$ bin of the low-mass channel for the 2017 data-taking period. The bottom panel shows the significance of any differences between the observed $4b$ data and the background prediction. The $1\sigma$ and $2\sigma$ bands are shown in green and yellow, respectively. All systematics are included except the background normalization, which is 3.7%.
Pre-fit data and background (reweighted $2b$) predictions for each $4b$ SR $E_\text{T}^\text{miss}$ and $m_\text{eff}$ bin of the low-mass channel for the 2018 data-taking period. The bottom panel shows the significance of any differences between the observed $4b$ data and the background prediction. The $1\sigma$ and $2\sigma$ bands are shown in green and yellow, respectively. All systematics are included except the background normalization, which is 1.8%.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the 95% CL observed (solid) and expected (dashed) upper limits on $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})$, assuming the theory cross section for higgsino pair production. The higgsinos are assumed to decay as $\tilde{H}\rightarrow h + \tilde{G}$ or $\tilde{H}\rightarrow Z + \tilde{G}$. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the 95% CL observed (solid) and expected (dashed) upper limits on $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})$, assuming the theory cross section for higgsino pair production. The higgsinos are assumed to decay as $\tilde{H}\rightarrow h + \tilde{G}$ or $\tilde{H}\rightarrow Z + \tilde{G}$. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the 95% CL observed (solid) and expected (dashed) upper limits on $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})$, assuming the theory cross section for higgsino pair production. The higgsinos are assumed to decay as $\tilde{H}\rightarrow h + \tilde{G}$ or $\tilde{H}\rightarrow Z + \tilde{G}$. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the 95% CL observed (solid) and expected (dashed) upper limits on $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})$, assuming the theory cross section for higgsino pair production. The higgsinos are assumed to decay as $\tilde{H}\rightarrow h + \tilde{G}$ or $\tilde{H}\rightarrow Z + \tilde{G}$. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the 95% CL observed (solid) and expected (dashed) upper limits on $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})$, assuming the theory cross section for higgsino pair production. The higgsinos are assumed to decay as $\tilde{H}\rightarrow h + \tilde{G}$ or $\tilde{H}\rightarrow Z + \tilde{G}$. The phase space above the lines is excluded.
Exclusion limits of the low-mass channel. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass channel. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the high-mass channel. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the high-mass channel. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Results of the background-only fit in the low-mass channel discovery region SR_LM_150. Both pre-fit and post-fit values are shown.
Results of the background-only fit in the low-mass channel discovery region SR_LM_300. Both pre-fit and post-fit values are shown.
The experimental efficiency of the low-mass channel for the exclusion and discovery signal regions as a function of higgsino mass. The experimental efficiency is defined as the number of events passing the detector-level event selections divided by the number of events passing the event selections for a perfect detector. The denominator is obtained by implementing particle-level event selections that emulate the detector-level selections. This treats the lack of availability of $b$-jet triggers as an inefficiency.
The particle-level acceptance for the low-mass exclusion and discovery signal regions, shown as a function of higgsino mass. The acceptance is defined as the fraction of signal events passing the particle-level event selection that emulates the detector-level selection. The acceptance calculation considers only those signal events where both higgsinos decay to Higgs bosons.
The experimental efficiency of the high-mass channel discovery regions as a function of higgsino mass. For each higgsino mass, the efficiency is shown for the SR-1 region corresponding to the mass. For masses above 1100 GeV, SR-1-1100 is used. The experimental efficiency is defined as the number of events passing the detector-level event selections divided by the number of events passing the event selections for a perfect detector. The denominator is obtained by implementing particle-level event selections that emulate the detector-level selections. The efficiency calculation considers only those signal events where both higgsinos decay to Higgs bosons.
The particle-level acceptance for the high-mass signal regions, shown as a function of higgsino mass. For each higgsino mass, the acceptance is shown for the SR-1 region corresponding to the mass. For masses above 1100 GeV, SR-1-1100 is used. The acceptance is defined as the fraction of signal events passing the particle-level event selection that emulates the detector-level selection. The acceptance calculation considers only those signal events where both higgsinos decay to Higgs bosons.
Cutflow for the low-mass channel for a representative 130 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 150 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 200 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 250 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 300 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 400 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 500 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 600 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 700 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 800 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 900 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 1000 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 1100 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 200 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 250 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 300 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 400 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 500 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 600 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 700 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 800 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 900 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 1000 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 1100 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 1200 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 1300 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 1400 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 1500 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
A combination of the results of several searches for the electroweak production of the supersymmetric partners of standard model bosons, and of charged leptons, is presented. All searches use proton-proton collision data at $\sqrt{s}$ = 13 TeV recorded with the CMS detector at the LHC in 2016-2018. The analyzed data correspond to an integrated luminosity of up to 137 fb$^{-1}$. The results are interpreted in terms of simplified models of supersymmetry. Two new interpretations are added with this combination: a model spectrum with the bino as the lightest supersymmetric particle together with mass-degenerate higgsinos decaying to the bino and a standard model boson, and the compressed-spectrum region of a previously studied model of slepton pair production. Improved analysis techniques are employed to optimize sensitivity for the compressed spectra in the wino and slepton pair production models. The results are consistent with expectations from the standard model. The combination provides a more comprehensive coverage of the model parameter space than the individual searches, extending the exclusion by up to 125 GeV, and also targets some of the intermediate gaps in the mass coverage.
Post-fit distribution of the $M(ll)$ variable for the low-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.
Post-fit distribution of the $M(ll)$ variable for the medium-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.
Post-fit distribution of the $M(ll)$ variable for the high-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.
Post-fit distribution of the $M(ll)$ variable for the ultrahigh-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.
Post-fit distribution of the $M(ll)$ variable for the low-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '3l soft' signal region of the the '2/3l soft' analysis.
Post-fit distribution of the $M(ll)$ variable for the medium-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '3l soft' signal region of the the '2/3l soft' analysis.
Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for low-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.
Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for medium-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.
Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for high-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.
Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for ultrahigh-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.
2SS $\ell/{\geq}\,3\ell$ search: observed and expected yields across the SRs in category A, events with three light leptons of which at least two form an OSSF pair, after the requirement that the leading-lepton $p_{\mathrm{T}}$ be greater than 30 GeV is applied.
2SS $\ell/{\geq}\,3\ell$ search: observed and expected yields across the SRs of the '${\geq}\ 3\ell$' search in category B, events with three light leptons and no OSSF pair, after the requirement that the leading-lepton $p_{\mathrm{T}}$ be greater than 30 GeV is applied.
Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production in the WZ topology for the full parameter space.
Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production in the WZ topology for the compressed space.
Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production in the WH topology for the full parameter space.
Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production with mixed topology with equal branching fraction to WZ and WH.
Wino-bino model: exclusion contours from the individual and combined analyses targeting WZ topology for the full parameter space. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.
Wino-bino model: exclusion contours from the individual and combined analyses targeting the corresponding compressed region. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.
Wino-bino model: exclusion contours from the individual and combined analyses targeting the WH topology for the full parameter space. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.
Wino-bino model: exclusion contours from the individual and combined analyses targeting combined contours for these two topologies. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.
GMSB model: expected and observed cross section limits for the neutralino-neutralino production for the ZZ topology.
GMSB model: expected and observed cross section limits for the neutralino-neutralino production for the HH topology.
GMSB model: expected and observed cross section limits for the neutralino-neutralino production for the mixed topology with equal branching fraction to H and Z.
GMSB model: cross section limits for neutralino-neutralino production as a function of the NSLP mass and the branching fraction to the H boson for the combination of the searches.
GMSB model: exclusion limit for neutralino-neutralino production as a function of the NSLP mass and the branching fraction to the H boson for the combination of the searches along with the input searches. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.
Cross section upper limit(s) in the mass plane of NLSP and LSP masses for the higgsino-bino model.
Mass plane cross section upper limit for direct slepton pair production, with observed and expected exclusion limits in the full mass plane from the combination.
Mass plane cross section upper limit for direct slepton pair production, with observed and expected exclusion limits in the compressed region from '2/3l' soft search.
Statistical combinations of searches for charginos and neutralinos using various decay channels are performed using $139\,$fb$^{-1}$ of $pp$ collision data at $\sqrt{s}=13\,$TeV with the ATLAS detector at the Large Hadron Collider. Searches targeting pure-wino chargino pair production, pure-wino chargino-neutralino production, or higgsino production decaying via Standard Model $W$, $Z$, or $h$ bosons are combined to extend the mass reach to the produced SUSY particles by 30-100 GeV. The depth of the sensitivity of the original searches is also improved by the combinations, lowering the 95% CL cross-section upper limits by 15%-40%.
Expected 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.
$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.
$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.
Observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.
$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.
$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.
Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.
$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.
$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.
Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.
$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.
$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.
Expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.
$+1\sigma$ expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.
$-1\sigma$ expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.
Observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.
$+1\sigma$ observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.
$-1\sigma$ observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.
Observed upper limit on the signal cross section in fb for the production of $\tilde{\chi}_1^{+}\tilde{\chi}_{1}^{-}$.
The analyses used in combination for each scenario to set limits in models of the production of $\tilde{\chi}_1^{+}\tilde{\chi}_{1}^{-}$.
Observed upper limit on the signal cross section in fb for chargino--neutralino production decaying via W and Z bosons.
The analyses used in combination for each scenario to set limits in models of chargino--neutralino production decaying via W and Z bosons.
Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
Observed upper limit on the signal cross section in fb for chargino--neutralino production decaying via W and h bosons.
The analyses used in combination for each scenario to set limits in models of chargino--neutralino production decaying via W and h bosons.
Observed upper limit on the signal cross section in fb for higgsino GGM scenarios.
The analyses used in combination for each scenario to set limits in higgsino GGM scenarios.
This paper presents a search for top-squark pair production in final states with a top quark, a charm quark and missing transverse momentum. The data were collected with the ATLAS detector during LHC Run 2 and corresponds to an integrated luminosity of 139fb$^{-1}$ of proton-proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV. The analysis is motivated by an extended Minimal Supersymmetric Standard Model featuring a non-minimal flavour violation in the second- and third-generation squark sector. The top squark in this model has two possible decay modes, either $\tilde{t}_1 \rightarrow c\tilde{\chi}_1^0$ or $\tilde{t}_1\rightarrow t\tilde{\chi}_1^0$, where the $\tilde{\chi}_1^0$ is undetected. The analysis is optimised assuming that both of the decay modes are equally probable, leading to the most likely final state of $tc + E_{\text{T}}^{\text{miss}}$. Good agreement is found between the Standard Model expectation and the data in the search regions. Exclusion limits at 95% CL are obtained in the $m(\tilde{t}_1)$ vs $m(\tilde{\chi}_1^0)$ plane and, in addition, limits on the branching ratio of the $\tilde{t}_1\rightarrow t\tilde{\chi}_1^0$ decay as a function of $m(\tilde{t}_1)$ are also produced. Top-squark masses of up to 800 GeV are excluded for scenarios with light neutralinos, and top-squark masses up to 600 GeV are excluded in scenarios where the neutralino and the top squark are almost mass degenerate.
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <br><br> <b>Exclusion contours:</b> <ul> <li><a href="?table=mass_obs">Observed exclusion contour in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$</a> <li><a href="?table=mass_exp">Expected exclusion contour in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$</a> <li><a href="?table=mass_band_1">$\pm1\sigma$ exclusion contour in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$</a> <li><a href="?table=mass_band_2">$\pm1\sigma$ exclusion contour in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$</a> <li><a href="?table=br_m1_obs">Observed exclusion contour in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$</a> <li><a href="?table=br_m1_exp">Expected exclusion contour in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$</a> <li><a href="?table=br_m1_band_1">$\pm1\sigma$ exclusion contour in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$</a> <li><a href="?table=br_m1_band_2">$\pm1\sigma$ exclusion contour in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$</a> </ul> <b>Upper limits:</b> <ul> <li><a href="?table=mass_upperLimits_obs">Observed upper limits on the top-spartner pair production cross-section at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$</a> <li><a href="?table=br_m1_upperLimits_obs">Observed upper limits on the top-spartner pair production cross-section at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.</a> <li><a href="?table=mass_upperLimits_exp">Expected upper limits on the top-spartner pair production cross-section at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$</a> <li><a href="?table=br_m1_upperLimits_exp">Expected upper limits on the top-spartner pair production cross-section at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.</a> </ul> <b>Kinematic distributions:</b> <ul> <li><a href="?table=SRA_ntop">SRA region number of top-tagged jets distribution</a> <li><a href="?table=SRA_mttwo">SRA region $m_{\mathrm{T2}}(j^{b}_{R=1.0}, c)$ distribution</a> <li><a href="?table=SRB_ptc">SRB region leading c-tagged jet $p_{\mathrm{T}}$</a> <li><a href="?table=SRB_mtj">SRB region $m_{\mathrm{T}}(j, E_{\mathrm{T}}^{\mathrm{miss}})_{\mathrm{close}}$ distribution</a> <li><a href="?table=SRC_metsig">SRC region missing transverse momentum significance distribution</a> <li><a href="?table=SRC_mtj">SRC region $m_{\mathrm{T}}(j, E_{\mathrm{T}}^{\mathrm{miss}})_{\mathrm{close}}$ distribution</a> <li><a href="?table=SRD_NN">SRD NN signal score distribution</a> <li><a href="?table=SRD_meff">SRD $m_{\mathrm{eff}}$ distribution</a> </ul> <b>Pull distributions:</b> <ul> <li><a href="?table=SRABCPull">Pull plots showing the SRA, SRB and SRC post-fit data and SM agreement using the background-only fit configuration</a> <li><a href="?table=SRDPull">Pull plots showing the SRD post-fit data and SM agreement using the background-only fit configuration</a> </ul> <b>Cut flows:</b> <ul> <li><a href="?table=cutflow_SRA">Cutflow of 3 signal points in the SRA region.</a> <li><a href="?table=cutflow_SRB">Cutflow of 3 signal points in the SRB region.</a> <li><a href="?table=cutflow_SRC">Cutflow of 3 signal points in the SRC region.</a> <li><a href="?table=cutflow_SRD750">Cutflow of 3 signal points in the SRD750 region.</a> <li><a href="?table=cutflow_SRD1000">Cutflow of 3 signal points in the SRD1000 region.</a> <li><a href="?table=cutflow_SRD1250">Cutflow of 3 signal points in the SRD1250 region.</a> <li><a href="?table=cutflow_SRD1500">Cutflow of 3 signal points in the SRD1500 region.</a> <li><a href="?table=cutflow_SRD1750">Cutflow of 3 signal points in the SRD1750 region.</a> <li><a href="?table=cutflow_SRD2000">Cutflow of 3 signal points in the SRD2000 region.</a> </ul> <b>Acceptance and efficiencies:</b> <ul> <li> <b>SRA_bin1:</b> <a href="?table=Acc_SRA_bin1">Acceptance table of the SRA$^{[450,575]}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRA_bin1">Efficiency table of the SRA$^{[450,575]}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRA_bin2:</b> <a href="?table=Acc_SRA_bin2">Acceptance table of the SRA$^{\geq 575}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRA_bin2">Efficiency table of the SRA$^{\geq 575}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRB_bin1:</b> <a href="?table=Acc_SRB_bin1">Acceptance table of the SRB$^{[100,150]}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRB_bin1">Efficiency table of the SRB$^{[100,150]}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRB_bin2:</b> <a href="?table=Acc_SRB_bin2">Acceptance table of the SRB$^{[150,400]}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRB_bin2">Efficiency table of the SRB$^{[150,400]}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRB_bin3:</b> <a href="?table=Acc_SRB_bin3">Acceptance table of the SRB$^{\geq 400}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRB_bin3">Efficiency table of the SRB$^{\geq 400}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRC_bin1:</b> <a href="?table=Acc_SRC_bin1">Acceptance table of the SRC$^{[100,150]}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRC_bin1">Efficiency table of the SRC$^{[100,150]}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRC_bin2:</b> <a href="?table=Acc_SRC_bin2">Acceptance table of the SRC$^{[150,300]}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRC_bin2">Efficiency table of the SRC$^{[150,300]}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRC_bin3:</b> <a href="?table=Acc_SRC_bin3">Acceptance table of the SRC$^{[300,500]}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRC_bin3">Efficiency table of the SRC$^{[300,500]}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRC_bin4:</b> <a href="?table=Acc_SRC_bin4">Acceptance table of the SRC$^{\geq 500}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRC_bin4">Efficiency table of the SRC$^{\geq 500}$ in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRD_bin1:</b> <a href="?table=Acc_SRD_bin1">Acceptance table of the SRD750 in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRD_bin1">Efficiency table of the SRD750 in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRD_bin2:</b> <a href="?table=Acc_SRD_bin2">Acceptance table of the SRD1000 in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRD_bin2">Efficiency table of the SRD1000 in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRD_bin3:</b> <a href="?table=Acc_SRD_bin3">Acceptance table of the SRD1250 in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRD_bin3">Efficiency table of the SRD1250 in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRD_bin4:</b> <a href="?table=Acc_SRD_bin4">Acceptance table of the SRD1500 in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRD_bin4">Efficiency table of the SRD1500 in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRD_bin5:</b> <a href="?table=Acc_SRD_bin5">Acceptance table of the SRD1750 in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRD_bin5">Efficiency table of the SRD1750 in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <li> <b>SRD_bin6:</b> <a href="?table=Acc_SRD_bin6">Acceptance table of the SRD2000 in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> <a href="?table=Eff_SRD_bin6">Efficiency table of the SRD2000 in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.</a> </ul> <b>Truth Code snippets</b> are available under "Resources" (purple button on the left)
Observed exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Observed exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$ and a $+1 \sigma$ deviation of the NNLO+NNLL theoretical cross-section of a $\tilde{t}_1$ pair-production.
Observed exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$ and a $-1 \sigma$ deviation of the NNLO+NNLL theoretical cross-section of a $\tilde{t}_1$ pair-production.
Expected exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
The $1\sigma$ variation of expected 95% CL exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
The $2\sigma$ variation of expected 95%CL exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Observed exclusion limits at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.
Observed exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{ GeV}$ and a $+1 \sigma$ deviation of the NNLO+NNLL theoretical cross-section of a $\tilde{t}_1$ pair-production.
Observed exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{ GeV}$ and a $-1 \sigma$ deviation of the NNLO+NNLL theoretical cross-section of a $\tilde{t}_1$ pair-production.
Expected exclusion limits at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.
The $1\sigma$ variation of expected 95% CL exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.
The $2\sigma$ variation of expected 95%CL exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.
Observed upper limits on the top-spartner pair production cross-section in fb at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$
Expected upper limits on the top-spartner pair production cross-section in fb at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$
Observed upper limits on the top-spartner pair production cross-section in fb at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.
Expected upper limits on the top-spartner pair production cross-section in fb at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.
Post-fit distribution of $N_{\mathrm{tops}}^{\mathrm{DNN}} (\mathrm{R=1.0})$ in the SRA signal region presented without the associated SRA applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
Post-fit distribution of $m_{\mathrm{T2}}(j^{b}_{R=1.0}, c)$ in the SRA signal region presented without the associated SRA applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
Post-fit distribution of $p_{\mathrm{T}}(c_{1})$ in the SRB signal region presented without the associated SRB applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
Post-fit distribution of $m_{\mathrm{T}}(j, \mathrm{E}_{\mathrm{T}}^{\mathrm{miss}})_{\mathrm{close}}$ in the SRB signal region presented without the associated SRB applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
Post-fit distribution of $\mathrm{E}_{\mathrm{T}}^{\mathrm{miss}} \textrm{Significance}$ in the SRC signal region presented without the associated SRC applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
Post-fit distribution of $m_{\mathrm{T}}(j, \mathrm{E}_{\mathrm{T}}^{\mathrm{miss}})_{\mathrm{close}}$ in the SRC signal region presented without the associated SRC applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
Post-fit distribution of NN signal score in the SRD signal region presented without the associated SRD applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
Post-fit distribution of $m_{\mathrm{eff}}$ in the SRD signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
Pull plots showing the SRA, SRB and SRC post-fit data and SM agreement using the background-only fit configuration
Pull plots showing the SRD post-fit data and SM agreement using the background-only fit configuration
Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region A. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region B. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region C. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 750. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 1000. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 1250. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 1500. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 1750. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 2000. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Signal acceptance in the SRA$^{[450,575]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRA$^{[450,575]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRA$^{\geq 575}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRA$^{\geq 575}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRB$^{[100,150]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRB$^{[100,150]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRB$^{[150,400]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRB$^{[150,400]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRB$^{\geq 400}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRB$^{\geq 400}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRC$^{[100,150]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRC$^{[100,150]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRC$^{[150,300]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRC$^{[150,300]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRC$^{[300,500]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRC$^{[300,500]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRC$^{\geq 500}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRC$^{\geq 500}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRD750 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRD750 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRD1000 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRD1000 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRD1250 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRD1250 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRD1500 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRD1500 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRD1750 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRD1750 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
Signal acceptance in the SRD2000 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).
Signal efficiency in the SRD2000 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.
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.
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.
This Letter presents the first study of the energy-dependence of diboson polarization fractions in $WZ \rightarrow \ell\nu \ell'\ell'~(\ell, \ell'=e, \mu)$ production. The data set used corresponds to an integrated luminosity of 140 fb$^{-1}$ of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the ATLAS detector. Two fiducial regions with an enhanced presence of events featuring two longitudinally-polarized bosons are defined. A non-zero fraction of events with two longitudinally-polarized bosons is measured with an observed significance of 5.3 standard deviations in the region with $100<p_T^Z\leq200$ GeV and 1.6 standard deviations in the region with $p_T^Z>200$ GeV, where $p_T^Z$ is the transverse momentum of the $Z$ boson. This Letter also reports the first study of the Radiation Amplitude Zero effect. Events with two transversely-polarized bosons are analyzed for the $\Delta Y(\ell_W Z)$ and $\Delta Y(WZ)$ distributions defined respectively as the rapidity difference between the lepton from the $W$ boson decay and the $Z$ boson and the rapidity difference between the $W$ boson and the $Z$ boson. Significant suppression of events near zero is observed in both distributions. Unfolded $\Delta Y(\ell_W Z)$ and $\Delta Y(WZ)$ distributions are also measured and compared to theoretical predictions.
Polarization fractions in the region with $100<p_T^Z\leq200$ GeV using three unconstrained parameters.
Polarization fractions in the region with $p_T^Z>200$ GeV using three unconstrained parameters.
Fraction of events where both bosons are longitudinally polarized in the region with $100<p_T^Z\leq200$ GeV using two unconstrained parameters.
Fraction of events where both bosons are longitudinally polarized in the region with $p_T^Z>200$ GeV using two unconstrained parameters.
Numbers of observed and expected events in the 00-enhanced signal regions, before the fit. The total uncertainties are quoted.
Summary of the relative uncertainties in the measured longitudinal-longitudinal fractions $f_{00}$. The uncertainties are reported as percentages.
Numbers of observed and expected events in the 00-enhanced signal regions, after the fit. The total uncertainties are quoted.
$|\Delta Y(l_{W}Z)|$ Migration matrix RAZ Region $p_{T}^{WZ}< 20$ GeV of the TT state.
$|\Delta Y(l_{W}Z)|$ Migration matrix RAZ Region $p_{T}^{WZ}< 40$ GeV of the TT state.
$|\Delta Y(l_{W}Z)|$ Migration matrix RAZ Region $p_{T}^{WZ}< 70$ GeV of the TT state.
$|\Delta Y(l_{W}Z)|$ Migration matrix RAZ Region $p_{T}^{WZ}< 20$ GeV of of the sum of all polarization.
$|\Delta Y(l_{W}Z)|$ Migration matrix RAZ Region $p_{T}^{WZ}< 40$ GeV of of the sum of all polarization.
$|\Delta Y(l_{W}Z)|$ Migration matrix RAZ Region $p_{T}^{WZ}< 70$ GeV of of the sum of all polarization.
$|\Delta Y(WZ)|$ Migration matrix RAZ Region $p_{T}^{WZ}< 20$ GeV of the TT state.
$|\Delta Y(WZ)|$ Migration matrix RAZ Region $p_{T}^{WZ}< 40$ GeV of the TT state.
$|\Delta Y(WZ)|$ Migration matrix RAZ Region $p_{T}^{WZ}< 70$ GeV of the TT state.
$|\Delta Y(WZ)|$ Migration matrix RAZ Region $p_{T}^{WZ}< 20$ GeV of of the sum of all polarization.
$|\Delta Y(WZ)|$ Migration matrix RAZ Region $p_{T}^{WZ}< 40$ GeV of of the sum of all polarization.
$|\Delta Y(WZ)|$ Migration matrix RAZ Region $p_{T}^{WZ}< 70$ GeV of of the sum of all polarization.
The $\mathcal{D}$ value for the unfolded $|\Delta Y(l_{W}Z)|$ distributions of the TT polarization state as a function of the $p_T^{WZ}$ cut value.
The $\mathcal{D}$ value for the unfolded $|\Delta Y(WZ)|$ distributions of the TT polarization state as a function of the $p_T^{WZ}$ cut value.
Measured normalized differential $|\Delta Y(l_{W}Z)|$ cross-section of the TT state in the RAZ Region $p_{T}^{WZ}< 20$ GeV. The total uncertainties are quoted. The last bin covers all events above the lower end of the bin.
Measured normalized differential $|\Delta Y(l_{W}Z)|$ cross-section of the TT state in the RAZ Region $p_{T}^{WZ}< 40$ GeV. The total uncertainties are quoted. The last bin covers all events above the lower end of the bin.
Measured normalized differential $|\Delta Y(l_{W}Z)|$ cross-section of the TT state in the RAZ Region $p_{T}^{WZ}< 70$ GeV. The total uncertainties are quoted. The last bin covers all events above the lower end of the bin.
Measured normalized differential $|\Delta Y(WZ)|$ cross-section of the TT state in the RAZ Region $p_{T}^{WZ}< 20$ GeV. The total uncertainties are quoted. The last bin covers all events above the lower end of the bin.
Measured normalized differential $|\Delta Y(WZ)|$ cross-section of the TT state in the RAZ Region $p_{T}^{WZ}< 40$ GeV. The total uncertainties are quoted. The last bin covers all events above the lower end of the bin.
Measured normalized differential $|\Delta Y(WZ)|$ cross-section of the TT state in the RAZ Region $p_{T}^{WZ}< 70$ GeV. The total uncertainties are quoted. The last bin covers all events above the lower end of the bin.
Measured normalized differential $|\Delta Y(l_{W}Z)|$ cross-section of the sum of polarization states in the RAZ Region $p_{T}^{WZ}< 20$ GeV. The total uncertainties are quoted. The last bin covers all events above the lower end of the bin.
Measured normalized differential $|\Delta Y(l_{W}Z)|$ cross-section of the sum of polarization states in the RAZ Region $p_{T}^{WZ}< 40$ GeV. The total uncertainties are quoted. The last bin covers all events above the lower end of the bin.
Measured normalized differential $|\Delta Y(l_{W}Z)|$ cross-section of the sum of polarization states in the RAZ Region $p_{T}^{WZ}< 70$ GeV. The total uncertainties are quoted. The last bin covers all events above the lower end of the bin.
Measured normalized differential $|\Delta Y(WZ)|$ cross-section of the sum of polarization states in the RAZ Region $p_{T}^{WZ}< 20$ GeV. The total uncertainties are quoted. The last bin covers all events above the lower end of the bin.
Measured normalized differential $|\Delta Y(WZ)|$ cross-section of the sum of polarization states in the RAZ Region $p_{T}^{WZ}< 40$ GeV. The total uncertainties are quoted. The last bin covers all events above the lower end of the bin.
Measured normalized differential $|\Delta Y(WZ)|$ cross-section of the sum of polarization states in the RAZ Region $p_{T}^{WZ}< 70$ GeV. The total uncertainties are quoted. The last bin covers all events above the lower end of the bin.
Summary of the relative uncertainties in the measured depth of the TT state in the RAZ Region $p_{T}^{WZ}<20$ GeV using $|\Delta Y(l_{W}Z)|$. The uncertainties are reported as percentages.
Summary of the relative uncertainties in the measured depth of the TT state in the RAZ Region $p_{T}^{WZ}<40$ GeV using $|\Delta Y(l_{W}Z)|$. The uncertainties are reported as percentages.
Summary of the relative uncertainties in the measured depth of the TT state in the RAZ Region $p_{T}^{WZ}<70$ GeV using $|\Delta Y(l_{W}Z)|$. The uncertainties are reported as percentages.
Summary of the relative uncertainties in the measured depth of the TT state in the RAZ Region $p_{T}^{WZ}<20$ GeV using $|\Delta Y(WZ)|$. The uncertainties are reported as percentages.
Summary of the relative uncertainties in the measured depth of the TT state in the RAZ Region $p_{T}^{WZ}<40$ GeV using $|\Delta Y(WZ)|$. The uncertainties are reported as percentages.
Summary of the relative uncertainties in the measured depth of the TT state in the RAZ Region $p_{T}^{WZ}<70$ GeV using $|\Delta Y(WZ)|$. The uncertainties are reported as percentages.
Summary of the relative uncertainties in the measured depth of the sum of polarization states in the RAZ Region $p_{T}^{WZ}<20$ GeV using $|\Delta Y(l_{W}Z)|$. The uncertainties are reported as percentages.
Summary of the relative uncertainties in the measured depth of the sum of polarization states in the RAZ Region $p_{T}^{WZ}<40$ GeV using $|\Delta Y(l_{W}Z)|$. The uncertainties are reported as percentages.
Summary of the relative uncertainties in the measured depth of the sum of polarization states in the RAZ Region $p_{T}^{WZ}<70$ GeV using $|\Delta Y(l_{W}Z)|$. The uncertainties are reported as percentages.
Summary of the relative uncertainties in the measured depth of the sum of polarization states in the RAZ Region $p_{T}^{WZ}<20$ GeV using $|\Delta Y(WZ)|$. The uncertainties are reported as percentages.
Summary of the relative uncertainties in the measured depth of the sum of polarization states in the RAZ Region $p_{T}^{WZ}<40$ GeV using $|\Delta Y(WZ)|$. The uncertainties are reported as percentages.
Summary of the relative uncertainties in the measured depth of the sum of polarization states in the RAZ Region $p_{T}^{WZ}<70$ GeV using $|\Delta Y(WZ)|$. The uncertainties are reported as percentages.
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