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The yields and average transverse momenta of pions, kaons, and antiprotons produced at the Fermilab p¯p collider at s=300, 540, 1000, and 1800 GeV are presented and compared with data from the energies reached at the CERN collider. We also present data on the dependence of average transverse momentum 〈pt〉 and particle ratios as a function of charged particle density dNcdη; data for particle densities as high as six times the average value, corresponding to a Bjorken energy density 6 GeV/fm3, are reported. These data are relevant to the search for quark-gluon phase of QCD.
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The observation of the $\Lambda_\mathrm{b}^0 \to$J/$\psi \Lambda \phi$ decay is reported using proton-proton collision data collected at $\sqrt{s} =$ 13 TeV by the CMS experiment at the LHC in 2018, corresponding to an integrated luminosity of 60 fb$^{-1}$. The ratio of the branching fractions $\mathcal{B}(\Lambda_\mathrm{b}^0 \to$J/$\psi \Lambda \phi)/\mathcal{B}(\Lambda_\mathrm{b}^0\to\psi \Lambda)$ is measured to be (8.26$\pm$0.90 (stat) $\pm$ 0.68 (syst) $\pm$ 0.11 $(\mathcal{B}))\times $10$^{-2}$, where the first uncertainty is statistical, the second is systematic, and the last uncertainty reflects the uncertainties in the world-average branching fractions of $\phi$ and $\psi$(2S) decays to the reconstructed final states.
The measured ratio of branching fractions
Inclusive and differential fiducial cross sections of the Higgs boson are measured in the $H \to ZZ^{*} \to 4\ell$ ($\ell = e,\mu$) decay channel. The results are based on proton$-$proton collision data produced at the Large Hadron Collider at a centre-of-mass energy of 13 TeV and recorded by the ATLAS detector from 2015 to 2018, equivalent to an integrated luminosity of 139 fb$^{-1}$. The inclusive fiducial cross section for the $H \to ZZ^{*} \to 4\ell$ process is measured to be $\sigma_\mathrm{fid} = 3.28 \pm 0.32$ fb, in agreement with the Standard Model prediction of $\sigma_\mathrm{fid, SM} = 3.41 \pm 0.18 $ fb. Differential fiducial cross sections are measured for a variety of observables which are sensitive to the production and decay of the Higgs boson. All measurements are in agreement with the Standard Model predictions. The results are used to constrain anomalous Higgs boson interactions with Standard Model particles.
Fractional uncertainties for the inclusive fiducial and total cross sections, and range of systematic uncertainties for the differential measurements. The columns e/$\mu$ and jets represent the experimental uncertainties in lepton and jet reconstruction and identification, respectively. The Z + jets, $t\bar{t}$, tXX (Other Bkg.) column includes uncertainties related to the estimation of these background sources. The $ZZ^{*}$ theory ($ZZ^{*}$ th.) uncertainties include the PDF and scale variations. Signal theory (Sig th.) uncertainties include PDF choice, QCD scale, and shower modelling of the signal. Finally, the column labelled Comp. contains uncertainties related to production mode composition and unfolding bias which affect the response matrices. The uncertainties have been rounded to the nearest 0.5%, except for the luminosity uncertainty which has been measured to be 1.7%.
Expected (pre-fit) and observed number of events in the four decay final states after the event selection, in the mass range 115< $m_{4l}$ < 130 GeV. The sum of the expected number of SM Higgs boson events and the estimated background yields is compared to the data. Combined statistical and systematic uncertainties are included for the predictions.
The fiducial and total cross sections of Higgs boson production measured in the 4l final state. The fiducial cross sections are given separately for each decay final state, and for same- and different-flavour decays. The inclusive fiducial cross section is measured as the sum of all final states ($\sigma_{sum}$), as well as by combining the per-final state measurements assuming SM $ZZ^{*} \to 4l$ relative branching ratios ($\sigma_{comb}$). For the total cross section ($\sigma_{tot}$), the Higgs boson branching ratio at $m_{H}$= 125 GeV is assumed. The total SM prediction is accurate to N3LO in QCD and NLO EW for the ggF process. The cross sections for all other Higgs boson production modes XH are added. For the fiducial cross section predictions, the SM cross sections are multiplied by the acceptances determined using the NNLOPS sample for ggF. The p-values indicating the compatibility of the measurement and the SM prediction are shown as well. They do not include the systematic uncertainty in the theoretical predictions.
Correlation matrix between the fiducial cross sections for the four individual decay final states and the $ZZ^{*}$ normalisation factor.
Differential fiducial cross section for the transverse momentum $p_{T}^{4l}$ of the Higgs boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 . Measured value in the last bin is un upper limit at 95% CL.
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum $p_{T}^{4l}$ of the Higgs boson.
Differential fiducial cross section for the invariant mass $m_{12}$ of the leading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass $m_{12}$ of the leading Z boson.
Differential fiducial cross section for the invariant mass $m_{34}$ of the subleading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass $m_{34}$ of the subleading Z boson.
Differential fiducial cross section for the rapidity $|y_{4l}|$ of the Higgs boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the rapidity $|y_{4l}|$ of the Higgs boson.
Differential fiducial cross section for the production angle $|\cos\theta^{*}|$ of the leading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the production angle $|\cos\theta^{*}|$ of the leading Z boson.
Differential fiducial cross section for the production angle $\cos\theta_{1}$ of the anti-lepton from the leading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the production angle $\cos\theta_{1}$ of the anti-lepton from the leading Z boson.
Differential fiducial cross section for the production angle $\cos\theta_{2}$ of the anti-lepton from the subleading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the production angle $\cos\theta_{2}$ of the anti-lepton from the subleading Z boson.
Differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons.
Differential fiducial cross section for the azimuthal angle $\phi_{1}$ of the decay plane of the leading Z boson and the plane formed between its four-momentum and the z-axis. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the azimuthal angle $\phi_{1}$ of the decay plane of the leading Z boson and the plane formed between its four-momentum and the z-axis.
Differential fiducial cross section for the jet multiplicity $N_{jets}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the jet multiplicity $N_{jets}$.
Differential fiducial cross section for the inclusive jet multiplicity $N_{jets}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Differential fiducial cross section for the number of b-quark initiated jets $N_{b-jets}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the number of b-quark initiated jets $N_{b-jets}$.
Differential fiducial cross section for the transverse momentum of the leading jet $p_{T}^{lead.jet}$ in events with at least one jet. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the leading jet $p_{T}^{lead.jet}$ in events with at least one jet.
Differential fiducial cross section for the transverse momentum of the subleading jet $p_{T}^{sublead.jet}$ in events with at least two jets. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the subleading jet $p_{T}^{sublead.jet}$ in events with at least two jets.
Differential fiducial cross section for the invariant mass of the two highest-pT jets $m_{jj}$ in events with at least two jets. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass of the two highest-pT jets $m_{jj}$ in events with at least two jets.
Differential fiducial cross section for the distance between the two highest-pT jets in pseudorapidity $\Delta\eta_{jj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the distance between the two highest-pT jets in pseudorapidity $\Delta\eta_{jj}$.
Differential fiducial cross section for the distance between the two highest-pT jets in $\phi$ $\Delta\phi_{jj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the distance between the two highest-pT jets in $\phi$ $\Delta\phi_{jj}$.
Differential fiducial cross section for the transverse momentum of the four lepton plus jet system, in events with at least one jet $p_{T}^{4lj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the four lepton plus jet system, in events with at least one jet $p_{T}^{4lj}$.
Differential fiducial cross section for the transverse momentum of the four lepton plus di-jet system, in events with at least two jets $p_{T}^{4ljj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 . Measured value in the last bin is un upper limit at 95% CL.
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the four lepton plus di-jet system, in events with at least two jets $p_{T}^{4ljj}$.
Differential fiducial cross section for the invariant mass of the four lepton plus jet system in events with at least one jet $m_{4lj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass of the four lepton plus jet system in events with at least one jet $m_{4lj}$.
Differential fiducial cross section for the invariant mass of the four lepton plus di-jet system in events with at least two jets $m_{4ljj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass of the four lepton plus di-jet system in events with at least two jets $m_{4ljj}$.
Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$.
Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $ll\mu\mu$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $llee$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the leading vs. subleading Z boson mass m12 vs. m34 in $ll\mu\mu$ and $llee$ final states.
Differential fiducial cross section of the $p_{T}^{4l}$ distribution in $|y_{4l}|$ bins. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section of the $p_{T}^{4l}$ distribution in $|y_{4l}|$ bins.
Differential fiducial cross section of the $p_{T}^{4l}$ distribution in $N_{jets}$ bins. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section of the $p_{T}^{4l}$ distribution in $N_{jets}$ bins.
Differential fiducial cross section for transverse momentum of the four lepton system vs. the transverse momentum of the four lepton plus jet system $p_{T}^{4l}$vs.$p_{T}^{4lj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for transverse momentum of the four lepton system vs. the transverse momentum of the four lepton plus jet system $p_{T}^{4l}$vs.$p_{T}^{4lj}$.
Differential fiducial cross section for the transverse momentum of the four lepton plus jet system vs the invariant mass of the four lepton plus jet system $p_{T}^{4l}$vs.$m_{4lj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the four lepton plus jet system vs the invariant mass of the four lepton plus jet system $p_{T}^{4l}$vs.$m_{4lj}$.
Differential fiducial cross section for the transverse momentum of the four lepton vs the transverse momentum of the leading jet $p_{T}^{4l}$vs.$p_{T}^{l.jet}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the four lepton vs the transverse momentum of the leading jet $p_{T}^{4l}$vs.$p_{T}^{lead.jet}$.
Differential fiducial cross section for the transverse momentum of the leading jet vs the rapidity of the leading jet $p_{T}^{lead.jet}$vs.$|y^{lead.jet}|$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the leading jet vs the rapidity of the leading jet $p_{T}^{lead.jet}$vs.$|y^{lead.jet}|$.
Differential fiducial cross section for the transverse momentum of the leading jet vs the transverse momentum of the subleading jet $p_{T}^{lead.jet}$vs.$p_{T}^{sublead.jet}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the leading jet vs the transverse momentum of the subleading jet $p_{T}^{lead.jet}$vs.$p_{T}^{sublead.jet}$.
Differential fiducial cross section for the leading Z boson mass $m_{12}$ in $4\mu$ and $4e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Differential fiducial cross section for the leading Z boson mass $m_{12}$ in $2e2\mu$ and $2\mu2e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the leading Z boson mass $m_{12}$ in $4l$ and $2l2l$ final states.
Differential fiducial cross section for the subleading Z boson mass $m_{34}$ in $4\mu$ and $4e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Differential fiducial cross section for the subleading Z boson mass $m_{34}$ in $2e2\mu$ and $2\mu2e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the subleading Z boson mass $m_{34}$ in $4l$ and $2l2l$ final states.
Differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons in $4\mu$ and $4e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons in $2e2\mu$ and $2\mu2e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons in $4l$ and $2l2l$ final states.
Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $4\mu$ and $4e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $2\mu2e$ and $2e2\mu$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $4l$ and $2l2l$ final states.
The Standard Model of particle physics encapsulates our current best understanding of physics at the smallest scales. A fundamental axiom of this theory is the universality of the couplings of the different generations of leptons to the electroweak gauge bosons. The measurement of the ratio of the rate of decay of $W$ bosons to $\tau$-leptons and muons, $R(\tau/\mu) = B(W \to \tau \nu_\tau)/B(W \to \mu \nu_\mu)$, constitutes an important test of this axiom. A measurement of this quantity with a novel technique using di-leptonic $t\bar{t}$ events is presented based on 139 fb${}^{-1}$ of data recorded with the ATLAS detector in proton--proton collisions at $\sqrt{s}=13$ TeV. Muons originating from $W$ bosons and those originating from an intermediate $\tau$-lepton are distinguished using the lifetime of the $\tau$-lepton, through the muon transverse impact parameter, and differences in the muon transverse momentum spectra. The value of $R(\tau/\mu)$ is found to be $0.992 \pm 0.013 [\pm 0.007 (stat) \pm 0.011 (syst)]$ and is in agreement with the hypothesis of universal lepton couplings as postulated in the Standard Model. This is the most precise measurement of this ratio, and the only such measurement from the Large Hadron Collider, to date.
The number of data and fitted simulated events in each bin of the $|d_{0}^{\mu}|$ distribution in the $5<p_{\textrm{T}}^{\mu}<10$ GeV selection in the $e-\mu$ channel.
The number of data and fitted simulated events in each bin of the $|d_{0}^{\mu}|$ distribution in the $5<p_{\textrm{T}}^{\mu}<10$ GeV selection in the $\mu-\mu$ channel.
The number of data and fitted simulated events in each bin of the $|d_{0}^{\mu}|$ distribution in the $10<p_{\textrm{T}}^{\mu}<20$ GeV selection in the $e-\mu$ channel.
The number of data and fitted simulated events in each bin of the $|d_{0}^{\mu}|$ distribution in the $10<p_{\textrm{T}}^{\mu}<20$ GeV selection in the $\mu-\mu$ channel.
The number of data and fitted simulated events in each bin of the $|d_{0}^{\mu}|$ distribution in the $20<p_{\textrm{T}}^{\mu}<250$ GeV selection in the $e-\mu$ channel.
The number of data and fitted simulated events in each bin of the $|d_{0}^{\mu}|$ distribution in the $20<p_{\textrm{T}}^{\mu}<250$ GeV selection in the $\mu-\mu$ channel.
The measurement of the ratio of the rate of decay of W bosons to τ-leptons and muons, $R(\tau/\mu)=B(W\rightarrow\tau\nu_\tau)/B(W\rightarrow \mu\nu_\mu)$.
A search is described for the production of a pair of bottom-type vector-like quarks (VLQs), each decaying into a b or $\mathrm{\bar{b}}$ quark and either a Higgs or a Z boson, with a mass greater than 1000 GeV. The analysis is based on data from proton-proton collisions at a 13 TeV center-of-mass energy recorded at the CERN LHC, corresponding to a total integrated luminosity of 137 fb$^{-1}$. As the predominant decay modes of the Higgs and Z bosons are to a pair of quarks, the analysis focuses on final states consisting of jets resulting from the six quarks produced in the events. Since the two jets produced in the decay of a highly Lorentz-boosted Higgs or Z boson can merge to form a single jet, nine independent analyses are performed, categorized by the number of observed jets and the reconstructed event mode. No signal in excess of the expected background is observed. Lower limits are set on the VLQ mass at 95% confidence level equal to 1570 GeV in the case where the VLQ decays exclusively to a b quark and a Higgs boson, 1390 GeV for when it decays exclusively to a b quark and a Z boson, and 1450 GeV for when it decays equally in these two modes. These limits represent significant improvements over the previously published VLQ limits.
Measured values of the trigger efficiencies for events with $\HT > 1350\GeV$. The uncertainties are statistical only.
Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).
Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).
Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).
Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).
Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).
Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).
Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).
Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).
Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).
Distribution of $\chi^{2}$/ndf for the best jet combination for simulated 1200\GeV VLQ events (red histogram) and data (black points), for 4-jet events (left), 5-jet events (center), and 6-jet events (right). The simulated signal events and data events are normalized to the same value within the displayed $\chi^{2}$/ndf range.
Distribution of $\chi^{2}$/ndf for the best jet combination for simulated 1200\GeV VLQ events (red histogram) and data (black points), for 4-jet events (left), 5-jet events (center), and 6-jet events (right). The simulated signal events and data events are normalized to the same value within the displayed $\chi^{2}$/ndf range.
Distribution of $\chi^{2}$/ndf for the best jet combination for simulated 1200\GeV VLQ events (red histogram) and data (black points), for 4-jet events (left), 5-jet events (center), and 6-jet events (right). The simulated signal events and data events are normalized to the same value within the displayed $\chi^{2}$/ndf range.
Distributions of the average reconstructed mass of VLQ candidates for the jet combination with the least $\chi^{2}$ in 4-jet (left), 5-jet (center), and 6-jet (right) multiplicity events. The red lines show the exponential fit in the range 1000-2000 GeV. The lower panels show the fractional difference, (data-fit)/fit
Distributions of the average reconstructed mass of VLQ candidates for the jet combination with the least $\chi^{2}$ in 4-jet (left), 5-jet (center), and 6-jet (right) multiplicity events. The red lines show the exponential fit in the range 1000-2000 GeV. The lower panels show the fractional difference, (data-fit)/fit
Distributions of the average reconstructed mass of VLQ candidates for the jet combination with the least $\chi^{2}$ in 4-jet (left), 5-jet (center), and 6-jet (right) multiplicity events. The red lines show the exponential fit in the range 1000-2000 GeV. The lower panels show the fractional difference, (data-fit)/fit
Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.
The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.
Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.
Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.
Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.
Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.
Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.
Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.
Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.
Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.
Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.
Expected limits on the VLQ mass at 95% CL as a function of the branching fractions $\mathcal{B}$( B -> bH ) and $\mathcal{B}$( B -> bZ)
Observed limits on the VLQ mass at 95% CL as a function of the branching fractions $\mathcal{B}$( B -> bH ) and $\mathcal{B}$( B -> bZ)
The 95% confidence limit on the cross section for VLQ pair production as a function of VLQ mass for three branching fraction hypotheses: B( B -> bH ) = 100% (upper left), B( B -> bZ ) = 100% (upper right), and and B( B -> bH ) = B( B -> bZ ) = 50% (lower). The solid black line indicates the observed limit and the dashed line indicates the expected limit with 1 sigma (green band) and 2 sigma (yellow band) uncertainties. The theoretical cross section and its uncertainty are shown as the red line and pale red band.
The 95% confidence limit on the cross section for VLQ pair production as a function of VLQ mass for three branching fraction hypotheses: B( B -> bH ) = 100% (upper left), B( B -> bZ ) = 100% (upper right), and and B( B -> bH ) = B( B -> bZ ) = 50% (lower). The solid black line indicates the observed limit and the dashed line indicates the expected limit with 1 sigma (green band) and 2 sigma (yellow band) uncertainties. The theoretical cross section and its uncertainty are shown as the red line and pale red band.
The 95% confidence limit on the cross section for VLQ pair production as a function of VLQ mass for three branching fraction hypotheses: B( B -> bH ) = 100% (upper left), B( B -> bZ ) = 100% (upper right), and and B( B -> bH ) = B( B -> bZ ) = 50% (lower). The solid black line indicates the observed limit and the dashed line indicates the expected limit with 1 sigma (green band) and 2 sigma (yellow band) uncertainties. The theoretical cross section and its uncertainty are shown as the red line and pale red band.
The ATLAS experiment at the Large Hadron Collider reports a search for charged-lepton-flavour violation in decays of $Z$ bosons into a τ lepton and an electron or muon of opposite charge.
The best-fit expected and observed distributions of the combined NN output in the CRZ$\tau\tau$ for the $\mu\tau$ channel for events with 1-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the CRZ$\tau\tau$ for the $\mu\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the VRSS for the $e\tau$ channel for events with 1-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the VRSS for the $e\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the SR for the $e\tau$ channel for events with 1-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the SR for the $e\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the SR for the $\mu\tau$ channel for events with 1-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the SR for the $\mu\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
Observed and expected upper limits on $\mathcal{B}(Z\rightarrow\ell\tau)$ at 95% confidence level.
This paper presents a search for dark matter in the context of a two-Higgs-doublet model together with an additional pseudoscalar mediator, $a$, which decays into the dark-matter particles. Processes where the pseudoscalar mediator is produced in association with a single top quark in the 2HDM+$a$ model are explored for the first time at the LHC. Several final states which include either one or two charged leptons (electrons or muons) and a significant amount of missing transverse momentum are considered. The analysis is based on proton-proton collision data collected with the ATLAS experiment at $\sqrt{s} = 13$ TeV during LHC Run2 (2015-2018), corresponding to an integrated luminosity of 139 fb$^{-1}$. No significant excess above the Standard Model predictions is found. The results are expressed as 95% confidence-level limits on the parameters of the signal models considered.
Efficiencies of the DMt samples in the tW1L channel for all bins in the SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
Acceptances on TRUTH level of the DMt samples in the tW1L channel for all bins in the SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
Efficiencies of the DMt samples in the tW1L channel for all bins in the SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Acceptances on TRUTH level of the DMt samples in the tW1L channel for all bins in the SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Efficiencies of the DMt samples in the tW2L SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
Acceptances on TRUTH level of the DMt samples in the tW2L SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
Efficiencies of the DMt samples in the tW2L SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Acceptances on TRUTH level of the DMt samples in the tW2L SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Efficiencies of the DMt samples in the tj1L channel for all bins in the SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The map includes all used samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Acceptances on TRUTH level of the DMt samples in the tj1L channel for all bins in the SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The map includes all used samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering only DMt signal.
Upper limits on excluded cross sections of the tW1L analysis considering only the DMt signal.
The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW1L analysis channel.
The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW1L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering only DMt signal.
Upper limits on excluded cross sections of the tW1L analysis considering only the DMt signal.
The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW1L analysis channel.
The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW1L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering only DMt signal.
Upper limits on excluded cross sections of the tW2L analysis considering only the DMt signal.
The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW2L analysis channel.
The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering only DMt signal.
Upper limits on excluded cross sections of the tW2L analysis considering only the DMt signal.
The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW2L analysis channel.
The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering only the DMt signal.
Upper limits on excluded cross sections of the combined tW1L and tW2L analyses considering only the DMt signal.
The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.
The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering only the DMt signal.
Upper limits on excluded cross sections of the combined tW1L and tW2L analyses considering only the DMt signal.
The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.
The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering the DMt$\bar{t}$+DMt signal.
The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.
The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering the DMt$\bar{t}$+DMt signal.
The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.
The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering the DMt$\bar{t}$+DMt signal.
The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.
The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering the DMt$\bar{t}$+DMt signal.
The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.
The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering the DMt$\bar{t}$+DMt signal.
The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.
The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering the DMt$\bar{t}$+DMt signal.
The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.
The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tj1L analysis considering only the DMt signal.
Upper limits on upper limits on excluded cross sections of the tj1L analysis considering only the DMt signal.
The expected and observed cross section exclusion limits as a function of $m_{H^{\pm}}$ in the tj1L analysis channel for signal models with $m_a = 250~GeV$, and $\tan\beta=0.3$. The $\sigma^{}_\mathrm{BSM}$ is the cross section of the $t$-channel DM production process.
The expected and observed cross section exclusion limits as a function of $m_{H^{\pm}}$ in the tj1L analysis channel for signal models with $m_a = 250~GeV$, and $\tan\beta=0.5$. The $\sigma^{}_\mathrm{BSM}$ is the cross section of the $t$-channel DM production process.
Cross sections of the DMt samples in the tW1L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
Cross sections of the DMt samples in the tW1L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Cross sections times branching ratio of the DMt samples in the tW2L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
Cross sections times branching ratio of the DMt samples in the tW2L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Cross sections of the DMt samples in the tj1L channel. The map includes all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
MC generator filter efficiencies of the DMt samples in the tW1L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
MC generator filter efficiencies of the DMt samples in the tW1L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
MC generator filter efficiencies of the DMt samples in the tW2L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
MC generator filter efficiencies of the DMt samples in the tW2L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
MC generator filter efficiencies of the DMt samples in the tj1L channel. The map includes all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Background-only fit results for the tW1L and tW2L signal regions. The backgrounds which contribute only a small amount (rare processes such as triboson, Higgs boson production processes, $t\bar{t}t\bar{t}$, $t\bar{t}WW$ and non-prompt or misidentified leptons background) are grouped and labelled as ``Others´´. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Background-only fit results for the tj1L signal regions. The backgrounds which contribute only a small amount ($Z$+jets, rare processes such as $tWZ$, triboson, Higgs boson production processes, ,$t\bar{t}t\bar{t}$, $t\bar{t}WW$) are grouped and labelled as ``Others´´. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Cutflow of the weighted events with statistical uncertainties for two DMt samples in all bins of the tW1L channel. The PreSelection includes at least 1 lepton in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 50~GeV$, $m\mathrm{_{T}^{lep}} > 30~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.
Cutflow of the weighted events with statistical uncertainties for two DMt samples in the tW2L channel. The PreSelection includes at least 2 leptons in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 40~GeV$, $m_{ll} > 40~GeV$, $m\mathrm{_{T2}} > 40~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.
Cutflow of the weighted events with the statistical uncertainties (except for the first cuts) for two DMt samples in all bins off the tj1L channel. The PreSelection includes at least 1 lepton in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 50~GeV$, $m\mathrm{_{T}^{lep}} > 30~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.
The results of a search for gluino and squark pair production with the pairs decaying via the lightest charginos into a final state consisting of two $W$ bosons, the lightest neutralinos ($\tilde\chi^0_1$), and quarks, are presented. The signal is characterised by the presence of a single charged lepton ($e^{\pm}$ or $\mu^{\pm}$) from a $W$ boson decay, jets, and missing transverse momentum. The analysis is performed using 139 fb$^{-1}$ of proton-proton collision data taken at a centre-of-mass energy $\sqrt{s}=13$ TeV delivered by the Large Hadron Collider and recorded by the ATLAS experiment. No statistically significant excess of events above the Standard Model expectation is found. Limits are set on the direct production of squarks and gluinos in simplified models. Masses of gluino (squark) up to 2.2 TeV (1.4 TeV) are excluded at 95% confidence level for a light $\tilde\chi^0_1$.
Post-fit $m_{T}$ distribution in the SR 2J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 2J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 2J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 2J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Pre-fit $m_{eff}$ distribution in the TR6J control region. Uncertainties include statistical and systematic uncertainties (added in quadrature). The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Pre-fit $m_{eff}$ distribution in the WR6J control region. Uncertainties include statistical and systematic uncertainties (added in quadrature). The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the TR6J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the WR6J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J high-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J high-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J high-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Post-fit $m_{eff}$ distribution in the 4J high-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model. space.
Post-fit $m_{eff}$ distribution in the 6J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Observed 95% CL exclusion contours for the gluino one-step variable-x
Post-fit $m_{eff}$ distribution in the 6J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Expected 95% CL exclusion contours for the gluino one-step variable-x
Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model. space.
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Observed 95% CL exclusion contours for the gluino one-step variable-x
Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.
Expected 95% CL exclusion contours for the gluino one-step variable-x
Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-step variable-x
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-step variable-x
Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Expected 95% CL exclusion contours for the squark one-step variable-x
Upper limits on the signal cross section for simplified model gluino one-step x = 1/2
Expected 95% CL exclusion contours for the squark one-step variable-x
Upper limits on the signal cross section for simplified model gluino one-step variable-x
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Upper limits on the signal cross section for simplified model squark one-step x = 1/2
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Upper limits on the signal cross section for simplified model squark one-step variable-x
Upper limits on the signal cross section for simplified model gluino one-step x = 1/2
Upper limits on the signal cross section for simplified model squark one-step x=1/2 in one-flavour schemes
Upper limits on the signal cross section for simplified model gluino one-step variable-x
Upper limits on the signal cross section for simplified model squark one-step variable-x in one-flavour schemes
Upper limits on the signal cross section for simplified model squark one-step x = 1/2
Post-fit $m_{eff}$ distribution in the 2J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Upper limits on the signal cross section for simplified model squark one-step variable-x
Post-fit $m_{eff}$ distribution in the 2J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Upper limits on the signal cross section for simplified model squark one-step x=1/2 in one-flavour schemes
Post-fit $m_{eff}$ distribution in the 4J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Upper limits on the signal cross section for simplified model squark one-step variable-x in one-flavour schemes
Post-fit $m_{eff}$ distribution in the 4J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the TR2J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-tag validation region. Uncertainties include statistical and systematic uncertainties.
Post-fit $m_{eff}$ distribution in the WR2J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-veto validation region. Uncertainties include statistical and systematic uncertainties.
Post-fit $m_{eff}$ distribution in the TR4J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR2JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the WR4J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR2JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 2J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR4JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 2J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR4JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 4J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR6JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 4J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR6JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 6J b-tag validation region. Uncertainties include statistical and systematic uncertainties.
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Post-fit $m_{eff}$ distribution in the 6J b-veto validation region. Uncertainties include statistical and systematic uncertainties.
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR2JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR2JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR4JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR4JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR6JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J discovery high region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR6JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J discovery high region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J discovery low region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J discovery high region for squark production one-step variable-x simplified models
Signal efficiency in SR2J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J discovery low region for squark production one-step variable-x simplified models
Signal efficiency in SR2J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
A search for charged Higgs bosons decaying into $W^\pm W^\pm$ or $W^\pm Z$ bosons is performed, involving experimental signatures with two leptons of the same charge, or three or four leptons with a variety of charge combinations, missing transverse momentum and jets. A data sample of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018 is used. The data correspond to a total integrated luminosity of 139 fb$^{-1}$. The search is guided by a type-II seesaw model that extends the scalar sector of the Standard Model with a scalar triplet, leading to a phenomenology that includes doubly and singly charged Higgs bosons. Two scenarios are explored, corresponding to the pair production of doubly charged $H^{\pm\pm}$ bosons, or the associated production of a doubly charged $H^{\pm\pm}$ boson and a singly charged $H^\pm$ boson. No significant deviations from the Standard Model predictions are observed. $H^{\pm\pm}$ bosons are excluded at 95% confidence level up to 350 GeV and 230 GeV for the pair and associated production modes, respectively.
Distribution of $E_{T}^{miss}$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $\Delta R_{\ell^{\pm}\ell^{\pm}}$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $M_{jets}$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $S$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $E_{T}^{miss}$, which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $\Delta R_{\ell^{\pm}\ell^{\pm}}$, which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $m_{x\ell}$ ($x$=3), which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $p_{T}^{leading jet}$, which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $E_{T}^{miss}$, which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $\Delta R_{\ell^{\pm}\ell^{\pm}}^{min}$, which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $m_{x\ell}$ ($x$=4), which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $p_{T}^{\ell_{1}}$, which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Contributions from different categories of uncertainties relative to the expected background yields in the defined SRs, as obtained after performing the likelihood ratio test discussed in Section 9 in the paper. The uncertainties are shown for the combination of the individual channels of the $2\ell^{sc}$, $3\ell$ and $4\ell$ SRs. The SRs are indicated along the horizontal axis. In the HEPData entry, the x-axis is simplified for easier visualisation. The first number indicates the sub channel (2:$2\ell^{sc}$, 3:$3\ell$, 4:$4\ell$), while the second number indicates the mass point (2:200, 3:300, 4:400, 5:500).
Data event yields compared with the expected contributions from relevant background sources, for the combination of the individual channels of the $2\ell^{sc}$, $3\ell$ and $4\ell$ SRs. The total uncertainties in the expected event yields are shown as the hatched bands. The SRs are indicated along the horizontal axis. In the HEPData entry, the x-axis is simplified for easier visualisation. The first number indicates the sub channel (2:$2\ell^{sc}$, 3:$3\ell$, 4:$4\ell$), while the second number indicates the mass point (2:200, 3:300, 4:400, 5:500).
The $E_{T}^{miss}$ distribution for the SRs of the $m_{H^{\pm\pm}} = 300~GeV$ signal mass hypothesis, where the selection requirement on $E_{T}^{miss}$ has been removed. In the attached plot, the signals are stacked on top of the backgrounds while individuals contributions of the $2\ell^{sc}$ channel are shown in HEPData. The last bin, isolated by a vertical red dashed line, is inclusive and corresponds to the SR.
The $E_{T}^{miss}$ distribution for the SRs of the $m_{H^{\pm\pm}} = 300~GeV$ signal mass hypothesis, where the selection requirement on $E_{T}^{miss}$ has been removed. In the attached plot, the signals are stacked on top of the backgrounds while individuals contributions of the $3\ell$ channel are shown in HEPData. The last bin, isolated by a vertical red dashed line, is inclusive and corresponds to the SR.
The $E_{T}^{miss}$ distribution for the SRs of the $m_{H^{\pm\pm}} = 300~GeV$ signal mass hypothesis, where the selection requirement on $E_{T}^{miss}$ has been removed. In the attached plot, the signals are stacked on top of the backgrounds while individuals contributions of the $4\ell$ channel are shown in HEPData. The last bin, isolated by a vertical red dashed line, is inclusive and corresponds to the SR.
Observed and expected upper limits of the $H^{\pm\pm}$ pair production cross section times branching fraction at 95% CL obtained from the combination of 2$\ell^{sc}$, 3$\ell$ and 4$\ell$ channels. The region above the observed limit is excluded by the measurement. The bands represent the expected exclusion curves within one and two standard deviations.
The theoretical prediction of Figure 9(a) in the paper.
Observed and expected upper limits of the $H^{\pm\pm}$ and $H^{\pm}$ production cross section times branching fraction at 95% CL obtained from the combination of 2$\ell^{sc}$, 3$\ell$ and 4$\ell$ channels. The region above the observed limit is excluded by the measurement. The bands represent the expected exclusion curves within one and two standard deviations.
The theoretical prediction of Figure 9(b) in the paper.
Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 200~GeV$ or $m_{H^{\pm\pm}} = 220~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).
Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 300~GeV$ or $m_{H^{\pm\pm}} = 350~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).
Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 400~GeV$ or $m_{H^{\pm\pm}} = 450~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).
Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 500~GeV$ or $m_{H^{\pm\pm}} = 550~GeV$ or $m_{H^{\pm\pm}} = 600~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).
A search is presented for long-lived particles produced in pairs in proton-proton collisions at the LHC operating at a center-of-mass energy of 13 TeV. The data were collected with the CMS detector during the period from 2015 through 2018, and correspond to a total integrated luminosity of 140 fb$^{-1}$. This search targets pairs of long-lived particles with mean proper decay lengths between 0.1 and 100 mm, each of which decays into at least two quarks that hadronize to jets, resulting in a final state with two displaced vertices. No significant excess of events with two displaced vertices is observed. In the context of $R$-parity violating supersymmetry models, the pair production of long-lived neutralinos, gluinos, and top squarks is excluded at 95% confidence level for cross sections larger than 0.08 fb, masses between 800 and 3000 GeV, and mean proper decay lengths between 1 and 25 mm.
Event yields in the control samples in data. The ''one-vertex'' events correspond to events containing exactly one vertex with the specified number of tracks. The ''two-vertex'' events have two or more vertices containing the specified numbers of tracks. We seek the signal in the $\geq$5-track two-vertex sample.
The distribution of distances between vertices in the $x$-$y$ plane, $d_{\mathrm{VV}}$, for three simulated multijet signals each with a mass of 1600 GeV, with the background template distribution overlaid. The production cross section for each signal model is assumed to be the lower limit excluded by CMS-EXO-17-018, corresponding to values of 0.8, 0.25, and 0.15 fb for the samples with $c\tau =$ 0.3, 1.0, and 10 mm, respectively. The last bin includes the overflow events. The two vertical pink dashed lines separate the regions used in the fit.
Multijet signal efficiencies as a function of the signal mass and lifetime for events satisfying all event and vertex requirements, with corrections based on systematic differences in the vertex reconstruction efficiency between data and simulation.
Dijet signal efficiencies as a function of the signal mass and lifetime for events satisfying all event and vertex requirements, with corrections based on systematic differences in the vertex reconstruction efficiency between data and simulation.
The distribution of $d_{\mathrm{BV}}$ for $\geq$5-track one-vertex events in data and three simulated multijet signal samples each with a mass of 1600 GeV. The production cross section for each signal model is assumed to be the lower limit excluded by CMS-EXO-17-018, corresponding to values of 0.8, 0.25, and 0.15 fb for the samples with $c\tau =$ 0.3, 1.0, and 10 mm, respectively. The last bin includes the overflow events. This bin includes one event in data with a vertex with large $d_{\mathrm{BV}}$ that appears to arise from tracks originating from separate pp interaction vertices, consistent with background.
Distribution of the $x$-$y$ distances between vertices, $d_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution $d_{\mathrm{VV}}^{\kern 0.15em\mathrm{C}}$ (blue continuous line) is constructed from one-vertex events in data, and is normalized to the number of two-vertex events in data with two 3-track vertices. The two vertical red dashed lines separate the regions used in the fit.
Distribution of the $x$-$y$ distances between vertices, $d_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution $d_{\mathrm{VV}}^{\kern 0.15em\mathrm{C}}$ (blue continuous line) is constructed from one-vertex events in data, and is normalized to the number of two-vertex events in data which have exactly one 4-track vertex and one 3-track vertex. The two vertical red dashed lines separate the regions used in the fit.
Distribution of the $x$-$y$ distances between vertices, $d_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution $d_{\mathrm{VV}}^{\kern 0.15em\mathrm{C}}$ (blue continuous line) is constructed from one-vertex events in data, and is normalized to the number of two-vertex events in data with two 4-track vertices. The two vertical red dashed lines separate the regions used in the fit.
Distribution of the $x$-$y$ distances between vertices, $d_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution $d_{\mathrm{VV}}^{\kern 0.15em\mathrm{C}}$ (blue continuous line) is constructed from one-vertex events in data, and is normalized using $\geq$5-track one-vertex event information. The two vertical red dashed lines separate the regions used in the fit.
Predicted yields for the background-only normalized template, predicted yields for three simulated multijet signals each with a mass of 1600 GeV, and the observed yield in each $d_{\mathrm{VV}}$ bin. The production cross section for each signal model is assumed to be the lower limit excluded by CMS-EXO-17-018, corresponding to values of 0.8, 0.25, and 0.15 fb for samples with $c\tau =$ 0.3, 1.0, and 10 mm, respectively. The uncertainties in the signal yields and the systematic uncertainties in the background prediction reflect the systematic uncertainties given in the text.
Observed 95% CL upper limits on the product of cross section and branching fraction squared for the multijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the neutralino (red) and gluino (purple) with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.
Observed 95% CL upper limits on the product of cross section and branching fraction squared for the multijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the neutralino (red) and gluino (purple) with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.
Observed 95% CL upper limits on the product of cross section and branching fraction squared for the multijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the neutralino (red) and gluino (purple) with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.
Observed 95% CL upper limits on the product of cross section and branching fraction squared for the dijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the top squark with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.
Observed 95% CL upper limits on the product of cross section and branching fraction squared for the dijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the top squark with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for multijet signals, for a fixed $c\tau$ of 300um in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for dijet signals, for a fixed $c\tau$ of 300um in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for multijet signals, for a fixed $c\tau$ of 1 mm in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for dijet signals, for a fixed $c\tau$ of 1 mm in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for multijet signals, for a fixed $c\tau$ of 10 mm in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for dijet signals, for a fixed $c\tau$ of 10 mm in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for multijet signals, for a fixed mass of 800 GeV in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for dijet signals, for a fixed mass of 800 GeV in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for multijet signals, for a fixed mass of 1600 GeV in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for dijet signals, for a fixed mass of 1600 GeV in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for multijet signals, for a fixed mass of 2400 GeV in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals. For $m$ = 2400 GeV, the expected neutralino cross section is $\approx 8\times 10^{-5}$ fb and is not shown.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for dijet signals, for a fixed mass of 2400 GeV in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.
Data-to-simulation efficiency correction factors, shown for multijet and dijet signal topologies in several ranges of $c\tau$. Note that these correction factors account for the two long-lived particles in the simulated events, and are therefore the total correction factors used to scale event yields rather than the correction factors one would apply to individual vertices.
Distribution of the azimuthal angle between vertices, $\Delta\phi_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution (blue continuous line) is constructed from 3-track one-vertex events in data, and is normalized to the number of 3-track two-vertex events in data.
Distribution of the azimuthal angle between vertices, $\Delta\phi_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution (blue continuous line) is constructed from 4-track and 3-track one-vertex events in data, and is normalized to the number of two-vertex events in data which have exactly one 4-track vertex and one 3-track vertex.
Distribution of the azimuthal angle between vertices, $\Delta\phi_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution (blue continuous line) is constructed from 4-track one-vertex events in data, and is normalized to the number of 4-track two-vertex events in data.
Distribution of the azimuthal angle between vertices, $\Delta\phi_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution (blue continuous line) is constructed from $\geq$5-track one-vertex events in data, and is normalized using one-vertex event information. No $\geq$5-track two-vertex data events pass the selection.
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