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A search for long-lived particles decaying into an oppositely charged lepton pair, $\mu\mu$, $ee$, or $e\mu$, is presented using 32.8 fb$^{-1}$ of $pp$ collision data collected at $\sqrt{s}=13$ TeV by the ATLAS detector at the LHC. Candidate leptons are required to form a vertex, within the inner tracking volume of ATLAS, displaced from the primary $pp$ interaction region. No lepton pairs with an invariant mass greater than 12 GeV are observed, consistent with the background expectations derived from data. The detection efficiencies for generic resonances with lifetimes ($c\tau$) of 100-1000 mm decaying into a dilepton pair with masses between 0.1-1.0 TeV are presented as a function of $p_T$ and decay radius of the resonances to allow the extraction of upper limits on the cross sections for theoretical models. The result is also interpreted in a supersymmetric model in which the lightest neutralino, produced via squark-antisquark production, decays into $\ell^{+}\ell^{'-}\nu$ ($\ell, \ell^{'} = e$, $\mu$) with a finite lifetime due to the presence of R-parity violating couplings. Cross-section limits are presented for specific squark and neutralino masses. For a 700 GeV squark, neutralinos with masses of 50-500 GeV and mean proper lifetimes corresponding to $c\tau$ values between 1 mm to 6 m are excluded. For a 1.6 TeV squark, $c\tau$ values between 3 mm to 1 m are excluded for 1.3 TeV neutralinos.
<h1>Overview of reinterpretation material</h1><p><b>Important note:</b> A detailed explanation of the reinterpretation material can be found <a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2017-04/hepdata_info.pdf">here</a>.<br/>Please read this stand-alone document before reinterpreting the search.</p><h2>Parameterized detection efficiencies</h2><p>RPV SUSY model: Tables <a href="90606?version=1&table=Table27">27</a> to <a href="90606?version=1&table=Table44">44</a><br/>Z' toy model: Tables <a href="90606?version=1&table=Table45">45</a> to <a href="90606?version=1&table=Table59">59</a></p><h2>Further material for the RPV SUSY model</h2><p>Acceptances: Tables <a href="90606?version=1&table=Table18">18</a> (ee), <a href="90606?version=1&table=Table19">19</a> (emu) and <a href="90606?version=1&table=Table20">20</a> (mumu)<br/>Detection efficiencies: Tables <a href="90606?version=1&table=Table21">21</a> (ee), <a href="90606?version=1&table=Table22">22</a> (emu) and <a href="90606?version=1&table=Table23">23</a> (mumu)<br/>Overall signal efficiencies: Tables <a href="90606?version=1&table=Table24">24</a> (ee), <a href="90606?version=1&table=Table25">25</a> (emu) and <a href="90606?version=1&table=Table26">26</a> (mumu)</p><h2>Further material for the Z' toy model</h2><p>Acceptances, detection efficiencies and overall signal efficiencies: Tables <a href="90606?version=1&table=Table60">60</a> (mZ' = 100 GeV) to <a href="90606?version=1&table=Table64">64</a> (mZ' = 1000 GeV)</p>
dRcos distribution of dimuon pairs (scaled) and dimuon vertices in the cosmic rays control region. The distribution of all dimuon pairs is scaled to the DV distribution.
Dependence of the overall signal efficiency on the transverse decay radius Rxy of the long-lived Z' for Z' -> ee. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the pT of the long-lived Z' for Z' -> ee. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the transverse decay radius Rxy of the long-lived Z' for Z' -> emu. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the pT of the long-lived Z' for Z' -> emu. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the transverse decay radius Rxy of the long-lived Z' for Z' -> mumu. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the pT of the long-lived Z' for Z' -> mumu. The error bars indicate the total uncertainties.
Overall signal efficiency as a function of the mean proper lifetime (ctau) of the neutralino for the lambda121 scenario of the RPV SUSY model. The error bars indicate the total uncertainties.
Overall signal efficiency as a function of the mean proper lifetime (ctau) of the neutralino for the lambda122 scenario of the RPV SUSY model. The error bars indicate the total uncertainties.
95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda121 scenario of the RPV SUSY model and a 700 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.
95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda122 scenario of the RPV SUSY model and a 700 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.
95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda121 scenario of the RPV SUSY model and a 1600 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.
95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda122 scenario of the RPV SUSY model and a 1600 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.
Fraction of detector volume covered by the material veto as a function of z and Rxy of the displaced dilepton vertex.
Fraction of detector volume covered by the disabled pixel modules veto veto as a function of z and Rxy of the displaced dilepton vertex.
Observed Rxy distribution of vertices composed of two non-leptonic tracks in a control sample in the data and the predicted distribution obtained from the event mixing. The error bars indicate the statistical uncertainties.
Rxy distributions of Kshort vertices from the large radius tracking in the data and background MC samples. Data has been normalised such that the total number of Kshort from the standard tracking in the data agrees with the total number of Kshort from the standard tracking in the MC. The error bars indicate the statistical uncertainties.
Acceptance per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> eenu. The error bars indicate the statistical uncertainties.
Acceptance per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> emunu. The error bars indicate the statistical uncertainties.
Acceptance per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> mumunu. The error bars indicate the statistical uncertainties.
Detection efficiency per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> eenu. The error bars indicate the total uncertainties.
Detection efficiency per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> emunu. The error bars indicate the total uncertainties.
Detection efficiency per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> mumunu. The error bars indicate the total uncertainties.
Overall signal efficiency (acceptance times efficiency) per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> eenu. The error bars indicate the total uncertainties.
Overall signal efficiency (acceptance times efficiency) per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> emunu. The error bars indicate the total uncertainties.
Overall signal efficiency (acceptance times efficiency) per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> mumunu. The error bars indicate the total uncertainties.
Detection efficiency per decay for Rxy < 22 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 22 <= Rxy < 38 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 38 <= Rxy < 73 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 73 <= Rxy < 111 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 111 <= Rxy < 145 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 145 <= Rxy < 300 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for Rxy < 22 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 22 <= Rxy < 38 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 38 <= Rxy < 73 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 73 <= Rxy < 111 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 111 <= Rxy < 145 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 145 <= Rxy < 300 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for Rxy < 22 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 22 <= Rxy < 38 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 38 <= Rxy < 73 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 73 <= Rxy < 111 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 111 <= Rxy < 145 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 145 <= Rxy < 300 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 100 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 100 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 100 GeV and LLP -> mumu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 250 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 250 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 250 GeV and LLP -> mumu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 500 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 500 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 500 GeV and LLP -> mumu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 750 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 750 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 750 GeV and LLP -> mumu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 1000 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 1000 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 1000 GeV and LLP -> mumu.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 100 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 250 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 500 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 750 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 1000 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Results of a search for new particles decaying into eight or more jets and moderate missing transverse momentum are presented. The analysis uses 139 fb$^{-1}$ of proton$-$proton collision data at $\sqrt{s} = 13$ TeV collected by the ATLAS experiment at the Large Hadron Collider between 2015 and 2018. The selection rejects events containing isolated electrons or muons, and makes requirements according to the number of $b$-tagged jets and the scalar sum of masses of large-radius jets. The search extends previous analyses both in using a larger dataset and by employing improved jet and missing transverse momentum reconstruction methods which more cleanly separate signal from background processes. No evidence for physics beyond the Standard Model is found. The results are interpreted in the context of supersymmetry-inspired simplified models, significantly extending the limits on the gluino mass in those models. In particular, limits on the gluino mass are set at 2 TeV when the lightest neutralino is nearly massless in a model assuming a two-step cascade decay via the lightest chargino and second-lightest neutralino.
Post-fit yields for data and prediction in each of the multi-bin signal regions for the 8 jet regions.
Post-fit yields for data and prediction in each of the multi-bin signal regions for the 9 jet regions.
Post-fit yields for data and prediction in each of the multi-bin signal regions for the 10 jet regions.
Post-fit yields for data and prediction in each of the single-bin signal regions of the analysis.
Observed 95% confidence level limit for the two-step signal grid.
Observed 95% confidence level limit for the two-step signal grid with the signal cross section increased by one sigma.
Observed 95% confidence level limit for the two-step signal grid with the signal cross section decreased by one sigma.
Expected 95% confidence level limit for the two-step signal grid.
Expected 95% confidence level limit for the two-step signal grid plus one sigma from experimental systematics.
Expected 95% confidence level limit for the two-step signal grid minus one sigma from experimental systematics.
Observed 95% confidence level limit for the Gtt signal grid.
Observed 95% confidence level limit for the Gtt signal grid with the signal cross section increased by one sigma.
Observed 95% confidence level limit for the Gtt signal grid with the signal cross section decreased by one sigma.
Expected 95% confidence level limit for the Gtt signal grid.
Expected 95% confidence level limit for the Gtt signal grid plus one sigma from experimental systematics.
Expected 95% confidence level limit for the Gtt signal grid minus one sigma from experimental systematics.
Observed 95% confidence level limit for the RPV signal grid.
Observed 95% confidence level limit for the RPV signal grid with the signal cross section increased by one sigma.
Observed 95% confidence level limit for the RPV signal grid with the signal cross section decreased by one sigma.
Expected 95% confidence level limit for the RPV signal grid.
Expected 95% confidence level limit for the RPV signal grid plus one sigma from experimental systematics.
Expected 95% confidence level limit for the RPV signal grid minus one sigma from experimental systematics.
Observed 95% confidence level limit for the two-step signal grid.
Expected 95% confidence level limit for the two-step signal grid.
Observed 95% confidence level limit for the Gtt signal grid.
Expected 95% confidence level limit for the Gtt signal grid.
Observed 95% confidence level limit for the RPV signal grid.
Expected 95% confidence level limit for the RPV signal grid.
$\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in the signal region SR-10ij50-0ib-MJ340. Two benchmark signal models are shown along with the background yields. These models, each representing a single mass point, are labelled 'RPV' with $(m_{\tilde{g}}, m_{\tilde{t}}) = (1600, 600) \, \mathrm{GeV}$ and 'two-step' with $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
$\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in the signal region SR-12ij50-2ib. Two benchmark signal models are shown along with the background yields. These models, each representing a single mass point, are labelled 'RPV' with $(m_{\tilde{g}}, m_{\tilde{t}}) = (1600, 600) \, \mathrm{GeV}$ and 'two-step' with $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
$\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in the signal region SR-9ij80-0ib. Two benchmark signal models are shown along with the background yields. These models, each representing a single mass point, are labelled 'RPV' with $(m_{\tilde{g}}, m_{\tilde{t}}) = (1600, 600) \, \mathrm{GeV}$ and 'two-step' with $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-8ij50-0ib-MJ500. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-9ij50-0ib-MJ340. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-10ij50-0ib-MJ340. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-10ij50-0ib-MJ500. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-10ij50-1ib-MJ500. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-11ij50-0ib. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-12ij50-2ib. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-9ij80-0ib. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Acceptance for the signal region SR-8ij50-0ib-MJ500 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-8ij50-0ib-MJ500 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-9ij50-0ib-MJ340 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-9ij50-0ib-MJ340 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-10ij50-0ib-MJ340 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-10ij50-0ib-MJ340 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-10ij50-0ib-MJ500 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-10ij50-0ib-MJ500 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-10ij50-1ib-MJ500 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-10ij50-1ib-MJ500 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-11ij50-0ib showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-11ij50-0ib showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-12ij50-2ib showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-12ij50-2ib showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-9ij80-0ib showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-9ij80-0ib showing the efficiency for the complete two-step signal grid.
The normalisation factors for the dominant backgrounds of the analysis in each of the multi-bin and single-bin regions.
Post-fit yields for data and prediction in each of the single-bin validation regions to test the $N_{\mathrm{jet}}$ extraction.
Post-fit yields for data and prediction in each of the single-bin validation regions to test the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ extrapolation.
Post-fit yields for data and prediction in each of the multi-bin validation regions to test the $N_{\mathrm{jet}}$ extraction.
Post-fit yields for data and prediction in each of the multi-bin validation regions to test the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ extrapolation.
The observed Cls from the best expected signal regions for the two-step decay.
The observed Cls from the best expected signal regions for the Gtt decay.
The observed Cls from the best expected signal regions for the RPV decay.
Number of events in each signal region broken down by background type and the number of observed data events.
From left to right; the $95\%$ CL upper limits on the visible cross section (${\langle \epsilon\sigma \rangle}^{95}_{obs}$) and on the number of signal events. Next is the $95\%$ CL upper limit on the number of signal events, given the expected number of background events. The last two columns show the confidence level for the background only hypothesis ($CL_{b}$) and the dicovery $p$-value along with the Gaussian significance (Z).
Visualisation of the highest jet multiplicity event selected in signal regions targeting long cascade decays of pair-produced gluinos. This event was recorded by ATLAS on 23 October 2016, and contains 16 jets, illustrated by cones. Yellow blocks represent the calorimeter energy measured in noise-suppressed clusters. Of the reconstructed jets, 13 (11) have transverse momenta above 50 GeV (80 GeV), with 3 (2) being b-tagged. The leading jet has a transverse momentum of 507 GeV, and the sum of jet transverse momenta $H_T=2.9$ TeV. A value of 343 GeV is observed for the $E_{T}^{miss}$, whose direction is shown by the dashed red line, producing a significance $S(E_{T}^{miss})=6.4$. The sum of the masses of large-radius jets is evaluated as $M_{J}^{\Sigma}=1070$ GeV.
Visualisation of the highest jet multiplicity event selected in a control region used to make predictions of the background from multijet production. This event was recorded by ATLAS on 18 July 2018, and contains 19 jets, illustrated by cones. Yellow blocks represent the calorimeter energy measured in in noise-suppressed clusters. Of the reconstructed jets, 16 (10) have transverse momenta above 50 GeV (80 GeV). No jets were b-tagged. The leading et has a transverse momentum of 371 GeV, and the sum of jet transverse momenta $H_T=2.2$ TeV. A value of 8 GeV is observed for the $E_{T}^{miss}$, whose direction is shown by the dashed red line, producing a significance $S(E_{T}^{miss})=0.2$. The sum of the masses of large-radius jets is evaluated as $M_{J}^{\Sigma}=767$ GeV.
The results of a search for direct pair production of top squarks and for dark matter in events with two opposite-charge leptons (electrons or muons), jets and missing transverse momentum are reported, using 139 fb$^{-1}$ of integrated luminosity from proton-proton collisions at $\sqrt{s} = 13$ TeV, collected by the ATLAS detector at the Large Hadron Collider during Run 2 (2015-2018). This search considers the pair production of top squarks and is sensitive across a wide range of mass differences between the top squark and the lightest neutralino. Additionally, spin-0 mediator dark-matter models are considered, in which the mediator is produced in association with a pair of top quarks. The mediator subsequently decays to a pair of dark-matter particles. No significant excess of events is observed above the Standard Model background, and limits are set at 95% confidence level. The results exclude top squark masses up to about 1 TeV, and masses of the lightest neutralino up to about 500 GeV. Limits on dark-matter production are set for scalar (pseudoscalar) mediator masses up to about 250 (300) GeV.
Two-body selection. Distributions of $m_{T2}$ in $SR^{2-body}_{110,\infty}$ for (a) different-flavour and (b) same-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference dark-matter signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction.
Two-body selection. Distributions of $m_{T2}$ in $SR^{2-body}_{110,\infty}$ for (a) different-flavour and (b) same-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference dark-matter signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction.
Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Four-body selection. (a) distributions of $E_{T}^{miss}$ in $SR^{4-body}_{Small\,\Delta m}$ and (b) distribution of $R_{2\ell 4j}$ in $SR^{4-body}_{Large\,\Delta m}$ for events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panel indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Four-body selection. (a) distributions of $E_{T}^{miss}$ in $SR^{4-body}_{Small\,\Delta m}$ and (b) distribution of $R_{2\ell 4j}$ in $SR^{4-body}_{Large\,\Delta m}$ for events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panel indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the Observed limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Two-body selection. Background fit results for $\mathrm{CR}^{\mathrm{2-body}}_{t\bar{t}}$, $\mathrm{CR}^{\mathrm{2-body}}_{t\bar{t}Z}$, $\mathrm{VR}^{\mathrm{2-body}}_{t\bar{t}, DF}$, $\mathrm{VR}^{\mathrm{2-body}}_{t\bar{t}, SF}$ and $\mathrm{VR}^{\mathrm{2-body}}_{t\bar{t} Z}$. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Three-body selection. Background fit results for $\mathrm{CR}^{\mathrm{3-body}}_{t\bar{t}}$, $\mathrm{CR}^{\mathrm{3-body}}_{VV}$, $\mathrm{CR}^{\mathrm{2-body}}_{t\bar{t}Z}$, $\mathrm{VR}^{\mathrm{3-body}}_{VV}$, $\mathrm{VR(1)}^{\mathrm{3-body}}_{t\bar{t}}$ and $\mathrm{VR(2)}^{\mathrm{3-body}}_{t\bar{t}}$. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Four-body selection. Background fit results for $\mathrm{CR}^{\mathrm{4-body}}_{t\bar{t}}$,$\mathrm{CR}^{\mathrm{4-body}}_{VV}$, $\mathrm{VR}^{\mathrm{4-body}}_{t\bar{t}}$, $VR^{4-body}_{VV}$ and $\mathrm{VR}^{\mathrm{4-body}}_{VV,lll}$. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Two-body selection. Background fit results for the different-flavour leptons binned SRs. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Two-body selection. Background fit results for the same-flavour leptons binned SRs. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Three-body selection. Observed event yields and background fit results for the three-body selection SRs. The ''Others'' category contains contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Four-body selection. Observed event yields and background fit results for SR$^{\mathrm{4-body}}_{\mathrm{Small}\,\Delta m}$ and SR$^{\mathrm{4-body}}_{\mathrm{Large}\,\Delta m}$. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Exclusion limits contours (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}^0_1$ with 100% branching ratio in $\tilde{t}_1--\tilde{\chi}^0_1$ masses planes. The dashed lines and the shaded bands are the expected limit and its $\pm 1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The exclusion limits contours for the two-body, three-body and four-body selections are respectively shown in blue, green and red.
Exclusion limits contours (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}^0_1$ with 100% branching ratio in $\tilde{t}_1--\tilde{\chi}^0_1$ masses planes. The dashed lines and the shaded bands are the expected limit and its $\pm 1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The exclusion limits contours for the two-body, three-body and four-body selections are respectively shown in blue, green and red.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm 1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty.The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty.The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Four-body selection Efficiency (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta m}$ for a simplified model assuming $\tilde{t}_1$ pair production.
Four-body selection Efficiency (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta\ m}$ for a simplified model assuming $\tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Four-body selection acceptance (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta m}$ for a simplified model assuming $\tilde{t}_1$ pair production.
Four-body selection acceptance (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta m}$ for a simplified model assuming $\tilde{t}_1$ pair production.
Two-body selection The numbers indicate the observed upper limits on the signal strenght for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Two-body selection The numbers indicate the observed upper limits on the signal strenght for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Two-body selection The numbers indicate the observed upper limits on the signal strenght for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Three-body selection The numbers indicate the upper limits on the signal strenght for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.
Four-body selection The numbers indicate the upper limits on the signal strenght for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.
Two-body selection The numbers indicate the upper limits on the signal cross-section for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Two-body selection The numbers indicate the upper limits on the signal cross-section for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Two-body selection The numbers indicate the upper limits on the signal cross-section for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Three-body selection The numbers indicate the upper limits on the signal cross-section for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.
Four-body selection The numbers indicate the upper limits on the signal cross-section for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.
Two-body selection. Background fit results for the $inclusive$ SRs. The Others category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Note that the individual uncertainties can be correlated, and do not necessarily add up quadratically to the total background uncertainty.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=600~ GeV$ and $m(\tilde{\chi}^0_1)=400~ GeV$ in the SRs for the two-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the scalar signal model $t\bar{t} + \phi $ with $m(\phi)=150~ GeV$ and $m(\chi)=1~ GeV$ in the SRs for the two-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the pseudoscalar signal model $t\bar{t} + a $ with $m(a)=150~ GeV$ and $m(\chi)=1~ GeV$ in the SRs for the two-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=385~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=400~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=430~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=460~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}^0_1$ with $m(\tilde{t}_1)=400~ GeV$ and $m(\tilde{\chi}^0_1)=380~ GeV$ in the SRs for the four-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}^0_1$ with $m(\tilde{t}_1)=460~ GeV$ and $m(\tilde{\chi}^0_1)=415~ GeV$ in the SRs for the four-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}^0_1$ with $m(\tilde{t}_1)=400~ GeV$ and $m(\tilde{\chi}^0_1)=320~ GeV$ in the SRs for the four-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
A search for pair production of bottom squarks in events with hadronically decaying $\tau$-leptons, $b$-tagged jets and large missing transverse momentum is presented. The analyzed dataset is based on proton-proton collisions at $\sqrt{s}$ = 13 TeV delivered by the Large Hadron Collider and recorded by the ATLAS detector from 2015 to 2018, and corresponds to an integrated luminosity of 139 fb$^{-1}$. The observed data are compatible with the expected Standard Model background. Results are interpreted in a simplified model where each bottom squark is assumed to decay into the second-lightest neutralino $\tilde \chi_2^0$ and a bottom quark, with $\tilde \chi_2^0$ decaying into a Higgs boson and the lightest neutralino $\tilde \chi_1^0$. The search focuses on final states where at least one Higgs boson decays into a pair of hadronically decaying $\tau$-leptons. This allows the acceptance and thus the sensitivity to be significantly improved relative to the previous results at low masses of the $\tilde \chi_2^0$, where bottom-squark masses up to 850 GeV are excluded at the 95% confidence level, assuming a mass difference of 130 GeV between $\tilde \chi_2^0$ and $\tilde \chi_1^0$. Model-independent upper limits are also set on the cross section of processes beyond the Standard Model.
The expected exclusion contour at $95\%$ CL as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Masses within the contour are excluded.
The observed exclusion contour at $95\%$ CL as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Masses within the contour are excluded.
Acceptance in the Single-bin SR as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.
Efficiency in the Single-bin SR as a function of the M(Sbottom) vs. M(N2) with the $\Delta$ M(N2,N1) $= 130$ GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.
Acceptance in the Multi-bin SR, $\min_{\Theta} < 0.5$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.
Efficiency in the Multi-bin SR, $\min_{\Theta} < 0.5$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.
Acceptance in the Multi-bin SR, $0.5 < \min_{\Theta} < 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.
Efficiency in the Multi-bin SR, $0.5 < \min_{\Theta} < 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.
Acceptance in the Multi-bin SR, $\min_{\Theta} > 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.
Efficiency in the Multi-bin SR, $\min_{\Theta} > 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.
Observed upper limits on the signal cross section as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV.
Expected upper limits on the signal cross section as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV.
Cutflows for the bechmarl signal point M(Sbottom) = 800 GeV, M(N2) = 180 GeV. Weighted event yields are reported starting with the "Preselection" line, normalized to an integrated luminosity of $139$ fb$^{−1}$.
Comparison of the expected and observed event yields in the signal regions. The top-quark and Z(mumu) background contributions are scaled with the normalization factors obtained from the background-only fit. The other contribution includes all the backgrounds not explicitly listed in the legend (V+jets except Z(mumu)+jets, di-/triboson, multijet). The hatched band indicates the total statistical and systematic uncertainties in the SM background. The contributions from three signal models to the signal regions are also displayed, where the masses M(Sbottom) and M(N2) are given in GeV in the legend. The lower panel shows the significance of the deviation of the observed yield from the expected background yield.
Dominant systematic uncertainties in the background prediction for the signal regions after the fit to the control regions. “Other” includes the uncertainties arising from muons, jet-vertex tagging, modeling of pile-up, the $E_{T}^{miss}$ computation, multijet background, and luminosity. The individual uncertainties can be correlated and do not necessarily add up quadratically to the total uncertainty.
A search for the supersymmetric partners of quarks and gluons (squarks and gluinos) in final states containing jets and missing transverse momentum, but no electrons or muons, is presented. The data used in this search were recorded by the ATLAS experiment in proton-proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb$^{-1}$. The results are interpreted in the context of various $R$-parity-conserving models where squarks and gluinos are produced in pairs or in association and a neutralino is the lightest supersymmetric particle. An exclusion limit at the 95% confidence level on the mass of the gluino is set at 2.30 TeV for a simplified model containing only a gluino and the lightest neutralino, assuming the latter is massless. For a simplified model involving the strong production of mass-degenerate first- and second-generation squarks, squark masses below 1.85 TeV are excluded if the lightest neutralino is massless. These limits extend substantially beyond the region of supersymmetric parameter space excluded previously by similar searches with the ATLAS detector.
Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-SSd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-SSd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed metSig distributions in signal regions MB-SSd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed metSig distributions in signal regions MB-SSd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-GGd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-GGd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed metSig distributions in signal regions MB-GGd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed metSig distributions in signal regions MB-GGd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-C. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-C. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed metSig distributions in signal regions MB-C. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed metSig distributions in signal regions MB-C. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed BDT-GGd1 score distributions in signal regions GGd1. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed BDT-GGd1 score distributions in signal regions GGd1. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed BDT-GGo1 score distributions in signal regions GGo1. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed BDT-GGo1 score distributions in signal regions GGo1. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd1
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd1
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd2
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd2
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd3
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd3
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd4
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd4
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo1
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo1
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo2
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo2
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo3
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo3
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo4
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo4
Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-1600
Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-1600
Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2200
Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2200
Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2800
Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2800
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-1000
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-1000
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-2200
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-2200
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-3400
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-3400
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 5j-1600
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 5j-1600
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-1000
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-1000
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-2200
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-2200
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-3400
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-3400
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd1. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd1. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd2. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd2. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd3. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd3. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd4. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd4. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo1. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo1. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo2. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo2. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo3. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo3. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo4. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo4. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-1600. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-1600. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2800. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2800. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-1000. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-1000. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-3400. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-3400. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 5j-1600. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 5j-1600. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-1000. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-1000. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-3400. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-3400. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Exclusion limits in the mass plane of the lightest neutralino and first- and second-generation squarks assuming squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and first- and second-generation squarks assuming squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and first- and second-generation squarks assuming squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and first- and second-generation squarks assuming squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and non degenerated squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and non degenerated squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and non degenerated squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and non degenerated squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and the gluino for gluino pair production with direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and the gluino for gluino pair production with direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and the gluino for gluino pair production with direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and the gluino for gluino pair production with direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and squarks. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and squarks. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and squarks. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and squarks. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for squark pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for squark pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for squark pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for squark pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and gluinos. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and gluinos. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and gluinos. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and gluinos. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for gluino pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the gluino mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for gluino pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the gluino mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for gluino pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the gluino mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for gluino pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the gluino mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 0 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 0 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 0 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 0 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 995 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 995 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 995 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 995 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 1495 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 1495 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 1495 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 1495 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with direct decays.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with direct decays.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with direct decays
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with direct decays
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with a one-step decay via an intermediate chargino.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with a one-step decay via an intermediate chargino.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with a one-step decay via an intermediate chargino.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with a one-step decay via an intermediate chargino.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60~GeV and exclusio limits are given for mass difference ratio, $X$, as a function of the gluino mass.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60~GeV and exclusio limits are given for mass difference ratio, $X$, as a function of the gluino mass.
Cut-flow for model-independent search regions targeting squarks for SS direct model points. Expected yields are normalized to a luminosity of 139 fb$^{-1}$.
Cut-flow for model-independent search regions targeting squarks for SS direct model points. Expected yields are normalized to a luminosity of 139 fb$^{-1}$.
Cut-flow for model-independent search regions targeting gluinos for GG direct model points. Expected yields are normalized to a luminosity of 139 fb$^{-1}$.
Cut-flow for model-independent search regions targeting gluinos for GG direct model points. Expected yields are normalized to a luminosity of 139 fb$^{-1}$.
Cut-flow for model-independent search regions targeting squarks and gluinos in models with one-step decay. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.
Cut-flow for model-independent search regions targeting squarks and gluinos in models with one-step decay. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.
Cut-flow for BDT search regions targeting gluinos in models with one-step decays. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.
Cut-flow for BDT search regions targeting gluinos in models with one-step decays. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.
Cut-flow for BDT search regions targeting gluinos in models with direct decays. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.
Cut-flow for BDT search regions targeting gluinos in models with direct decays. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.
A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell $W$ and $Z$ bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of $\sqrt{s}$ = 13 TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb$^{-1}$. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015-2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full dataset are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV.
Distributions in SR-low of the data and post-fit background prediction for m<sub>T</sub>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for m<sub>T</sub>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for H<sup>boost</sup>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for H<sup>boost</sup>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for m<sub>eff</sub><sup>3ℓ</sup>/H<sup>boost</sup>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for m<sub>eff</sub><sup>3ℓ</sup>/H<sup>boost</sup>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for p<sub>T</sub><sup>soft</sup>/(p<sub>T</sub><sup>soft</sup> + m<sub>eff</sub><sup>3ℓ</sup>). The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for p<sub>T</sub><sup>soft</sup>/(p<sub>T</sub><sup>soft</sup> + m<sub>eff</sub><sup>3ℓ</sup>). The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for m<sub>T</sub>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for m<sub>T</sub>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for R(E<sub>T</sub><sup>miss</sup>,jets). The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for R(E<sub>T</sub><sup>miss</sup>,jets). The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for p<sub>T</sub><sup>soft</sup>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for p<sub>T</sub><sup>soft</sup>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for p<sub>T</sub><sup>jets</sup>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for p<sub>T</sub><sup>jets</sup>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Plus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Plus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Minus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Minus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Plus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Plus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Minus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Minus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Upper limits on observed wino-bino simplified model signal cross section $\sigma_\text{obs}^\text{95}$.
Upper limits on observed wino-bino simplified model signal cross section $\sigma_\text{obs}^\text{95}$.
Upper limits on expected wino-bino simplified model signal cross section $\sigma_\text{exp}^\text{95}$.
Upper limits on expected wino-bino simplified model signal cross section $\sigma_\text{exp}^\text{95}$.
Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
The observed and expected yields after the background-only fit in the SRs. The normalization factors of the $WZ$ sample for the low-mass and ISR regions are different and are treated separately in the combined fit. \The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. Combined statistical and systematic uncertainties are presented. The individual uncertainties can be correlated and do not necessarily add in quadrature to equal the total background uncertainty.
The observed and expected yields after the background-only fit in the SRs. The normalization factors of the $WZ$ sample for the low-mass and ISR regions are different and are treated separately in the combined fit. \The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. Combined statistical and systematic uncertainties are presented. The individual uncertainties can be correlated and do not necessarily add in quadrature to equal the total background uncertainty.
Summary of the expected background and data yields in $\text{SR-low}$ and $\text{SR-ISR}$. The second and third columns show the data and total expected background with systematic uncertainties. The fourth column gives the model-independent upper limits at 95\% CL on the visible cross section ($\sigma_\text{vis}$). The fifth and sixth columns give the visible number of observed ($S^{95}_\text{obs}$) and expected ($S^{95}_\text{exp}$) events of a generic beyond-the-SM process, where uncertainties on $S^{95}_\text{exp}$ reflect the $\pm 1 \sigma$ uncertainties on the background estimation. The last column shows the discovery $p$-value and Gaussian significance $Z$ assuming no signal.
Summary of the expected background and data yields in $\text{SR-low}$ and $\text{SR-ISR}$. The second and third columns show the data and total expected background with systematic uncertainties. The fourth column gives the model-independent upper limits at 95\% CL on the visible cross section ($\sigma_\text{vis}$). The fifth and sixth columns give the visible number of observed ($S^{95}_\text{obs}$) and expected ($S^{95}_\text{exp}$) events of a generic beyond-the-SM process, where uncertainties on $S^{95}_\text{exp}$ reflect the $\pm 1 \sigma$ uncertainties on the background estimation. The last column shows the discovery $p$-value and Gaussian significance $Z$ assuming no signal.
Upper limits on observed (expected) wino-bino simplified model signal cross section $\sigma_\text{obs(exp)}^\text{95}$.
Upper limits on observed (expected) wino-bino simplified model signal cross section $\sigma_\text{obs(exp)}^\text{95}$.
Full list of event selections and MC generator-weighted yields and in $\text{SR-ISR}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.
Full list of event selections and MC generator-weighted yields and in $\text{SR-ISR}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.
Full list of event selections and MC generator-weighted yields and in $\text{SR-low}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.
Full list of event selections and MC generator-weighted yields and in $\text{SR-low}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.
A search for the direct production of the supersymmetric partners of $\tau$-leptons (staus) in final states with two hadronically decaying $\tau$-leptons is presented. The analysis uses a dataset of $pp$ collisions corresponding to an integrated luminosity of $139$ fb$^{-1}$, recorded with the ATLAS detector at the Large Hadron Collider at a center-of-mass energy of 13 TeV. No significant deviation from the expected Standard Model background is observed. Limits are derived in scenarios of direct production of stau pairs with each stau decaying into the stable lightest neutralino and one $\tau$-lepton in simplified models where the two stau mass eigenstates are degenerate. Stau masses from 120 GeV to 390 GeV are excluded at 95% confidence level for a massless lightest neutralino.
The observed upper limits on the model cross-section in units of pb for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production. Three points at ${M({\tilde{\chi}}^{0}_{1})}=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.
The observed upper limits on the model cross-section in units of pb for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production. Three points at ${M({\tilde{\chi}}^{0}_{1})}=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.
The observed upper limits on the model cross-section in units of pb for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production. Three points at $M({\tilde{\chi}}^{0}_{1})=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.
The observed upper limits on the model cross-section in units of pb for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production. Three points at $M({\tilde{\chi}}^{0}_{1})=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.
The observed 95\% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.
The observed 95\% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.
The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.
The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.
The observed 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.
The observed 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.
The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.
The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.
Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.
Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.
Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.
Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.
Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.
Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.
Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.
Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.
Signal acceptance in SR highMass for combined stau final states
Signal acceptance in SR highMass for combined stau final states
Signal acceptance in SR lowMass for combined stau final states
Signal acceptance in SR lowMass for combined stau final states
Signal efficiency in SR highMass for combined stau final states
Signal efficiency in SR highMass for combined stau final states
Signal efficiency in SR lowMass for combined stau final states
Signal efficiency in SR lowMass for combined stau final states
Signal acceptance*efficiency in SR highMass for combined stau final states
Signal acceptance*efficiency in SR highMass for combined stau final states
Signal acceptance*efficiency in SR lowMass for combined stau final states
Signal acceptance*efficiency in SR lowMass for combined stau final states
Cutflow for two reference points (${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production) in SR. The column labelled $N_{weighted}$ shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$, while $N_{raw}$ in brackets shows the results for the generated number of events. The quoted uncertainties are statistical only. The "Generator filter" includes the requirements that two $\tau$ in the event have ${p}_{T} > 15$ GeV and $|\eta| <$ 2.6. The "Baseline Cut" includes the requirement of two baseline $\tau$ with a minimum value at 0.01 of the boosted decision tree discriminant (JetBDTSigTransMin $>$ 0.01) and ${p}_{T, \tau_{1}} > 50$ GeV and ${p}_{T, \tau_{2}} > 40$ GeV. At the step "Trigger & offline cuts", the following requirements are applied: the event is recorded using the asymmetric di-$\tau$ trigger (di-$\tau$ $E_{T}^{miss}$ trigger) in SR-lowMass (SR-highMass), and the lepton $p_{T}$ and $E_{T}^{miss}$ are required at plateau.
Cutflow for two reference points (${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production) in SR. The column labelled $N_{weighted}$ shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$, while $N_{raw}$ in brackets shows the results for the generated number of events. The quoted uncertainties are statistical only. The "Generator filter" includes the requirements that two $\tau$ in the event have ${p}_{T} > 15$ GeV and $|\eta| <$ 2.6. The "Baseline Cut" includes the requirement of two baseline $\tau$ with a minimum value at 0.01 of the boosted decision tree discriminant (JetBDTSigTransMin $>$ 0.01) and ${p}_{T, \tau_{1}} > 50$ GeV and ${p}_{T, \tau_{2}} > 40$ GeV. At the step "Trigger & offline cuts", the following requirements are applied: the event is recorded using the asymmetric di-$\tau$ trigger (di-$\tau$ $E_{T}^{miss}$ trigger) in SR-lowMass (SR-highMass), and the lepton $p_{T}$ and $E_{T}^{miss}$ are required at plateau.
Observed and expected numbers of events in the control and signal regions where all control and signal region bins are included as constraints in the likelihood. The expected event yields of SM processes are given after the background-only fit. The entries marked as "--" are negligible. The uncertainties correspond to the sum in quadrature of statistical and systematic uncertainties. The correlation of systematic uncertainties among control regions and among background processes is fully taken into account.
Observed and expected numbers of events in the control and signal regions where all control and signal region bins are included as constraints in the likelihood. The expected event yields of SM processes are given after the background-only fit. The entries marked as "--" are negligible. The uncertainties correspond to the sum in quadrature of statistical and systematic uncertainties. The correlation of systematic uncertainties among control regions and among background processes is fully taken into account.
The post-fit $m_{T2}$ distribution for SR-lowMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.
The post-fit $m_{T2}$ distribution for SR-lowMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.
The post-fit $m_{T2}$ distribution for SR-highMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.
The post-fit $m_{T2}$ distribution for SR-highMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.
The $m_{T2}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $m_{T2}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $m_{T2}$ post-fit distributions in the multi-jet background validation VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $m_{T2}$ post-fit distributions in the multi-jet background validation VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The pre-fit $m_{T2}$ distribution in the $WCR$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is estimated from data using the OS--SS method. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The pre-fit $m_{T2}$ distribution in the $WCR$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is estimated from data using the OS--SS method. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The post-fit yields in the $WVR$, $TVRs$, $ZVRs$ and $VVVRs$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is negligible and is estimated from data using the ABCD method, using CRs obtained with the same technique used for the SRs. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate.
The post-fit yields in the $WVR$, $TVRs$, $ZVRs$ and $VVVRs$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is negligible and is estimated from data using the ABCD method, using CRs obtained with the same technique used for the SRs. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate.
A search for long-lived particles decaying into hadrons and at least one muon is presented. The analysis selects events that pass a muon or missing-transverse-momentum trigger and contain a displaced muon track and a displaced vertex. The analyzed dataset of proton-proton collisions at $\sqrt{s} = 13$ TeV was collected with the ATLAS detector and corresponds to 136 fb$^{-1}$. The search employs dedicated reconstruction techniques that significantly increase the sensitivity to long-lived particle decays that occur in the ATLAS inner detector. Background estimates for Standard Model processes and instrumental effects are extracted from data. The observed event yields are compatible with those expected from background processes. The results are presented as limits at 95% confidence level on model-independent cross sections for processes beyond the Standard Model, and interpreted as exclusion limits in scenarios with pair-production of long-lived top squarks that decay via a small $R$-parity-violating coupling into a quark and a muon. Top squarks with masses up to 1.7 TeV are excluded for a lifetime of 0.1 ns, and masses below 1.3 TeV are excluded for lifetimes between 0.01 ns and 30 ns.
Vertex selection acceptance for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.
Vertex selection acceptance for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.
Vertex selection efficiency for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.
Vertex selection efficiency for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.
Track multiplicity $n_{Tracks}$ for preselected DVs in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Track multiplicity $n_{Tracks}$ for preselected DVs in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Track multiplicity $n_{Tracks}$ for preselected DVs in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Track multiplicity $n_{Tracks}$ for preselected DVs in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
The observed event yields in the control, validation and signal regions are shown for the MET Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.
The observed event yields in the control, validation and signal regions are shown for the MET Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.
The observed event yields in the control, validation and signal regions are shown for the Muon Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.
The observed event yields in the control, validation and signal regions are shown for the Muon Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.
Expected exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected (1 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected (1 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected (2 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected (2 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed (+1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed (+1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed (-1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed (-1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Exclusion limits on the production cross section as a function of m($\tilde{t}$) are shown for several values of $\tau(\tilde{t})$ along with the nominal signal production cross section and its theoretical uncertainty.
Exclusion limits on the production cross section as a function of m($\tilde{t}$) are shown for several values of $\tau(\tilde{t})$ along with the nominal signal production cross section and its theoretical uncertainty.
Parameterized event selection efficiencies for the $E_{T}^{miss}$ Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.
Parameterized event selection efficiencies for the $E_{T}^{miss}$ Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.
Parameterized event selection efficiencies for the Muon Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.
Parameterized event selection efficiencies for the Muon Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.
Parameterized muon-level reconstruction efficiencies as a function of the muon $p_{T}$ and $d_{0}$. The muon-level efficiencies are extracted using muons passing the muon acceptance criteria.
Parameterized muon-level reconstruction efficiencies as a function of the muon $p_{T}$ and $d_{0}$. The muon-level efficiencies are extracted using muons passing the muon acceptance criteria.
Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated independent of the muons originating from this truth vertex.
Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated independent of the muons originating from this truth vertex.
Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated only for truth vertices which have a muon originating from them which is matched to a reconstructed muon.
Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated only for truth vertices which have a muon originating from them which is matched to a reconstructed muon.
The $p_{T}$ distribution of all muons originating from LLP decays in the samples used to calculate and validate the efficiencies.
The $p_{T}$ distribution of all muons originating from LLP decays in the samples used to calculate and validate the efficiencies.
The invariant mass and multiplicity of selected decay products of all truth vertices used in the calculation and validation of the reconstructed efficiencies.
The invariant mass and multiplicity of selected decay products of all truth vertices used in the calculation and validation of the reconstructed efficiencies.
The result of a search for the pair production of the lightest supersymmetric partner of the bottom quark ($\tilde{b}_{1}$) using 139 fb$^{-1}$ of proton-proton data collected at $\sqrt{s} = 13$ TeV by the ATLAS detector is reported. In the supersymmetric scenarios considered both of the bottom-squarks decay into a $b$-quark and the second-lightest neutralino, $\tilde{b}_{1} \rightarrow b + \tilde{\chi}^{0}_{2}$. Each $\tilde{\chi}^{0}_{2}$ is assumed to subsequently decay with 100% branching ratio into a Higgs boson ($h$) like the one in the Standard Model and the lightest neutralino: $\tilde{\chi}^{0}_{2} \rightarrow h + \tilde{\chi}^{0}_{1}$. The $\tilde{\chi}^{0}_{1}$ is assumed to be the lightest supersymmetric particle (LSP) and is stable. Two signal mass configurations are targeted: the first has a constant LSP mass of 60 GeV; and the second has a constant mass difference between the $\tilde{\chi}^{0}_{2}$ and $\tilde{\chi}^{0}_{1}$ of 130 GeV. The final states considered contain no charged leptons, three or more $b$-jets, and large missing transverse momentum. No significant excess of events over the Standard Model background expectation is observed in any of the signal regions considered. Limits at the 95% confidence level are placed in the supersymmetric models considered, and bottom-squarks with mass up to 1.5 TeV are excluded.
Distributions of ${E}_{\mathrm{T}}^{\mathrm{miss}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of ${E}_{\mathrm{T}}^{\mathrm{miss}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of ${E}_{\mathrm{T}}^{\mathrm{miss}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of $m_{\mathrm{eff}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of $m_{\mathrm{eff}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of $m_{\mathrm{eff}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of Object-based $E_{\mathrm{T}}^{\mathrm{miss}} {Sig.}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of Object-based $E_{\mathrm{T}}^{\mathrm{miss}} {Sig.}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of Object-based $E_{\mathrm{T}}^{\mathrm{miss}} {Sig.}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of MaxMin alternative algorithm $m(h_{\mathrm{cand1}},h_{\mathrm{cand2}})_{\mathrm{avg}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of MaxMin alternative algorithm $m(h_{\mathrm{cand1}},h_{\mathrm{cand2}})_{\mathrm{avg}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of MaxMin alternative algorithm $m(h_{\mathrm{cand1}},h_{\mathrm{cand2}})_{\mathrm{avg}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of Leading jet $p_T$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of Leading jet $p_T$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of Leading jet $p_T$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of MaxMin algorithm $m_{hcand}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of MaxMin algorithm $m_{hcand}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of MaxMin algorithm $m_{hcand}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Signal efficiency in SRA_M_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_M_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_M_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal acceptance in SRC_28 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_28 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_28 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_26 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_26 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_26 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_24 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_24 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_24 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_M_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_M_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_M_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRB for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRB for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRB for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_L_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_L_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_L_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_incl for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_incl for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_incl for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_L_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_L_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_L_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_incl_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_incl_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_incl_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_incl_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_incl_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_incl_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal efficiency in SRA_H_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_H_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_H_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_L_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_L_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_L_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRB for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRB for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRB for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal acceptance in SRC_22 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_22 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_22 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal efficiency in SRA_H_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_H_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_H_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_24 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_24 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_24 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_26 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_26 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_26 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal acceptance in SRA_H_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_H_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_H_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal efficiency in SRA_incl_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_incl_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_incl_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_22 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_22 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_22 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal acceptance in SRA_M_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_M_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_M_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal efficiency in SRC_28 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_28 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_28 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal acceptance in SRA_H_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_H_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_H_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal efficiency in SRA_incl_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_incl_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_incl_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_L_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_L_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_L_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_M_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_M_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_M_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_incl for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_incl for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_incl for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Observed 95% CLs exclusion limit for the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid for the best combined signal regions.
Observed 95% CLs exclusion limit for the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid for the best combined signal regions.
Observed 95% CLs exclusion limit for the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid for the best combined signal regions.
Expected 95% CLs exclusion limit for the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid for the best combined signal regions.
Expected 95% CLs exclusion limit for the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid for the best combined signal regions.
Expected 95% CLs exclusion limit for the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid for the best combined signal regions.
Observed 95% CLs exclusion limit for the $M(\widetilde{\chi}_{1}^{0})$=60GeV signal grid for the best combined signal regions.
Observed 95% CLs exclusion limit for the $M(\widetilde{\chi}_{1}^{0})$=60GeV signal grid for the best combined signal regions.
Observed 95% CLs exclusion limit for the $M(\widetilde{\chi}_{1}^{0})$=60GeV signal grid for the best combined signal regions.
Expected 95% CLs exclusion limit for the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid for the best combined signal regions.
Expected 95% CLs exclusion limit for the $M(\widetilde{\chi}_{1}^{0})$=60GeV signal grid for the best combined signal regions.
Expected 95% CLs exclusion limit for the $M(\widetilde{\chi}_{1}^{0})$=60GeV signal grid for the best combined signal regions.
Model dependent upper limit on the best combined signal regions considered in the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid
Model dependent upper limit on the best combined signal regions considered in the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid
Model dependent upper limit on the best combined signal regions considered in the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid
Model dependet upper limits on the best combined signal regions considered in the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid
Model dependet upper limits on the best combined signal regions considered in the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid
Model dependet upper limits on the best combined signal regions considered in the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid
Result of background only fit applied to signal regions. Event yields from the signal regions compared with SM MC predictions for the 3 highest contributing backgrounds separately and combined minor backgrounds.
Result of background only fit applied to signal regions. Event yields from the signal regions compared with SM MC predictions for the 3 highest contributing backgrounds separately and combined minor backgrounds.
Result of background only fit applied to signal regions. Event yields from the signal regions compared with SM MC predictions for the 3 highest contributing backgrounds separately and combined minor backgrounds.
Expected background event yields and dominant systematic uncertainties on background estimates in the A-type (inclusive), B-type and C-type (inclusive) regions.
Expected background event yields and dominant systematic uncertainties on background estimates in the A-type (inclusive), B-type and C-type (inclusive) regions.
Expected background event yields and dominant systematic uncertainties on background estimates in the A-type (inclusive), B-type and C-type (inclusive) regions.
Background-only fit results for the A- and B-type regions performed using 139$fb^{-1}$ of data. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Background-only fit results for the A- and B-type regions performed using 139$fb^{-1}$ of data. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Background-only fit results for the A- and B-type regions performed using 139$fb^{-1}$ of data. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Background-only fit results for the C-type region performed using 139$fb^{-1}$ of data. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Background-only fit results for the C-type region performed using 139$fb^{-1}$ of data. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Background-only fit results for the C-type region performed using 139$fb^{-1}$ of data. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Observed 95% CL upper limits on the visible cross sections σvis, the observed (S95obs) and expected (S95exp) 95% CL upper limits on the number of signal events with ± 1 σ excursions of the expectation, the CL of the background-only hypothesis, CLB, the discovery p-value (p0), truncated at 0.5, and the associated significance.
Observed 95% CL upper limits on the visible cross sections σvis, the observed (S95obs) and expected (S95exp) 95% CL upper limits on the number of signal events with ± 1 σ excursions of the expectation, the CL of the background-only hypothesis, CLB, the discovery p-value (p0), truncated at 0.5, and the associated significance.
Observed 95% CL upper limits on the visible cross sections σvis, the observed (S95obs) and expected (S95exp) 95% CL upper limits on the number of signal events with ± 1 σ excursions of the expectation, the CL of the background-only hypothesis, CLB, the discovery p-value (p0), truncated at 0.5, and the associated significance.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRA selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (1100, 330, 200)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRA selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (1100, 330, 200)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRA selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (1100, 330, 200)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRB selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (700, 680, 550)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRB selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (700, 680, 550)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRB selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (700, 680, 550)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRC selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (1200, 1150, 60)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRC selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (1200, 1150, 60)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRC selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (1200, 1150, 60)$ GeV, considered.
A search for supersymmetric partners of gluons and quarks is presented, involving signatures with jets and either two isolated leptons (electrons or muons) with the same electric charge, or at least three isolated leptons. A data sample of proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018, corresponding to a total integrated luminosity of 139 fb$^{-1}$, is used for the search. No significant excess over the Standard Model expectation is observed. The results are interpreted in simplified supersymmetric models featuring both R-parity conservation and R-parity violation, raising the exclusion limits beyond those of previous ATLAS searches to 1600 GeV for gluino masses and 750 GeV for bottom and top squark masses in these scenarios.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
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