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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.
A search for a heavy charged-boson resonance decaying into a charged lepton (electron or muon) and a neutrino is reported. A data sample of 139 fb$^{-1}$ of proton-proton collisions at $\sqrt{s} = 13$ TeV collected with the ATLAS detector at the LHC during 2015-2018 is used in the search. The observed transverse mass distribution computed from the lepton and missing transverse momenta is consistent with the distribution expected from the Standard Model, and upper limits on the cross section for $pp \to W^\prime \to \ell\nu$ are extracted ($\ell = e$ or $\mu$). These vary between 1.3 pb and 0.05 fb depending on the resonance mass in the range between 0.15 and 7.0 TeV at 95% confidence level for the electron and muon channels combined. Gauge bosons with a mass below 6.0 TeV and 5.1 TeV are excluded in the electron and muon channels, respectively, in a model with a resonance that has couplings to fermions identical to those of the Standard Model $W$ boson. Cross-section limits are also provided for resonances with several fixed $\Gamma / m$ values in the range between 1% and 15%. Model-independent limits are derived in single-bin signal regions defined by a varying minimum transverse mass threshold. The resulting visible cross-section upper limits range between 4.6 (15) pb and 22 (22) ab as the threshold increases from 130 (110) GeV to 5.1 (5.1) TeV in the electron (muon) channel.
Transverse mass distribution for events satisfying all selection criteria in the electron channel.
Transverse mass distribution for events satisfying all selection criteria in the muon channel.
Upper limits at the 95% CL on the cross section for SSM $W^\prime$ production and decay to the electron+neutrino channel as a function of the $W^\prime$ pole mass.
Upper limits at the 95% CL on the cross section for SSM $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.
Combined (electron and muon channels) upper limits at the 95% CL on the cross section for SSM $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.
Observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the electron+neutrino channel as a function of the $W^\prime$ pole mass.
Observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.
Combined (electron and muon channels) observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.
Observed upper limits at the 95% CL on the visible cross section in the electron+neutrino channel as a function of the transverse mass threshold.
Observed upper limits at the 95% CL on the visible cross section in the muon+neutrino channel as a function of the transverse mass threshold.
Product of acceptance and efficiency for the electron and muon selections as a function of the $W^\prime$ pole mass.
Expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the electron+neutrino channel as a function of the $W^\prime$ pole mass.
Expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.
Combined (electron and muon channels) expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.
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 $139~fb^{-1}$.
This paper describes a search for beyond the Standard Model decays of the Higgs boson into a pair of new spin-0 particles subsequently decaying into $b$-quark pairs, $H \rightarrow aa \rightarrow (b\bar{b})(b\bar{b})$, using proton-proton collision data collected by the ATLAS detector at the Large Hadron Collider at center-of-mass energy $\sqrt{s}=13$ TeV. This search focuses on the regime where the decay products are collimated and in the range $15 \leq m_a \leq 30$ GeV and is complementary to a previous search in the same final state targeting the regime where the decay products are well separated and in the range $20 \leq m_a \leq 60$ GeV. A novel strategy for the identification of the $a \rightarrow b\bar{b}$ decays is deployed to enhance the efficiency for topologies with small separation angles. The search is performed with 36 fb$^{-1}$ of integrated luminosity collected in 2015 and 2016 and sets upper limits on the production cross-section of $H \rightarrow aa \rightarrow (b\bar{b})(b\bar{b})$, where the Higgs boson is produced in association with a $Z$ boson.
Summary of the 95% CL upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$. Both observed and expected limits are listed. In the case of the expected limits, one- and two-standard-deviation uncertainty bands are also listed.
Summary of the 95% CL upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$. Both observed and expected limits are listed. In the case of the expected limits, one- and two-standard-deviation uncertainty bands are also listed.
Summary of the observed 95% CL upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$ for the resolved analysis.
Summary of the 95% C.L. upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$ for the dilepton channel in the resolved analysis. The observed limits are shown, together with the expected limits (dotted black lines). In the case of the expected limits, one- and two-standard-deviation uncertainty bands are also displayed. The data was published in JHEP 10 (2018) 031.
Efficiency and acceptance for simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ samples in two signal regions (SR) of the analysis, one with two $a\to b\bar{b}$ candidates in the High Purity Category (HPC), and the other with one $a\to b\bar{b}$ candidate in the High Purity Category (HPC) and one in the Low Purity Category (LPC).
Efficiency and acceptance for simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ samples in two signal regions (SR) of the analysis, one with two $a\to b\bar{b}$ candidates in the High Purity Category (HPC), and the other with one $a\to b\bar{b}$ candidate in the High Purity Category (HPC) and one in the Low Purity Category (LPC).
Event yields for a simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ sample with $m_a = 17.5\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. Cut 0 corresponds to the initial number of events. Cut 1 requires the single lepton trigger. Cut 2 requires 2 identified leptons. Cut 3 requires the Z-boson mass window. Cut 4 requires 2 reconstructed $a\to b\bar{b}$ candidates. Cut 5a requires 2 identified $a\to b\bar{b}$ candidates in the 1HPC1LPC region. Cut 6a requires the 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region to be inside the Higgs mass window. Cut 5b requires 2 identified $a\to b\bar{b}$ candidates in the 2HPC region. Cut 6b requires the 2 $a\to b\bar{b}$ candidates in the 2HPC region to be inside the Higgs mass window.
Event yields for a simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ sample with $m_a = 17.5\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. Cut 0 corresponds to the initial number of events. Cut 1 requires the single lepton trigger. Cut 2 requires 2 identified leptons. Cut 3 requires the Z-boson mass window. Cut 4 requires 2 reconstructed $a\to b\bar{b}$ candidates. Cut 5a requires 2 identified $a\to b\bar{b}$ candidates in the 1HPC1LPC region. Cut 6a requires the 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region to be inside the Higgs mass window. Cut 5b requires 2 identified $a\to b\bar{b}$ candidates in the 2HPC region. Cut 6b requires the 2 $a\to b\bar{b}$ candidates in the 2HPC region to be inside the Higgs mass window.
Background yield table for Z+jets, $t\bar{t}$, and rare sources. Observed data yield. Signal $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ yield with $m_a = 20\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$, with a branching ratio set to 1 for the $H \rightarrow aa$ decay, whereas the ATLAS figure attached to this entry instead uses the upper-limit branching ratio (smaller than 1). The table includes the yields in two signal regions with leptons consistent with an on-shell Z-boson decay, one with 2 $a\to b\bar{b}$ candidates in the 2HPC region and one with 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region. The table also includes the yields in four control regions, one with leptons consistent with an on-shell Z-boson decay and 2 $a\to b\bar{b}$ candidates in the Low Purity Category (LPC), and three others where the leptons are not consistent an on-shell Z-boson decay.
Background yield table for Z+jets, $t\bar{t}$, and rare sources. Observed data yield. Signal $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ yield with $m_a = 20\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. The table includes the yields in two signal regions with leptons consistent with an on-shell Z-boson decay, one with 2 $a\to b\bar{b}$ candidates in the 2HPC region and one with 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region. The table also includes the yields in four control regions, one with leptons consistent with an on-shell Z-boson decay and 2 $a\to b\bar{b}$ candidates in the Low Purity Category (LPC), and three others where the leptons are not consistent an on-shell Z-boson decay.
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.
Several extensions of the Standard Model predict the production of dark matter particles at the LHC. An uncharted signature of dark matter particles produced in association with $VV=W^\pm W^\mp$ or $ZZ$ pairs from a decay of a dark Higgs boson $s$ is searched for using 139 fb$^{-1}$ of $pp$ collisions recorded by the ATLAS detector at a center-of-mass energy of 13 TeV. The $s\to V(q\bar q)V(q\bar q)$ decays are reconstructed with a novel technique aimed at resolving the dense topology from boosted $VV$ pairs using jets in the calorimeter and tracking information. Dark Higgs scenarios with $m_s > 160$ GeV are excluded.
Data overlaid on SM background post-fit yields stacked in each SR and CR category and E<sub>T</sub><sup>miss</sup> bin with the maximum-likelihood estimators set to the conditional values of the CR-only fit, and propagated to SR and CRs. Pre-fit uncertainties cover differences between the data and pre-fit background prediction.
Dominant sources of uncertainty for three dark Higgs scenarios after the fit to Asimov data generated from the expected values of the maximum-likelihood estimators including predicted signals with m<sub>Z'</sub> = 1 TeV and m<sub>s</sub> of (a) 160 GeV, (b) 235 GeV, and (c) 310 GeV. The uncertainty in the fitted signal yield relative to the theory prediction is presented. Total is the quadrature sum of statistical and total systematic uncertainties, which consider correlations.
The ratios (μ) of the 95% C.L. upper limits on the combined s→ W<sup>±</sup>W<sup>∓</sup> and s→ ZZ cross section to simplified model expectations for the m<sub>Z'</sub>=0.5 TeV scenario, for various m<sub>s</sub> hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m<sub>s</sub>=160 GeV, discussed in the text.
The ratios (μ) of the 95% C.L. upper limits on the combined s→ W<sup>±</sup>W<sup>∓</sup> and s→ ZZ cross section to simplified model expectations for the m<sub>Z'</sub>=1 TeV scenario, for various m<sub>s</sub> hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m<sub>s</sub>=160 GeV, discussed in the text.
The ratios (μ) of the 95% C.L. upper limits on the combined s→ W<sup>±</sup>W<sup>∓</sup> and s→ ZZ cross section to simplified model expectations for the m<sub>Z'</sub>=1.7 TeV scenario, for various m<sub>s</sub> hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m<sub>s</sub>=160 GeV, discussed in the text.
Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s→ VV) for m<sub>Z'</sub>=0.5 TeV signal points. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s→ VV) process for m<sub>Z'</sub>=0.5 TeV, shown in dashed blue.
Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s→ VV) for m<sub>Z'</sub>=1 TeV signal points. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s→ VV) process for m<sub>Z'</sub>=1 TeV, shown in dashed blue.
Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s→ VV) for m<sub>Z'</sub>=1.7 TeV signal points. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s→ VV) process for m<sub>Z'</sub>=1.7 TeV, shown in dashed blue.
SM background post-fit yields stacked in each SR and CR category and E<sub>T</sub><sup>miss</sup> bin and data overlaid with the maximum likelihood estimators set to the conditional values of the combined signal and control region fit. The hatched uncertainty band shown includes simulation statistics uncertainties, experimental systematic uncertainties, and V+jets theory modelling systematic uncertainties. Pre-fit uncertainties cover differences between the data and pre-fit background prediction.
Cumulative efficiencies for the merged category for signal samples with m<sub>s</sub>=160 GeV (a), m<sub>s</sub>=235 GeV (b) and m<sub>s</sub>=310 GeV (c), each with m<sub>Z'</sub>=1 TeV. The dark Higgs candidate selection includes stringent jet substructure requirements and typically at most one candidate is present in signal events. Here, Δ φ<sub>jets<sub>1,2,3</sub> E<sub>T</sub><sup>miss</sup></sub> is the smallest azimuthal angle between the E<sub>T</sub><sup>miss</sup> and any of the three highest-p<sub>T</sub> (leading) small-R jets.
Cumulative efficiencies for the intermediate category for signal samples with m<sub>s</sub>=160 GeV (a), m<sub>s</sub>=235 GeV (b) and m<sub>s</sub>=310 GeV (c), each with m<sub>Z'</sub>=1 TeV. The TAR+Comb algorithm reconstructs the dark Higgs candidate from a TAR jet with m<sup>TAR</sup>>60 GeV that is supplemented by up to two additional small-R jets within ΔR<sub>cone</sub>=2.5 of the TAR jet. Here, Δ φ<sub>jets<sub>1,2,3</sub> E<sub>T</sub><sup>miss</sup></sub> is the smallest azimuthal angle between the E<sub>T</sub><sup>miss</sup> and any of the three highest-p<sub>T</sub> (leading) small-R jets. For details see text.
The product of acceptance and efficiency (A × ϵ), defined as the number of signal events satisfying the full set of selection criteria in the merged or intermediate signal regions, divided by the total number of generated signal events, for the s(W<sup>±</sup>W<sup>∓</sup>) dark Higgs signal points with dark Higgs boson mass m<sub>s</sub> and Z' boson mass m<sub>Z'</sub>.
The product of acceptance and efficiency (A × ϵ), defined as the number of signal events satisfying the full set of selection criteria in the merged or intermediate signal regions, divided by the total number of generated signal events, for the s(ZZ) dark Higgs signal points with dark Higgs boson mass m<sub>s</sub> and Z' boson mass m<sub>Z'</sub>.
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 heavy neutral Higgs bosons is performed using the LHC Run 2 data, corresponding to an integrated luminosity of 139 fb$^{-1}$ of proton-proton collisions at $\sqrt{s}=13$ TeV recorded with the ATLAS detector. The search for heavy resonances is performed over the mass range 0.2-2.5 TeV for the $\tau^+\tau^-$ decay with at least one $\tau$-lepton decaying into final states with hadrons. The data are in good agreement with the background prediction of the Standard Model. In the $M_{h}^{125}$ scenario of the Minimal Supersymmetric Standard Model, values of $\tan\beta>8$ and $\tan\beta>21$ are excluded at the 95% confidence level for neutral Higgs boson masses of 1.0 TeV and 1.5 TeV, respectively, where $\tan\beta$ is the ratio of the vacuum expectation values of the two Higgs doublets.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits with one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
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