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A search for the electroweak production of pairs of charged sleptons or charginos decaying into two-lepton final states with missing transverse momentum is presented. Two simplified models of $R$-parity-conserving supersymmetry are considered: direct pair-production of sleptons ($\tilde{\ell}\tilde{\ell}$), with each decaying into a charged lepton and a $\tilde{\chi}_1^0$ neutralino, and direct pair-production of the lightest charginos $(\tilde{\chi}_1^\pm\tilde{\chi}_1^\mp)$, with each decaying into a $W$-boson and a $\tilde{\chi}_1^0$. The lightest neutralino ($\tilde{\chi}_1^0$) is assumed to be the lightest supersymmetric particle (LSP). The analyses target the experimentally challenging mass regions where $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and $m(\tilde{\chi}_1^\pm)-m(\tilde{\chi}_1^0)$ are close to the $W$-boson mass (`moderately compressed' regions). The search uses 139 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collisions recorded by the ATLAS detector at the Large Hadron Collider. No significant excesses over the expected background are observed. Exclusion limits on the simplified models under study are reported in the ($\tilde{\ell},\tilde{\chi}_1^0$) and ($\tilde{\chi}_1^\pm,\tilde{\chi}_1^0$) mass planes at 95% confidence level (CL). Sleptons with masses up to 150 GeV are excluded at 95% CL for the case of a mass-splitting between sleptons and the LSP of 50 GeV. Chargino masses up to 140 GeV are excluded at 95% CL for the case of a mass-splitting between the chargino and the LSP down to about 100 GeV.
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <b>Title: </b><em>Search for direct pair production of sleptons and charginos decaying to two leptons and neutralinos with mass splittings near the $W$ boson mass in $\sqrt{s}=13$ TeV $pp$ collisions with the ATLAS detector</em> <b>Paper website:</b> <a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2019-02/">SUSY-2019-02</a> <b>Exclusion contours</b> <ul><li><b>Sleptons:</b> <a href=?table=excl_comb_obs_nominal>Combined Observed Nominal</a> <a href=?table=excl_comb_obs_up>Combined Observed Up</a> <a href=?table=excl_comb_obs_down>Combined Observed Down</a> <a href=?table=excl_comb_exp_nominal>Combined Expected Nominal</a> <a href=?table=excl_comb_exp_up>Combined Expected Up</a> <a href=?table=excl_comb_exp_down>Combined Expected Down</a> <a href=?table=excl_comb_obs_nominal_dM>Combined Observed Nominal $(\Delta m)$</a> <a href=?table=excl_comb_obs_up_dM>Combined Observed Up $(\Delta m)$</a> <a href=?table=excl_comb_obs_down_dM>Combined Observed Down $(\Delta m)$</a> <a href=?table=excl_comb_exp_nominal_dM>Combined Expected Nominal $(\Delta m)$</a> <a href=?table=excl_comb_exp_up_dM>Combined Expected Up $(\Delta m)$</a> <a href=?table=excl_comb_exp_down_dM>Combined Expected Down $(\Delta m)$</a> <a href=?table=excl_ee_obs_nominal>$\tilde{e}_\mathrm{L,R}$ Observed Nominal</a> <a href=?table=excl_ee_exp_nominal>$\tilde{e}_\mathrm{L,R}$ Expected Nominal</a> <a href=?table=excl_eLeL_obs_nominal>$\tilde{e}_\mathrm{L}$ Observed Nominal</a> <a href=?table=excl_eLeL_exp_nominal>$\tilde{e}_\mathrm{L}$ Expected Nominal</a> <a href=?table=excl_eReR_obs_nominal>$\tilde{e}_\mathrm{R}$ Observed Nominal</a> <a href=?table=excl_eReR_exp_nominal>$\tilde{e}_\mathrm{R}$ Expected Nominal</a> <a href=?table=excl_ee_obs_nominal_dM>$\tilde{e}_\mathrm{L,R}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_ee_exp_nominal_dM>$\tilde{e}_\mathrm{L,R}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_eLeL_obs_nominal_dM>$\tilde{e}_\mathrm{L}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_eLeL_exp_nominal_dM>$\tilde{e}_\mathrm{L}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_eReR_obs_nominal_dM>$\tilde{e}_\mathrm{R}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_eReR_exp_nominal_dM>$\tilde{e}_\mathrm{R}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_mm_obs_nominal>$\tilde{\mu}_\mathrm{L,R}$ Observed Nominal</a> <a href=?table=excl_mm_exp_nominal>$\tilde{\mu}_\mathrm{L,R}$ Expected Nominal</a> <a href=?table=excl_mLmL_obs_nominal>$\tilde{\mu}_\mathrm{L}$ Observed Nominal</a> <a href=?table=excl_mLmL_exp_nominal>$\tilde{\mu}_\mathrm{L}$ Expected Nominal</a> <a href=?table=excl_mRmR_obs_nominal>$\tilde{\mu}_\mathrm{R}$ Observed Nominal</a> <a href=?table=excl_mRmR_exp_nominal>$\tilde{\mu}_\mathrm{R}$ Expected Nominal</a> <a href=?table=excl_mm_obs_nominal_dM>$\tilde{\mu}_\mathrm{L,R}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_mm_exp_nominal_dM>$\tilde{\mu}_\mathrm{L,R}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_mLmL_obs_nominal_dM>$\tilde{\mu}_\mathrm{L}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_mLmL_exp_nominal_dM>$\tilde{\mu}_\mathrm{L}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_mRmR_obs_nominal_dM>$\tilde{\mu}_\mathrm{R}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_mRmR_exp_nominal_dM>$\tilde{\mu}_\mathrm{R}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_comb_obs_nominal_SR0j>Combined Observed Nominal SR-0j</a> <a href=?table=excl_comb_exp_nominal_SR0j>Combined Expected Nominal SR-0j</a> <a href=?table=excl_comb_obs_nominal_SR1j>Combined Observed Nominal SR-1j</a> <a href=?table=excl_comb_exp_nominal_SR1j>Combined Expected Nominal SR-1j</a> <li><b>Charginos:</b> <a href=?table=excl_c1c1_obs_nominal>Observed Nominal</a> <a href=?table=excl_c1c1_obs_up>Observed Up</a> <a href=?table=excl_c1c1_obs_down>Observed Down</a> <a href=?table=excl_c1c1_exp_nominal>Expected Nominal</a> <a href=?table=excl_c1c1_exp_nominal>Expected Up</a> <a href=?table=excl_c1c1_exp_nominal>Expected Down</a> <a href=?table=excl_c1c1_obs_nominal_dM>Observed Nominal $(\Delta m)$</a> <a href=?table=excl_c1c1_obs_up_dM>Observed Up $(\Delta m)$</a> <a href=?table=excl_c1c1_obs_down_dM>Observed Down $(\Delta m)$</a> <a href=?table=excl_c1c1_exp_nominal_dM>Expected Nominal $(\Delta m)$</a> <a href=?table=excl_c1c1_exp_nominal_dM>Expected Up $(\Delta m)$</a> <a href=?table=excl_c1c1_exp_nominal_dM>Expected Down $(\Delta m)$</a> </ul> <b>Upper Limits</b> <ul><li><b>Sleptons:</b> <a href=?table=UL_slep>ULs</a> <li><b>Charginos:</b> <a href=?table=UL_c1c1>ULs</a> </ul> <b>Pull Plots</b> <ul><li><b>Sleptons:</b> <a href=?table=pullplot_slep>SRs summary plot</a> <li><b>Charginos:</b> <a href=?table=pullplot_c1c1>SRs summary plot</a> </ul> <b>Cutflows</b> <ul><li><b>Sleptons:</b> <a href=?table=Cutflow_slep_SR0j>Towards SR-0J</a> <a href=?table=Cutflow_slep_SR1j>Towards SR-1J</a> <li><b>Charginos:</b> <a href=?table=Cutflow_SRs>Towards SRs</a> </ul> <b>Acceptance and Efficiencies</b> <ul><li><b>Sleptons:</b> <a href=?table=Acceptance_SR0j_MT2_100_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_100_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_110_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_110_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_120_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_120_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_130_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_130_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_100_105>SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_100_105>SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_105_110>SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_105_110>SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_110_115>SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_110_115>SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_115_120>SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_115_120>SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_120_125>SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_125_130>SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_130_140>SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_130_140>SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_140_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_140_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_100_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[100,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_100_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[100,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_110_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[110,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_110_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[110,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_120_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[120,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_120_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[120,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_130_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[130,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_130_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[130,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_100_105>SR-1j $m_{\mathrm{T2}}^{100} \in[100,105)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_100_105>SR-1j $m_{\mathrm{T2}}^{100} \in[100,105)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_105_110>SR-1j $m_{\mathrm{T2}}^{100} \in[105,110)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_105_110>SR-1j $m_{\mathrm{T2}}^{100} \in[105,110)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_110_115>SR-1j $m_{\mathrm{T2}}^{100} \in[110,115)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_110_115>SR-1j $m_{\mathrm{T2}}^{100} \in[110,115)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_115_120>SR-1j $m_{\mathrm{T2}}^{100} \in[115,120)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_115_120>SR-1j $m_{\mathrm{T2}}^{100} \in[115,120)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_120_125>SR-1j $m_{\mathrm{T2}}^{100} \in[120,125)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_125_130>SR-1j $m_{\mathrm{T2}}^{100} \in[125,130)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_130_140>SR-1j $m_{\mathrm{T2}}^{100} \in[130,140)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_130_140>SR-1j $m_{\mathrm{T2}}^{100} \in[130,140)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_140_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[140,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_140_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[140,\infty)$ Efficiency</a> <li><b>Charginos:</b> <a href=?table=Acceptance_SR_DF_81_1_SF_77_1>SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ Acceptance</a> <a href=?table=Efficiency_SR_DF_81_1_SF_77_1>SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ Efficiency</a> <a href=?table=Acceptance_SR_DF_81_1>SR-DF BDT-signal$\in(0.81,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_81_1>SR-DF BDT-signal$\in(0.81,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_82_1>SR-DF BDT-signal$\in(0.82,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_82_1>SR-DF BDT-signal$\in(0.82,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_83_1>SR-DF BDT-signal$\in(0.83,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_83_1>SR-DF BDT-signal$\in(0.83,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_84_1>SR-DF BDT-signal$\in(0.84,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_84_1>SR-DF BDT-signal$\in(0.84,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_85_1>SR-DF BDT-signal$\in(0.85,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_85_1>SR-DF BDT-signal$\in(0.85,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_81_8125>SR-DF BDT-signal$\in(0.81,8125]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_81_8125>SR-DF BDT-signal$\in(0.81,8125]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8125_815>SR-DF BDT-signal$\in(0.8125,815]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8125_815>SR-DF BDT-signal$\in(0.8125,815]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_815_8175>SR-DF BDT-signal$\in(0.815,8175]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_815_8175>SR-DF BDT-signal$\in(0.815,8175]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8175_82>SR-DF BDT-signal$\in(0.8175,82]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8175_82>SR-DF BDT-signal$\in(0.8175,82]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_82_8225>SR-DF BDT-signal$\in(0.82,8225]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_82_8225>SR-DF BDT-signal$\in(0.82,8225]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8225_825>SR-DF BDT-signal$\in(0.8225,825]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8225_825>SR-DF BDT-signal$\in(0.8225,825]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_825_8275>SR-DF BDT-signal$\in(0.825,8275]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_825_8275>SR-DF BDT-signal$\in(0.825,8275]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8275_83>SR-DF BDT-signal$\in(0.8275,83]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8275_83>SR-DF BDT-signal$\in(0.8275,83]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_83_8325>SR-DF BDT-signal$\in(0.83,8325]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_83_8325>SR-DF BDT-signal$\in(0.83,8325]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8325_835>SR-DF BDT-signal$\in(0.8325,835]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8325_835>SR-DF BDT-signal$\in(0.8325,835]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_835_8375>SR-DF BDT-signal$\in(0.835,8375]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_835_8375>SR-DF BDT-signal$\in(0.835,8375]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8375_84>SR-DF BDT-signal$\in(0.8375,84]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8375_84>SR-DF BDT-signal$\in(0.8375,84]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_84_845>SR-DF BDT-signal$\in(0.85,845]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_84_845>SR-DF BDT-signal$\in(0.85,845]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_845_85>SR-DF BDT-signal$\in(0.845,85]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_845_85>SR-DF BDT-signal$\in(0.845,85]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_85_86>SR-DF BDT-signal$\in(0.85,86]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_85_86>SR-DF BDT-signal$\in(0.85,86]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_86_1>SR-DF BDT-signal$\in(0.86,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_86_1>SR-DF BDT-signal$\in(0.86,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_77_1>SR-SF BDT-signal$\in(0.77,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_77_1>SR-SF BDT-signal$\in(0.77,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_78_1>SR-SF BDT-signal$\in(0.78,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_78_1>SR-SF BDT-signal$\in(0.78,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_79_1>SR-SF BDT-signal$\in(0.79,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_79_1>SR-SF BDT-signal$\in(0.79,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_80_1>SR-SF BDT-signal$\in(0.80,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_80_1>SR-SF BDT-signal$\in(0.80,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_77_775>SR-SF BDT-signal$\in(0.77,0.775]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_77_775>SR-SF BDT-signal$\in(0.77,0.775]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_775_78>SR-SF BDT-signal$\in(0.775,0.78]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_775_78>SR-SF BDT-signal$\in(0.775,0.78]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_78_785>SR-SF BDT-signal$\in(0.78,0.785]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_78_785>SR-SF BDT-signal$\in(0.78,0.785]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_785_79>SR-SF BDT-signal$\in(0.785,0.79]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_785_79>SR-SF BDT-signal$\in(0.785,0.79]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_79_795>SR-SF BDT-signal$\in(0.79,0.795]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_79_795>SR-SF BDT-signal$\in(0.79,0.795]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_795_80>SR-SF BDT-signal$\in(0.795,0.80]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_795_80>SR-SF BDT-signal$\in(0.795,0.80]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_80_81>SR-SF BDT-signal$\in(0.80,0.81]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_80_81>SR-SF BDT-signal$\in(0.80,0.81]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_81_1>SR-SF BDT-signal$\in(0.81,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_81_1>SR-SF BDT-signal$\in(0.81,1]$ Efficiency</a></ul> <b>Truth Code snippets</b>, <b>SLHA</b> and <b>machine learning</b> files are available under "Resources" (purple button on the left)
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
Cutflow table for the slepton signal sample with $m(\tilde{\ell},\tilde{\chi}_1^0) = (100,70)$ GeV, in the SR-0J $m_{\mathrm{T2}}^{100} \in [100,\infty)$ region. The yields include the process cross section and are weighted to the 139 fb$^{-1}$ luminosity. 246000 events were generated for the sample.
Cutflow table for the slepton signal sample with $m(\tilde{\ell},\tilde{\chi}_1^0) = (100,70)$ GeV, in the SR-1J $m_{\mathrm{T2}}^{100} \in [100,\infty)$ region. The yields include the process cross section and are weighted to the 139 fb$^{-1}$ luminosity. 246000 events were generated for the sample.
Observed and expected exclusion limits on SUSY simplified models, with observed upper limits on signal cross-section (fb) overlaid, for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.
The upper panel shows the observed number of events in each of the binned SRs defined in Table 3, together with the expected SM backgrounds obtained after applying the efficiency correction method to compute the number of expected FSB events. `Others' include the non-dominant background sources, e.g. $t \bar{t}$+$V$, Higgs boson and Drell--Yan events. The uncertainty band includes systematic and statistical errors from all sources. The distributions of two signal points with mass splittings $\Delta m(\tilde{\ell},\tilde{\chi}_1^0) = m(\tilde{\ell})-m(\tilde{\chi}_1^0) = 30$ GeV and $\Delta m(\tilde{\ell},\tilde{\chi}_1^0) = m(\tilde{\ell})-m(\tilde{\chi}_1^0) = 50$ GeV are overlaid. The lower panel shows the significance as defined in Ref. [115].
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,0.8125]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,0.8125]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8125,0.815]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8125,0.815]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.815,0.8175]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.815,0.8175]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8175,0.82]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8175,0.82]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,0.8225]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,0.8225]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8225,0.825]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8225,0.825]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.825,0.8275]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.825,0.8275]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8275,0.83]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8275,0.83]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,0.8325]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,0.8325]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8325,0.835]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8325,0.835]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.835,0.8375]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.835,0.8375]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8375,0.84]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8375,0.84]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,0.845]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,0.845]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.845,0.85]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.845,0.85]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,0.86]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,0.86]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.86,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.86,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,0.775]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,0.775]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.775,0.78]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.775,0.78]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,0.785]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,0.785]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.785,0.79]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.785,0.79]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,0.795]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,0.795]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.795,0.80]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.795,0.80]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,0.81]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,0.81]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
Cutflow table for the chargino signal sample with $m\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0=(125,25)$ GeV, in the SR-SF BDT-signal$\in (0.77,1]$ and SR-DF BDT-signal$\in (0.81,1]$ regions. The yields include the process cross-section and are weighted to the 139 fb$^{-1}$ luminosity. 170000 events were generated for the sample.
Observed and expected exclusion limits on SUSY simplified models, with observed upper limits on signal cross-section (fb) overlaid, for chargino-pair production with $W$-boson-mediated decays in the $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ plane. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
The upper panel shows the observed number of events in the SRs defined in Table 3, together with the expected SM backgrounds obtained after the background fit in the CRs. `Others' include the non-dominant background sources, e.g.$t \bar{t}$+$V$, Higgs boson and Drell--Yan events. The uncertainty band includes systematic and statistical errors from all sources. Distributions for three benchmark signal points are overlaid for comparison. The lower panel shows the significance as defined in Ref. [115].
A search for heavy Higgs bosons produced in association with a vector boson and decaying into a pair of vector bosons is performed in final states with two leptons (electrons or muons) of the same electric charge, missing transverse momentum and jets. A data sample of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018 is used. The data correspond to a total integrated luminosity of 139 fb$^{-1}$. The observed data are in agreement with Standard Model background expectations. The results are interpreted using higher-dimensional operators in an effective field theory. Upper limits on the production cross-section are calculated at 95% confidence level as a function of the heavy Higgs boson's mass and coupling strengths to vector bosons. Limits are set in the Higgs boson mass range from 300 to 1500 GeV, and depend on the assumed couplings. The highest excluded mass for a heavy Higgs boson with the coupling combinations explored is 900 GeV. Limits on coupling strengths are also provided.
Measurements of distributions of charged particles produced in proton-proton collisions with a centre-of-mass energy of 13 TeV are presented. The data were recorded by the ATLAS detector at the LHC and correspond to an integrated luminosity of 151 $\mu$b$^{-1}$. The particles are required to have a transverse momentum greater than 100 MeV and an absolute pseudorapidity less than 2.5. The charged-particle multiplicity, its dependence on transverse momentum and pseudorapidity and the dependence of the mean transverse momentum on multiplicity are measured in events containing at least two charged particles satisfying the above kinematic criteria. The results are corrected for detector effects and compared to the predictions from several Monte Carlo event generators.
The average charged-particle muliplicity per unit of rapidity for ETARAP=0 as a function of the centre-of-mass energy.
The extrapolated ($\tau > 30$ ps) average charged-particle muliplicity per unit of rapidity for ETARAP=0 as a function of the centre-of-mass energy.
Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 13000 GeV as a function of pseudorapidity for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.
Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 13000 GeV as a function of transverse momentum for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.
Charged-particle multiplicity distribution in proton-proton collisions at a centre-of mass energy of 13000 GeV for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.
Average transverse momentum in proton-proton collisions at a centre-of mass energy of 13000 GeV as a function of the number of charged particles in the event for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.
Extrapolated ($\tau > 30$ ps) charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 13000 GeV as a function of pseudorapidity for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.
Extrapolated ($\tau > 30$ ps) charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 13000 GeV as a function of transverse momentum for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.
Extrapolated ($\tau > 30$ ps) charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 13000 GeV for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.
Extrapolated ($\tau > 30$ ps) average transverse momentum in proton-proton collisions at a centre-of mass energy of 13000 GeV as a function of the number of charged particles in the event for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.
This paper presents studies of Bose-Einstein correlations (BEC) in proton-proton collisions at a centre-of-mass energy of 13 TeV, using data from the ATLAS detector at the CERN Large Hadron Collider. Data were collected in a special low-luminosity configuration with a minimum-bias trigger and a high-multiplicity track trigger, accumulating integrated luminosities of 151 $\mu$b$^{-1}$ and 8.4 nb$^{-1}$ respectively. The BEC are measured for pairs of like-sign charged particles, each with $|\eta|$ < 2.5, for two kinematic ranges: the first with particle $p_T$ > 100 MeV and the second with particle $p_T$ > 500 MeV. The BEC parameters, characterizing the source radius and particle correlation strength, are investigated as functions of charged-particle multiplicity (up to 300) and average transverse momentum of the pair (up to 1.5 GeV). The double-differential dependence on charged-particle multiplicity and average transverse momentum of the pair is also studied. The BEC radius is found to be independent of the charged-particle multiplicity for high charged-particle multiplicity (above 100), confirming a previous observation at lower energy. This saturation occurs independent of the transverse momentum of the pair.
Comparison of single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q) and C<sub>2</sub><sup>MC</sup>(Q), with the two-particle double-ratio correlation function, R<sub>2</sub>(Q), for the high-multiplicity track (HMT) events using the opposite hemisphere (OHP) like-charge particles pairs reference sample for k<sub>T</sub> - interval 1000 < k<sub>T</sub> ≤ 1500 MeV.
Comparison of single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q) and C<sub>2</sub><sup>MC</sup>(Q), with the two-particle double-ratio correlation function, R<sub>2</sub>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - interval 1000 < k<sub>T</sub> ≤ 1500 MeV.
The Bose-Einstein correlation (BEC) parameter R as a function of n<sub>ch</sub> for MB events using different MC generators in the calculation of R<sub>2</sub>(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameter R as a function of n<sub>ch</sub> for HMT events using different MC generators in the calculation of R<sub>2</sub>(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameter R as a function of k<sub>T</sub> for MB events using different MC generators in the calculation of R<sub>2</sub>(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameter λ as a function of k<sub>T</sub> for MB events using different MC generators in the calculation of R<sub>2</sub>(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The two-particle double-ratio correlation function, R<sub>2</sub>(Q), for pp collisions for track p<sub>T</sub> >100 MeV at √s=13 TeV in the multiplicity interval 71 ≤ n<sub>ch</sub> < 80 for the minimum-bias (MB) events. The blue dashed and red solid lines show the results of the exponential and Gaussian fits, respectively. The region excluded from the fits is shown. The statistical uncertainty and the systematic uncertainty for imperfections in the data reconstruction procedure are added in quadrature.
The two-particle double-ratio correlation function, R<sub>2</sub>(Q), for pp collisions for track p<sub>T</sub> >100 MeV at √s=13 TeV in the multiplicity interval 231 ≤ n<sub>ch</sub> < 300 for the high-multiplicity track (HMT) events. The blue dashed and red solid lines show the results of the exponential and Gaussian fits, respectively. The region excluded from the fits is shown. The statistical uncertainty and the systematic uncertainty for imperfections in the data reconstruction procedure are added in quadrature.
The dependence of the correlation strength, λ(m<sub>ch</sub>), on rescaled multiplicity, m<sub>ch</sub>, obtained from the exponential fit of the R<sub>2</sub>(Q) correlation functions for tracks with p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m<sub>ch</sub>) for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively.
The dependence of the correlation strength, λ(m<sub>ch</sub>), on rescaled multiplicity, m<sub>ch</sub>, obtained from the exponential fit of the R<sub>2</sub>(Q) correlation functions for tracks with p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m<sub>ch</sub>) for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively.
The dependence of the correlation strength, λ(m<sub>ch</sub>), on rescaled multiplicity, m<sub>ch</sub>, obtained from the exponential fit of the R<sub>2</sub>(Q) correlation functions for tracks with p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m<sub>ch</sub>) for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively.
The dependence of the correlation strength, λ(m<sub>ch</sub>), on rescaled multiplicity, m<sub>ch</sub>, obtained from the exponential fit of the R<sub>2</sub>(Q) correlation functions for tracks with p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m<sub>ch</sub>) for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively.
The dependence of the source radius, R(m<sub>ch</sub>), on m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively.
The dependence of the source radius, R(m<sub>ch</sub>), on m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively.
The dependence of the source radius, R(m<sub>ch</sub>), on m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively.
The dependence of the source radius, R(m<sub>ch</sub>), on m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively.
The dependence of the R(m<sub>ch</sub>) on ∛m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively
The dependence of the R(m<sub>ch</sub>) on ∛m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively
The dependence of the R(m<sub>ch</sub>) on ∛m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively
The dependence of the R(m<sub>ch</sub>) on ∛m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively
Comparison of single-ratio two-particle correlation functions, using the unlike-charge particle (UCP) pair reference sample, for minimum-bias (MB) events, showing C<sub>2</sub><sup>data</sup>(Q) (top panel) at 13 TeV (black circles) and 7 TeV (open blue circles), and the ratio of C<sub>2</sub><sup>7 TeV</sup> (Q) to C<sub>2</sub><sup>13 TeV</sup> (Q) (bottom panel). Comparison of C<sub>2</sub><sup>data</sup> (Q) for representative multiplicity region 3.09 < m<sub>ch</sub> ≤ 3.86. The statistical and systematic uncertainties, combined in quadrature, are presented. The systematic uncertainties include track efficiency, Coulomb correction, non-closure and multiplicity-unfolding uncertainties.
Comparison of single-ratio two-particle correlation functions, using the unlike-charge particle (UCP) pair reference sample, for minimum-bias (MB) events, showing C<sub>2</sub><sup>data</sup>(Q) (top panel) at 13 TeV (black circles) and 7 TeV (open blue circles), and the ratio of C<sub>2</sub><sup>7 TeV</sup> (Q) to C<sub>2</sub><sup>13 TeV</sup> (Q) (bottom panel). Comparison of C<sub>2</sub><sup>data</sup> (Q) for representative k<sub>T</sub> region 400 < k<sub>T</sub> ≤500 MeV. The statistical and systematic uncertainties, combined in quadrature, are presented. The systematic uncertainties include track efficiency, Coulomb correction, non-closure and multiplicity-unfolding uncertainties.
The k<sub>T</sub> dependence of the correlation strength, λ(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k<sub>T</sub>).
The k<sub>T</sub> dependence of the correlation strength, λ(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k<sub>T</sub>).
The k<sub>T</sub> dependence of the correlation strength, λ(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k<sub>T</sub>).
The k<sub>T</sub> dependence of the correlation strength, λ(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k<sub>T</sub>).
The k<sub>T</sub> dependence of the source radius, R(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k<sub>T</sub>).
The k<sub>T</sub> dependence of the source radius, R(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k<sub>T</sub>).
The k<sub>T</sub> dependence of the source radius, R(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k<sub>T</sub>).
The k<sub>T</sub> dependence of the source radius, R(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k<sub>T</sub>).
The two-dimensional dependence on m<sub>ch</sub> and k<sub>T</sub> for p<sub>T</sub> > 100 MeV for the correlation strength, λ, obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions using the MB sample for m<sub>ch</sub> ≤ 3.08 and the HMT sample for m<sub>ch</sub> > 3.08.
The two-dimensional dependence on m<sub>ch</sub> and k<sub>T</sub> for p<sub>T</sub> > 100 MeV for the source radius, R, obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions using the MB sample for m<sub>ch</sub> ≤ 3.08 and the HMT sample for m<sub>ch</sub> > 3.08.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m<sub>ch</sub> > 3.0 for tracks with p<sub>T</sub> >100 MeV and for m<sub>ch</sub> > 2.8 for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m<sub>ch</sub> > 3.0 for tracks with p<sub>T</sub> >100 MeV and for m<sub>ch</sub> > 2.8 for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m<sub>ch</sub> > 3.0 for tracks with p<sub>T</sub> >100 MeV and for m<sub>ch</sub> > 2.8 for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m<sub>ch</sub> > 3.0 for tracks with p<sub>T</sub> >100 MeV and for m<sub>ch</sub> > 2.8 for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p<sub>T</sub> >100 MeV and for tracks with p<sub>T</sub> >500 MeV, respectively.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), in dependence on the multiplicity, m<sub>ch</sub>, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p<sub>T</sub> > 100 MeV at √s = 13 TeV. Statistical uncertainties for √χ<sup>2</sup>/ndf>1 are corrected by the √χ<sup>2</sup>/ndf. The total uncertainties are shown.
The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), in dependence on the multiplicity, m<sub>ch</sub>, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p<sub>T</sub> > 500 MeV at √s = 13 TeV. Statistical uncertainties for √χ<sup>2</sup>/ndf>1 are corrected by the √χ<sup>2</sup>/ndf. The total uncertainties are shown.
The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), in dependence on the pair transverse momentum, k<sub>T</sub>, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p<sub>T</sub> > 100 MeV at √s = 13 TeV. Statistical uncertainties for √χ<sup>2</sup>/ndf>1 are corrected by the √χ<sup>2</sup>/ndf. The total uncertainties are shown.
The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), in dependence on the pair transverse momentum, k<sub>T</sub>, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p<sub>T</sub> > 500 MeV at √s = 13 TeV. Statistical uncertainties for √χ<sup>2</sup>/ndf>1 are corrected by the √χ<sup>2</sup>/ndf. The total uncertainties are shown.
A search for events with two displaced vertices from long-lived particles (LLP) pairs using data collected by the ATLAS detector at the LHC is presented. This analysis uses 139~fb$^{-1}$ of proton-proton collision data at $\sqrt{s}=13$ TeV recorded in 2015-2018. The search employs techniques for reconstructing vertices of LLPs decaying to jets in the muon spectrometer displaced between 3 m and 14 m with respect to the primary interaction vertex. The observed numbers of events are consistent with the expected background and limits for several benchmark signals are determined. For the Higgs boson with a mass of 125 GeV, the paper reports the first exclusion limits for branching fractions into neutral long-lived particles below 0.1%, while branching fractions above 10% are excluded at 95% confidence level for LLP proper lifetimes ranging from 4 cm to 72.4 m. In addition, the paper present the first results for the decay of LLPs into into $t\bar{t}$ in the ATLAS muon spectrometer.
Efficiency for the Muon RoI Cluster trigger as a function of the decay position of the LLP for some scalar portal samples in the MS barrel for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, “RPC 1/2” represent the first/second stations of RPC chambers, “TGC 1” represents the first stations of TGC chambers and “L/S” indicate whether they are in the Large or Small sectors.
Efficiency for the Muon RoI Cluster trigger as a function of the decay position of the LLP for some scalar portal samples in the MS endcaps for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, “RPC 1/2” represent the first/second stations of RPC chambers, “TGC 1” represents the first stations of TGC chambers and “L/S” indicate whether they are in the Large or Small sectors.
Efficiency to reconstruct an MS DV in the MS barrel fiducial volume as a function of the transverse decay position of the LLP for scalar portal samples with $m_\varPhi=125$~\GeV\ for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling. The vertical lines show the relevant detector boundaries, where ``HCal end'' is the outer limit of the hadronic calorimeter, ``MDT 1/2'' represent the first/second stations of MDT chambers and ``L/S'' indicate whether they are in Large or Small sectors.
Efficiency to reconstruct an MS DV in the MS endcaps fiducial volume as a function of the longitudinal decay position of the LLP for scalar portal samples with $m_\varPhi=125$~\GeV\ for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling. The vertical lines show the relevant detector boundaries, where ``HCal end'' is the outer limit of the hadronic calorimeter, ``MDT 1/2'' represent the first/second stations of MDT chambers and ``L/S'' indicate whether they are in Large or Small sectors.
Expected and observed 95% CL limits on ($\sigma / \sigma_{\text{SM}}) \times B$ for $m_\phi=125$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Efficiency for the Muon RoI Cluster trigger in the MS barrel fiducial volume as a function of the transverse decay position of the LLP for non-SM Higgs benchmark samples for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling. The vertical lines show the relevant detector boundaries, where ``HCal end'' is the outer limit of the hadronic calorimeter, RPC 1/2 represent the first/second stations of RPC chambers, TGC 1 represents the first stations of TGC chambers and L/S indicate whether they are in the Large or Small sectors. The dependence on detector geometry can be seen by looking at the various detector boundaries depicted by dashed lines in the plots. In the barrel the trigger efficiency increases when the LLP decays are close to the end of the hadronic calorimeter (r ~ 4 m) and substantially decreases as the decay occurs closer to the middle station of the muon spectrometer (r ~ 7 m). For decays occurring close to the middle station the charged hadrons and photons (and their EM showers) are not spatially separated, resulting in low efficiency (the same reasoning is applicable to decays in the endcap regions).
Efficiency for the Muon RoI Cluster trigger in the MS endcaps fiducial volume as a function of the longitudinal decay position of the LLP for non-SM Higgs benchmark samples for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling. The vertical lines show the relevant detector boundaries, where ``HCal end'' is the outer limit of the hadronic calorimeter, RPC 1/2 represent the first/second stations of RPC chambers, TGC 1 represents the first stations of TGC chambers and L/S indicate whether they are in the Large or Small sectors. The dependence on detector geometry can be seen by looking at the various detector boundaries depicted by dashed lines in the plots. In the barrel the trigger efficiency increases when the LLP decays are close to the end of the hadronic calorimeter (r ~ 4 m) and substantially decreases as the decay occurs closer to the middle station of the muon spectrometer (r ~ 7 m). For decays occurring close to the middle station the charged hadrons and photons (and their EM showers) are not spatially separated, resulting in low efficiency (the same reasoning is applicable to decays in the endcap regions).
Efficiency for the Muon RoI Cluster trigger in the MS barrel fiducial volume as a function of the transverse decay position of the LLP for non-SM Higgs benchmark samples for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling. The vertical lines show the relevant detector boundaries, where ``HCal end'' is the outer limit of the hadronic calorimeter, RPC 1/2 represent the first/second stations of RPC chambers, TGC 1 represents the first stations of TGC chambers and L/S indicate whether they are in the Large or Small sectors. The dependence on detector geometry can be seen by looking at the various detector boundaries depicted by dashed lines in the plots. In the barrel the trigger efficiency increases when the LLP decays are close to the end of the hadronic calorimeter (r ~ 4 m) and substantially decreases as the decay occurs closer to the middle station of the muon spectrometer (r ~ 7 m). For decays occurring close to the middle station the charged hadrons and photons (and their EM showers) are not spatially separated, resulting in low efficiency (the same reasoning is applicable to decays in the endcap regions).
Efficiency for the Muon RoI Cluster trigger in the MS endcaps fiducial volume as a function of the longitudinal decay position of the LLP for non-SM Higgs benchmark samples for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling. The vertical lines show the relevant detector boundaries, where ``HCal end'' is the outer limit of the hadronic calorimeter, RPC 1/2 represent the first/second stations of RPC chambers, TGC 1 represents the first stations of TGC chambers and L/S indicate whether they are in the Large or Small sectors. The dependence on detector geometry can be seen by looking at the various detector boundaries depicted by dashed lines in the plots. In the barrel the trigger efficiency increases when the LLP decays are close to the end of the hadronic calorimeter (r ~ 4 m) and substantially decreases as the decay occurs closer to the middle station of the muon spectrometer (r ~ 7 m). For decays occurring close to the middle station the charged hadrons and photons (and their EM showers) are not spatially separated, resulting in low efficiency (the same reasoning is applicable to decays in the endcap regions).
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi = 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi = 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi = 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi = 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi = 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi = 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi = 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi = 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency of the Muon RoI Cluster trigger in the MS fiducial volume as a function of the LLP boost and decay position for scalar portal samples with $m_\varPhi \ne 125$ GeV for events passing the data quality requirements and having a reconstructed primary vertex. These efficiency distributions are based solely on MC simulation, without any corrections applied for mismodeling.
Efficiency to reconstruct an MS DV in the MS barrel fiducial volume as a function of transverse decay position of the LLP for non-SM Higgs benchmark samples for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, MDT 1/2 represent the first/second stations of MDT chambers and L/S indicate whether they are in Large or Small sectors.
Efficiency to reconstruct an MS DV in the MS endcaps fiducial volume as a function of longitudinal decay position of the LLP for non-SM Higgs benchmark samples for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, MDT 1/2 represent the first/second stations of MDT chambers and L/S indicate whether they are in Large or Small sectors.
Efficiency to reconstruct an MS DV in the MS barrel fiducial volume as a function of transverse decay position of the LLP for non-SM Higgs benchmark samples for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, MDT 1/2 represent the first/second stations of MDT chambers and L/S indicate whether they are in Large or Small sectors.
Efficiency to reconstruct an MS DV in the MS endcaps fiducial volume as a function of longitudinal decay position of the LLP for non-SM Higgs benchmark samples for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, MDT 1/2 represent the first/second stations of MDT chambers and L/S indicate whether they are in Large or Small sectors.
Efficiency to reconstruct an MS DV in the MS barrel fiducial volume as a function of the transverse decay position of the LLP for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, MDT 1/2 represent the first/second stations of MDT chambers and L/S indicate whether they are in Large or Small sectors.
Efficiency to reconstruct an MS DV in the MS endcaps fiducial volume as a function of the longitudinal decay position of the LLP for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, MDT 1/2 represent the first/second stations of MDT chambers and L/S indicate whether they are in Large or Small sectors.
Efficiency to reconstruct an MS DV in the MS barrel fiducial volume as a function of the transverse decay position of the LLP for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, MDT 1/2 represent the first/second stations of MDT chambers and L/S indicate whether they are in Large or Small sectors.
Efficiency to reconstruct an MS DV in the MS endcaps fiducial volume as a function of the longitudinal decay position of the LLP for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, MDT 1/2 represent the first/second stations of MDT chambers and L/S indicate whether they are in Large or Small sectors.
Efficiency to reconstruct an MS DV in the MS barrel fiducial volume as a function of the transverse decay position of the LLP for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, MDT 1/2 represent the first/second stations of MDT chambers and L/S indicate whether they are in Large or Small sectors.
Efficiency to reconstruct an MS DV in the MS endcaps fiducial volume as a function of the longitudinal decay position of the LLP for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, MDT 1/2 represent the first/second stations of MDT chambers and L/S indicate whether they are in Large or Small sectors.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi = 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Efficiency to reconstruct an MS DV in the MS fiducial volume as a function of the LLP boost and decay position for a scalar portal sample with $m_\varPhi \ne 125$ GeV for vertices that pass the baseline event selection (except for the trigger) and satisfy the vertex isolation criteria. The efficiency distributions are corrected for mismodeling.
Expected and observed 95% CL limits on ($\sigma / \sigma_{\text{SM}}) \times B$ for $m_\phi=125$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Expected and observed 95% CL limits on ($\sigma / \sigma_{\text{SM}}) \times B$ for $m_\phi=125$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Expected and observed 95% CL limits on ($\sigma / \sigma_{\text{SM}}) \times B$ for $m_\phi=125$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Expected and observed 95% CL limits on $\sigma \times B$ for $m_\phi=60$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Expected and observed 95% CL limits on $\sigma \times B$ for $m_\phi=60$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Expected and observed 95% CL limits on $\sigma \times B$ for $m_\phi=200$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Expected and observed 95% CL limits on $\sigma \times B$ for $m_\phi=400$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Expected and observed 95% CL limits on $\sigma \times B$ for $m_\phi=600$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Expected and observed 95% CL limits on $\sigma \times B$ for $m_\phi=600$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Expected and observed 95% CL limits on $\sigma \times B$ for $m_\phi=600$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Expected and observed 95% CL limits on $\sigma \times B$ for $m_\phi=1000$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Expected and observed 95% CL limits on $\sigma \times B$ for $m_\phi=1000$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
Expected and observed 95% CL limits on $\sigma \times B$ for $m_\phi=1000$ GeV assuming 100% branching fraction of the long-lived scalar into fermion pairs.
This paper presents results of searches for electroweak production of supersymmetric particles in models with compressed mass spectra. The searches use 139 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider. Events with missing transverse momentum and two same-flavor, oppositely charged, low transverse momentum leptons are selected, and are further categorized by the presence of hadronic activity from initial-state radiation or a topology compatible with vector-boson fusion processes. The data are found to be consistent with predictions from the Standard Model. The results are interpreted using simplified models of $R$-parity-conserving supersymmetry in which the lightest supersymmetric partner is a neutralino with a mass similar to the lightest chargino, the second-to-lightest neutralino or the slepton. Lower limits on the masses of charginos in different simplified models range from 193 GeV to 240 GeV for moderate mass splittings, and extend down to mass splittings of 1.5 GeV to 2.4 GeV at the LEP chargino bounds (92.4 GeV). Similar lower limits on degenerate light-flavor sleptons extend up to masses of 251 GeV and down to mass splittings of 550 MeV. Constraints on vector-boson fusion production of electroweak SUSY states are also presented.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
A search for Higgs boson pair production in events with two $b$-jets and two $\tau$-leptons is presented, using a proton-proton collision dataset with an integrated luminosity of 139 fb$^{-1}$ collected at $\sqrt{s}=13$ TeV by the ATLAS experiment at the LHC. Higgs boson pairs produced non-resonantly or in the decay of a narrow scalar resonance in the mass range from 251 to 1600 GeV are targeted. Events in which at least one $\tau$-lepton decays hadronically are considered, and multivariate discriminants are used to reject the backgrounds. No significant excess of events above the expected background is observed in the non-resonant search. The largest excess in the resonant search is observed at a resonance mass of 1 TeV, with a local (global) significance of $3.1\sigma$ ($2.0\sigma$). Observed (expected) 95% confidence-level upper limits are set on the non-resonant Higgs boson pair-production cross-section at 4.7 (3.9) times the Standard Model prediction, assuming Standard Model kinematics, and on the resonant Higgs boson pair-production cross-section at between 21 and 900 fb (12 and 840 fb), depending on the mass of the narrow scalar resonance.
The electroweak production of $Z(\nu\bar{\nu})\gamma$ in association with two jets is studied in a regime with a photon of high transverse momentum above 150 GeV using proton-proton collisions at a centre-of-mass energy of 13 TeV at the Large Hadron Collider. The analysis uses a data sample with an integrated luminosity of 139 fb$^{-1}$ collected by the ATLAS detector during the 2015-2018 LHC data-taking period. This process is an important probe of the electroweak symmetry breaking mechanism in the Standard Model and is sensitive to quartic gauge boson couplings via vector-boson scattering. The fiducial $Z(\nu\bar{\nu})\gamma jj$ cross section for electroweak production is measured to be 0.77$^{+0.34}_{-0.30}$ fb and is consistent with the Standard Model prediction. Evidence of electroweak $Z(\nu\bar{\nu})\gamma jj$ production is found with an observed significance of 3.2$\sigma$ for the background-only hypothesis, compared with an expected significance of 3.7$\sigma$. The combination of this result with the previously published ATLAS observation of electroweak $Z(\nu\bar{\nu})\gamma jj$ production yields an observed (expected) signal significance of 6.3$\sigma$ (6.6$\sigma$). Limits on anomalous quartic gauge boson couplings are obtained in the framework of effective field theory with dimension-8 operators.
A search for flavour-changing neutral current (FCNC) $tqH$ interactions involving a top quark, another up-type quark ($q=u$, $c$), and a Standard Model (SM) Higgs boson decaying into a $\tau$-lepton pair ($H\rightarrow \tau^+\tau^-$) is presented. The search is based on a dataset of $pp$ collisions at $\sqrt{s}=13$ TeV that corresponds to an integrated luminosity of 139 fb$^{-1}$ recorded with the ATLAS detector at the Large Hadron Collider. Two processes are considered: single top quark FCNC production in association with a Higgs boson ($pp\rightarrow tH$), and top quark pair production in which one of the top quarks decays into $Wb$ and the other decays into $qH$ through the FCNC interactions. The search selects events with two hadronically decaying $\tau$-lepton candidates ($\tau_{\text{had}}$) or at least one $\tau_{\text{had}}$ with an additional lepton ($e$, $\mu$), as well as multiple jets. Event kinematics is used to separate signal from the background through a multivariate discriminant. A slight excess of data is observed with a significance of 2.3$\sigma$ above the expected SM background, and 95% CL upper limits on the $t\to qH$ branching ratios are derived. The observed (expected) 95% CL upper limits set on the $t\to cH$ and $t\to uH$ branching ratios are $9.4 \times 10^{-4}$ $(4.8^{+2.2}_{-1.4}\times 10^{-4})$ and $6.9\times 10^{-4}$ $(3.5^{+1.5}_{-1.0}\times 10^{-4})$, respectively. The corresponding combined observed (expected) upper limits on the dimension-6 operator Wilson coefficients in the effective $tqH$ couplings are $C_{c\phi} <1.35$ $(0.97)$ and $C_{u\phi} <1.16$ $(0.82)$.
A generic search for resonances is performed with events containing a $Z$ boson with transverse momentum greater than 100 GeV, decaying into $e^+e^-$ or $\mu^+\mu^-$. The analysed data collected with the ATLAS detector in proton-proton collisions at a centre-of-mass energy of 13 TeV at the Large Hadron Collider correspond to an integrated luminosity of 139 fb$^{-1}$. Two invariant mass distributions are examined for a localised excess relative to the expected Standard Model background in six independent event categories (and their inclusive sum) to increase the sensitivity. No significant excess is observed. Exclusion limits at 95% confidence level are derived for two cases: a model-independent interpretation of Gaussian-shaped resonances with the mass width between 3% and 10% of the resonance mass, and a specific heavy vector triplet model with the decay mode $W'\to ZW \to \ell\ell qq$.
Results of applying the BH algorithm to the mass spectra in the leading small-R jet category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the leading bjet category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the leading large-R jet category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the leading photon category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the leading electron category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the leading muon category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the leading small-R jet category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the leading bjet category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the leading large-R jet category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the leading photon category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the leading electron category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the leading muon category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the inclusive category, using the fitted background estimations from the initial step
Results of applying the BH algorithm to the mass spectra in the inclusive category, using the fitted background estimations from the initial step
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading small-R jet category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading bjet category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading large-R jet category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading photon category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading electron category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading muon category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading small-R jet category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading bjet category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading large-R jet category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading photon category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading electron category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading muon category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the inclusive category
Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the inclusive category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading small-R jet category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading bjet category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading large-R jet category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading photon category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading electron category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading muon category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading small-R jet category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading bjet category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading large-R jet category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading photon category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading electron category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading muon category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the inclusive category
Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the inclusive category
Acceptance times efficiency in an HVT model as a function of mass in the leading large-R jet category
Upper limits at 95% CL on the cross section times the branching fraction($W^{\prime} \to ZW$) for the HVT signal as functions of mass($m_{ZX}$) in the leading large-R jet category.The full(dashed) red curves correspond to the theoretical predictions of HVT model A(B)
Comparison of the identification efficiencies using standard and merged-ee reconstruction as a function of true PT(Z)
Background rejection factor as a function of signal efficiency. The red curve shows the BDT performance whereas the blue curve corresponds to that of a cut-based analysis relying only on the jet energyfraction deposited in the EM calorimeter
BH p-values of the 100 pseudo-experiments as a function of in the leading small-R jet category for an injected Gaussian-shaped signal with a relative width value of 3%. The fractions of the pseudo-experiments that have the correctly identified interval and BH p-values below the threshold of 0.01 are indicated. The background is derived by the background-only fit in the full fitting range.
BH p-values of the 100 pseudo-experiments as a function of in the leading small-R jet category for an injected Gaussian-shaped signal with a relative width value of 3%. The fractions of the pseudo-experiments that have the correctly identified interval and BH p-values below the threshold of 0.01 are indicated. The background is derived by the background-only fit in the range excluding the BH interval.
Fractions of pseudo-experiments in which the detected BH interval agrees with the injected mass point and the BH p-value is below 0.01 as a function of mass in the leading small-R jet category for Gaussian-shaped signal with a relative width of 3%.
Fractions of pseudo-experiments in which the detected BH interval agrees with the injected mass point and the BH p-value is below 0.01 as a function of mass in the leading small-R jet category for Gaussian-shaped signal with a relative width of 3%.
Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 3% at the low boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.
Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 3% at the high boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.
Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 5% at the low boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.
Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 5% at the high boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.
Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 10% at the low boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.
Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 10% at the high boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.
Data yields of the six event categories in the $Z\to e^+e^-$ and $\mu^+\mu^-$ decay channels. The merged-$e^+e^-$ events are included in the $e^+e^-$ channel, increasing the event yield, mainly in the leading large-$R$-jet category, by 0.6 %.
A list of mass spectra, event categories and their corresponding fit ranges, functional forms, numbers of free parameters and global $\chi^2$ $p$-values from background-only fits. The fit range values are rounded to the nearest 5 GeV. Here $f_1(x)=p_0\left(\mathrm{e}^{-p_1x}+p_2\mathrm{e}^{-(p_1+p_3)x}+p_4\mathrm{e}^{-(p_1+p_3+p_5)x}+\cdots\right)$ and $f_2(x)=p_0(1-x)^{p_1}x^{p_2+p_3\ln\!x+p_4\ln^2\!x+\cdots}$
A list of mass spectra, event categories and their corresponding signal-sensitive mass ranges. The initial BH $p$-value is obtained by using the background derived from the background-only fit in the full fit range, whereas the new BH $p$-value uses the background derived from the background-only fit in the range excluding the initial BH interval.
A list of mass spectra, event categories, relative width values of Gaussian-shaped signals and limit-sensitive mass ranges and fractions, corresponding to the mass values in the previous column, of pseudo-experiments having exclusion upper limits higher than the nominal exclusion limit at 95% CL
Cutflow of HVT model $A$ signals ($W^\prime \to ZW \to \ell\ell qq$) with $m_{W^\prime} = 1$ TeV and $m_{W^\prime} = 4$ TeV based on MC simulations.
Acceptance times efficiency ($\mathcal{A} \times \epsilon$) values in % in the dominant event category for $p^Z_{\mathrm{T}} > 100$ GeV in the $Z \to \ell^{+}\ell^{-}$ decay channel.
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